System and method for health evaluation

A system, an apparatus and a method for human health evaluation utilizing Thermal Micro Texture (TMT) mapping technology is disclosed. The method comprises scanning body areas of a patient utilizing an infrared camera, detecting abnormalities in the body of the patient, analyzing abnormalities of the patient against information stored in a database, and reporting results to the patient in a pre-determined format. The method provides an earlier discovery of disease by mapping and analyzing abnormal temperatures changes in the body, which can help prevent the disease from progressing at an early stage.

COPYRIGHT NOTICE

A portion of the disclosure of this patent application contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent application or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever.

BACKGROUND OF THE INVENTION

CAT scans, MRIs, and other traditional diagnostic techniques use X-rays, which are harmful to the human body. High energy radiation X-rays emitted by CAT scans and MRIs that are used to diagnose diseases cause damage to cells in the body. The risk of developing cancer from one X-ray procedure may be low, but the risk increases with each subsequent X-ray test a patient undergoes. Additionally, CAT scans and MRIs have limitations when used to diagnose diseases. Although these procedures are used to identify structural physical changes in the body, they are often not capable of diagnosing a disease when it is in its early stage.

SUMMARY OF THE INVENTION

The human health evaluation system utilizing Thermal Micro Texture (TMT) mapping technology, according to the present invention, departs from the conventional concepts and designs of the prior art, and in doing so, provides a means to detect structural physical changes and functional physiological changes in the body to provide an earlier discovery of a disease by mapping and analyzing abnormal temperatures changes in the body. In one embodiment, human health evaluation system (hereinafter referred to as “TMT system” or “health evaluation system”) utilizes TMT mapping technology for diagnosing human illness at an early stage without exposing a patient to harmful rays.

In one embodiment, a health evaluation system includes a thermal imaging device to capture a thermal image of a human anatomy and a medical analysis rules library database for storing a set of rules to perform a thermal mapping and automatic zoning analysis. The database includes significant number of patients' clinical data files, which provide a stable platform for comparison and analysis. The system also includes a processor, wherein the processor is coupled to the thermal imaging device and configured to apply the thermal mapping and automatic zoning analysis to the thermal image to create thermal zones and to calculate a temperature distribution for each thermal zone. The processor is further configured to automatically evaluate and determine a health condition of the human anatomy based on a comparison between the temperature distribution for each thermal zone and at least one of a particular temperature range, a distribution, and a corresponding symmetry to said each thermal zone. The processor is configured to utilize thermal mapping and vectorization techniques. The processor is further configured to evaluate a human respiratory system abnormalities, otorhinolaryngological abnormalities, cardiovascular system abnormalities, reproductive system abnormalities, respiratory system abnormalities, digestive system abnormalities, urinary system abnormalities, endocrine system abnormalities, and lymphatic system abnormalities.

In another embodiment, an apparatus for a human health evaluation is disclosed wherein the apparatus includes means for capturing a thermal image of a human anatomy, means for applying thermal mapping and automatic zoning analysis to the thermal image to create thermal zones, means for calculating a temperature distribution for each thermal zone, and means for automatically evaluating and determining the health condition of the human anatomy based on a comparison between the temperature distribution for each thermal zone and predefined criteria for evaluation selected from a medical analysis rules library database to said each thermal zone. The apparatus further includes means for generating and displaying three-dimensional (3D) results related to the human anatomy to help diagnose a human illness.

In one embodiment, a computer program product is disclosed. The computer program product includes a computer readable medium having instructions for causing a computer to receive a thermal image of a human anatomy, to apply a thermal mapping and automatic zoning analysis to the thermal image to create thermal zones, calculate a temperature distribution for each thermal zone, and automatically evaluate and determine a health condition of the human anatomy based on a comparison between the temperature distribution for each thermal zone and at least one of a particular temperature range, a distribution, and a corresponding symmetry, from a medical analysis rules library database to said each thermal zone.

In another embodiment, a system and method for health evaluation utilizing TMT mapping technology is disclosed. The health evaluation system includes a client system, a centralized database for storing information, and a server system configured to be coupled to the client system and the centralized database. The server system is further configured to measure temperature data at various points of a patient's body utilizing an infrared camera, to process temperature data, and to map and analyze temperature data against information stored in the centralized database. The system is further capable of reporting results in a predetermined format including clinical information, thermal images and all corresponding analysis relating to the thermal images. The server system includes a medical records management module, an image collection management module, an image processing and analysis module, a report output module, a thermal image comparison module, and a cascade chromatography module.

The software utilized in the health evaluation system includes various independent yet integrated modules. The software is capable of managing a patient's medical records, analyzing, printing and storing the patient's thermal images, comparing the patient's thermal images to other patients' information stored in the database, and converting static thermal images into dynamic thermal images through cascade chromatography.

The health evaluation system produces three dimensional data and images. The different colors represent different temperature areas of the human body or parts of the body that are scanned. The health evaluation system is capable of scanning more than the surface area of a patient. The TMT mapping technology identifies abnormal heat sources deep within the body, including abnormalities from tissues and organs, blood vessels, and heat sources under hair, which help pin-point a location and cause of an illness or disease.

In one embodiment, a method for evaluating human health utilizing TMT mapping technology includes the steps of scanning body areas of a patient utilizing an infrared camera, detecting abnormal temperature changes in the body of the patient, mapping and analyzing abnormal temperature changes in the body of the patient against information stored in a centralized database, evaluating health condition of the patient, and reporting results to the patient in a pre-determined format. Another embodiment includes capturing a thermal image of a selected human anatomy area of a patient, applying a thermal mapping and automatic zoning analysis to the thermal image to create thermal zones, calculating a temperature distribution for each thermal zone, and automatically evaluating and determining the health condition of the patient based on a comparison between the temperature distribution for each thermal zone and at least one of a particular temperature range, a distribution, and a corresponding symmetry, from a medical analysis rules library database to said each thermal zone.

In yet another embodiment, a computer program for fitness evaluation embodied on a computer readable medium is disclosed. The computer program is capable of evaluating human fitness by performing a Qi (flow) evaluation process, a thermal muscle metabolism evaluation process, a fat mapping evaluation process, a thermal microcirculation metabolism evaluation process, an anatomical structures and systems evaluation process, a muscle endurance evaluation process, and a psychological evaluation process.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments described herein relate to methods and systems of structuring the infrared software, mapping, processing, analysis, data-sharing, and work-flow systems. Methods and structures of the system are not limited to the specific embodiments described herein. Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

In one embodiment, a system and method for health evaluation utilizing Thermal Micro Texture (TMT) mapping technology is disclosed (hereinafter referred to as “the TMT system” or “health evaluation system”). The TMT system detects and maps changes in the body's temperature by analyzing the infrared rays emitted by the body in order to discover and diagnose early signs of an illness or disease.

When an individual undergoes a health check-up to detect early signs of a disease, he or she undergoes screening such as CAT scans or MRIs. The TMT system differs from these types of X-ray detection devices on four respects described below.

The first difference is that CAT scans, ultrasound X-rays, and MRIs (traditional techniques) generally provide structural checks reflecting changes in human tissue organs. In contrast, the TMT system reflects changes in an individual's human metabolism and blood circulation, or the body's change in temperature. The metabolism of cancerous tissue is the most active in the early phases of cancer. This cancerous tissue thereby produces a large amount of local surface heat and subsequently causes a change in the body surface temperature. Because of this, the TMT system enables the physician to diagnose and evaluate the source/cause of the variation or disease. The TMT system thereby enables early discovery of cancer.

The second difference is that traditional techniques, identified earlier, generally provide structural checks that reflect changes in human tissue structure. The TMT system tracks changes in the function and thermal radiation of a specific area of the body. These changes occur generally before changes to the tissue or organ structure. This allows the TMT system to detect signs of a disease while it is in the early stage. Hence, the TMT system acts as a preventive, rather than a reactive, system.

The third difference is that the TMT system avoids potential damage caused by X-rays. As discussed earlier, traditional techniques are known to expose the body to harmful radiation. Exposure to harmful rays does not occur when utilizing the TMT system because it does not make use of such harmful radiation techniques. Instead, the technology in the TMT system is set up to receive (and pinpoint) any heat energy that is emitted from the body. The TMT system does not produce any harmful radiation, thereby avoiding the risk of exposing an individual to harmful radiation.

Finally, the TMT system provides a procedure which is convenient, quick, and cost-effective compared to other systems.

FIG. 1illustrates a conventional electromagnetic spectrum distribution. The infrared ray portion of the electromagnetic spectrum distribution is expanded and shown following a visible light range. The visible light range includes violet, blue, green, yellow, orange, and red colors. The visible light range is followed by the infrared ray range, which includes a near infrared range, a mid infrared range, a far infrared range, and a very far infrared range. The infrared ray is a kind of ray invisible to the human eye, in the spectrum beyond the visible red light. The infrared ray range is comprised of electromagnetic radiation in the wavelength interval 0.76 μm˜1000 μm, connected to visible light at the lower end and millimeter wave at the higher end. The visible light range is 0.4 μm˜0.76 μm and is considerably narrower than the wide infrared ray range (0.76 μm˜1000μ).

Infrared (IR) rays are also known as heat rays or thermal radiation. Although different in form, the infrared ray, the visible light, and the radio wave are the same in essence, all being part of electromagnetic radiation, only differing in frequency (wavelength). Infrared rays have the same properties as other light waves: linear propagation in a vacuum and follow the laws of reflection, refraction, diffraction and polarization.

There are three laws which describe the radiation. The three laws include the Planck Law, the Stephan-Boltzmann Law, and the Wien Displacement Law. The Planck Law, in general, describes the spectral distribution of blackbody radiation. The Stephan-Boltzmann Law describes the total power radiated from an object in a unit area. According to the Stephan-Boltzmann Law, the higher the absolute temperature, the greater the radiant existence. According to the Wien Displacement Law, the wavelength of infrared radiation of an object relates to its temperature. Thus, the higher the absolute temperature, the shorter the radiation wavelength, and vice versa.

The TMT system provides functional checks reflecting changes in human metabolism and blood circulation. Such changes are expressed through human thermal micro-sectional view technology. X-ray, CAT Scans, Ultrasonic B, and nuclear magnetic resonance technologies provide structural checks reflecting changes in human tissue structure. The two kinds of checks are complementary to, but not replaceable by, each other.

FIG. 2illustrates a flow diagram of one embodiment of a TMT mapping technology health evaluation process10. Health evaluation process10allows a user to create or load a patient file at block12or retrieve patient file at block12from a database or a computer readable medium denoted by block24. Once the patient file is created or loaded at block12, the desired scan type is selected (created or loaded) at block14for capturing an infrared image capture at block16.

The scan type is made up of sets of predefined infrared positional images (shown inFIGS. 21A-21R) of the human anatomy, which are specific to the type of evaluation scan to be performed. In one embodiment, the scan type can be retrieved from the database or computer readable medium denoted by block24or loaded from memory/sharing zone denoted by block26. Following the loading of the scan type, infrared images are captured or collected at block16in order to provide health evaluation system40(shown inFIG. 3) with infrared data to process and evaluate. Once the infrared images are captured at block16, image processing is performed at block18. The image processing at block18is accomplished through several software modules, further described below inFIG. 4, which enable the user to enhance the raw infrared data for manual and automated use. Block18is followed by block20where auto-analysis takes place. The auto-analysis operation at block20receives the refined data from block18, after image processing has been completed. The auto-analysis includes the processing of the data against a rule-set corresponding to the selected scan type to determine the health of the patient in regards to the selected scan type. After the auto-analysis at block20, an output report is generated at block22with results of the auto-analysis on the infrared scan. The data for the patient file, scan type, infrared image capture, image processing, auto-analysis, and report output may be loaded and stored utilizing the database or computer readable medium denoted by block24and the memory/sharing zone denoted by block26.

In an alternate embodiment, health evaluation process10may omit certain blocks or steps illustrated inFIG. 2. For example, block16to capture or collect the infrared image may be omitted if pre-captured infrared images are used or a scan type which does not require the capture of new positional infrared images is used. Block20for performing auto-analysis may also be omitted if health irregularities are determined manually.

FIG. 3illustrates a general block diagram of system components of a health evaluation system40. Health evaluation system40includes, in general, a control panel52to operate and manage an infrared camera42. Control panel52transmits instructions to a processor44, as necessary. Infrared camera42captures an infrared image and communicates the infrared image to processor44. The captured infrared image is initial raw data. Processor44communicates the initial raw data to a database or computer storage medium46for storage therein and subsequent retrieval.

Control panel52is configured to send a command to instruct processor44to process the initial raw data according to methods described inFIGS. 7-10, and to store the processed data in a database or computer storage medium46. In addition, control panel52is also capable of sending a command to instruct processor44to auto-analyze the processed image data according to rule-sets, as described in more detail below, retrieved from database or computer readable medium46. Image data and results are also available to be displayed on a client system (not shown) or output to multiple media output devices48including, but not limited to, display monitors, computers, web pages, email, fax machines, and printers.

Database or computer readable medium46includes a TMT technology module50for carrying out health evaluation process10. Module50includes instructions and rule-sets for performing health evaluation process10. Module50includes at least the rule-set for auto-analyzing the processed image data, as well as the TMT graphical user interfaces (FIGS. 22-39) for allowing the user to interact with health evaluation system40for carrying out health evaluation process10.

In one embodiment, database or computer readable medium46stores all of the system information including raw infrared image data, processed infrared image data, auto-analysis results, and reports. In another embodiment, however, database or computer readable medium46may also be split into multiple databases, each database storing its own set of specific data. In yet another embodiment, a computer may act as multiple components as shown inFIG. 3.

FIG. 3Aillustrates a network diagram depicting a multi-modal data sharing system. In one embodiment, multiple systems40all over the world are linked to a central database. The central database contains patient information and analysis from external linked systems40all over the world. When a local network linked system40gathers and analyzes data from a patient, the data is sent to the central database. At the central database, central processing control sends information to the information analysis and diagnosis center. The information analysis and diagnosis center compares the patient information gathered from local system40against information in the central database of patients with similar TMT mappings. Based on comparison with the previously diagnosed patients, the information analysis and diagnosis center determines the illness of the patient scanned at local system40.

FIG. 4illustrates a general block diagram of module50of health evaluation system40(shown inFIG. 3). Module50has generally three layers: an application layer100, a database management layer102, and a database layer104. Application layer100is made up of a common memory or sharing zone26for which data between modules is shared and accessed. Application layer100includes a medical records module (MRM)80, an image collection module (ICM)82, an image processing and analysis module (IPAM)84, a report output module (ROM)86, a thermal image comparison module (TICM)88, a sectional view module90, and an automatic analysis module (AAM)92. These modules are further described and depicted inFIGS. 5-13. As illustrated inFIG. 2andFIG. 3, data for each module may be stored in a database or a computer readable medium98. A database management component94identifies the module request to store or retrieve information and routes the request to database98if the module request is valid. Through database management component94, the modules exchange information, data disk files etc. among each other. At database layer102, the generation, retrieval, and addition of medical records take place. Database layer104stores such information as the basic medical information, additional medical information, image file index information, and temperature measurements of patients.

MRM80includes, for each patient, basic and clinical information which is saved and managed in database98. The medical history, present condition of the patient, etc. can be readily accessed and retrieved from database98.

ICM82includes, for each patient, infrared information obtained through scanning or image capturing. The infrared information is also saved and stored in database98. ICM82converts the infrared information into color images and displays them onto a suitable user interface such as a display monitor.

IPAM84allows a user to manipulate a patient's three-dimensional images so as to most effectively depict the thermal distribution. The user can also make a comprehensive analysis of the thermal images using different functions. Completed analysis is saved in the database and may be retrieved at a later date for future comparison.

ROM86allows the user to print out the records of a patient, including all clinical information, thermal images, and corresponding analysis utilizing the various features of ROM86.

TICM88allows the user to compare the same bodily areas of different patients and their corresponding body area temperatures. Because database98is capable of saving and storing a large number of patients' thermal images, the user can utilize different options to compare the same bodily areas of different patients for various data sets of information.

Module90is also referred to as the cascade chromatography module (CCM). CCM allows dynamic temperature changes of a patient's thermal image to be converted into a static form through cascade chromatography of the thermal image, as described later in relation toFIGS. 40A,40B, and40C.

Health evaluation system40(shown inFIG. 3) is capable of automatically analyzing the infrared images using artificial intelligence with reference to the results generated by various modules including, but not limited to, modules82,84,86,88, and90. The system is capable of storing the sectional views of the patients' data and medical analysis rules, and also storing final analysis results.

As can be appreciated, to describe each and every request, storage, and retrieval operation is prohibitive. Thus, one example is described below. In one embodiment, ICM82sends a request to store new infrared images captured for a patient. Database management component94stores the new infrared images in a raw infrared thermal images database96. Other information pertaining to other modules, such as ROM86, may store and retrieve its information from another database98.

FIG. 5illustrates a flow diagram depicting MRM80. MRM80can create a new patient record by collecting patient data at block120(via hand-written forms or questionnaires, etc.) including information such as the patient's name, date of birth, case history, family history, and symptoms. Graphical user interfaces (GUI) as shown inFIGS. 22-29allow a user to enter the patient's information into data entry fields of the GUI. Block120is followed by block122where the collected patient data is input or entered for processing. During the operations of block122, the electronic processing of patient data assigns the patient a medical record index for storage and retrieval using a database132.

Block124provides for a patient data query. If the patient already has a medical record, then a patient data query can be generated at block124. Block124is followed by block126where the query is processed and medical records (previously stored) are retrieved from the database132. Patient data queries of block124are not limited to retrieval of records for a single patient. Thus, patient data queries can include population studies of a pool of patients for clinical studies use. Once the desired medical record(s) are retrieved from block126, the medical record(s) can be output as raw data via a direct medical record(s) output at block128, or as a formatted medical record report output at block130. The medical record output generated at block128and medical record report generated at block130can be output to multiple media formats, including electronic and hard-copy forms. Information collected from the electronic processing of patient data at block122and retrieval of medical records at block126is also sent to memory or sharing zone26for access by other modules.

FIG. 6illustrates a flow diagram depicting ICM82. An infrared camera42is controlled through a communications interface180, which sends control signals and receives infrared data. Infrared camera42is demarcated in a dashed-line box to denote separation from ICM82. ICM82includes a communications interface denoted at block180, which is driven by a camera control denoted at block184through an infrared equipment driver denoted at block182.

In one embodiment, a computer may act as the camera control at block184, using a software version of infrared equipment driver182to control infrared camera42through communications interface at block180. By way of example, communications interface at block180may be a universal serial bus connection. When infrared equipment driver at block182is given a command to perform an infrared data capture operation at block186, an infrared image display at block188is generated and output to a display device such as a monitor. Infrared data capture at block186is also sent to memory or sharing zone26for access by other modules. Infrared data captured at block186is also stored in database46. In one embodiment, database46can be its own dedicated database to store infrared images, whereas in another embodiment, database46may be utilized to store all relevant information relating to health evaluation system40(shown inFIG. 3).

FIG. 7illustrates a flow diagram depicting IPAM84. IPAM84is one of the modules which make up image processing operation of block18(shown inFIG. 2). IPAM84begins with block200where a function selection module is linked to a database222and memory or sharing zone26. IPAM84retrieves infrared images and other related information from database222for processsing. Block202performs a function selection to determine how the infrared image data is manipulated. The available options for the function selection are a noise processing function at block204, a color scheme selection function at block206, a temperature adjustment function at block208, a temperature measurement function at block210, a temperature layer analysis function at block212, and an option to save changes function at block214.

The noise processing function at block204is an automated process which filters out irrelevant background infrared data that may be present in the captured infrared image. The color scheme selection function at block206allows for the selection or specification of color palettes which are used to display infrared images. The temperature adjustment function at block208allows for the specification of an upper and lower range of temperature values that is displayed by colors from the color scheme selection function at block206. The temperature measurement function at block210allows temperature measurement of points, rectangles, ellipses, and polygons of parts of an infrared image. The temperature measurement function at block210provides values which can also be saved. The temperature layer analysis function at block212allows the system to determine the depth of global or local temperature areas of a patient's body.

Aside from saving changes at block214, when one of the other functions is selected, an infrared image display at block218is updated to reflect the processed image. Each of the blocks204,206,208,210, and212proceed to block218. Block218is followed by memory or sharing zone26. Such changes to the infrared image are then sent to memory or sharing zone26to be used by other modules or downloaded to database222. IPAM84can also save changes via the save changes function at block214to a data file216in a standard format (e.g. BMP, JPG, etc.).

FIG. 8illustrates a flow diagram depicting TICM88. TICM88is one of the modules which makes up the image processing at block18(shown inFIG. 2). TICM88begins with block240where a function selection module is linked to a database260and memory or sharing zone26to provide it with thermal images to compare. Block240is followed by block242where a function selection takes place to determine how the infrared image data is manipulated and compared. The available options are a thermal image selection function at block244, a temperature adjustment function at block246, a color scheme selection function at block248, an area selection function at block250, a print results function at block252, a save results function at block254coupled to a data file256and database260.

The thermal image selection function at block244allows multiple thermal images to be selected for comparison. These thermal images can be from the same or different patients, from the same or different time periods, or from the same or different image capture positions. The color scheme selection function at block248allows for the selection or specification of color palettes with which to represent infrared images. The temperature adjustment function at block246allows for the specification of an upper and lower range of temperature values that can be displayed by colors from the color scheme selection function at block248. The area selection function at block250allows for a selection of points or areas of thermal images to be compared by temperature, and have such comparisons recorded for analysis. The print results function at block252creates a visual report showing the areas compared and the results of the comparison. The save results function at block254saves the temperature comparison results into database260or data file256. Except for the print results function at block252and save results function at block254, when one of the other functions is selected, a comparison results display at block258is updated to reflect the comparison results. Such changes to the infrared image are then sent to memory or sharing zone26to be used by other modules or written to a database260. Thus, blocks244,246,248,250, and254are followed by block258. Block258is followed by memory or sharing zone26.

FIG. 9illustrates a flow diagram depicting module90. Module90is one of the modules which makes up the image processing at block18inFIG. 2. Module90begins with block280. A function selection module at block280is linked to a database300and memory or sharing zone26to provide it with thermal images to compare. Block280is followed by a function selection at block282to determine how the infrared image data is manipulated and displayed. In one embodiment, block282allows the user to select one or more of the five different options. The available options are a temperature range selection function at block284, a temperature accuracy selection function at block286, a color scheme selection function at block288, an area selection function at block294, and a save results function at block296.

The color scheme selection function at block288allows for the selection or specification of color palettes with which to represent infrared images. The temperature range selection function at block284allows for the specification of an upper and lower range of temperature values to be displayed by colors selected from the color scheme selection function at block288. The temperature accuracy selection function at block286specifies the temperature precision between layers of thermal sectional views. The area selection function at block294allows an area to be highlighted for focus (in color) while the rest of the image is displayed as gray. Use of the option of the area selection function at block294forces an update to a section view display at block292. The section view display at block292can be output to a variety of devices or shown within an application interface. A sectional view option at block290generates sectional views utilizing specified or default values of temperature range, temperature accuracy, and color scheme values. The generation of these sectional images is described in further detail inFIG. 10. The section view display at block292shows the generated sectional views and transfers this data to memory or sharing zone26before being stored in a database300. The save results function at block296saves all or parts of the sectional view thermal images as common graphic formats (e.g. JPEG, BMP, etc.) in a data file298. The blocks284,286, and288are followed by the sectional view option at block290. Block290is followed by block292. The results display at block292is followed by memory or sharing zone26.

FIG. 10illustrates a flowchart depicting a sectional view option process310(shown in block290ofFIG. 9). In the initial step of generating a sectional view, the maximum temperature (Tmax), minimum temperature (Tmin), and precision values (PV) are set at block320. In block322, the infrared data (t) is converted into color pixels according to the specified color scheme fromFIG. 9. Any t values which exceed the Tmax value are assigned a color value equal to black. Any t values which fall under the Tmin value are assigned a color value equal to white. Otherwise, the t value is assigned a color corresponding to its temperature. This process generates a false color image which is then displayed in block324. To create the next sectional view, the bounds Tmax and Tmin are narrowed by the specified precision value in block326. Block328checks if Tmax is less than Tmin. If Tmax has been reduced to a value less than Tmin, sectional view option process310ends since there is no more precision to extract from the infrared image. Otherwise, process310loops back to block322with a new set of Tmax and Tmin values to generate a new sectional view.

FIGS. 11A and 11Billustrate a flowchart describing automatic analysis module92(shown inFIG. 4). Automatic analysis module92utilizes a thermal mapping technique which allows the system to determine the overall health of a patient by examining relevant parts of a thermal scan. Automatic analysis module92begins at block360where thermal mapping and automatic zoning is applied to a patient's thermal images. The thermal mapping and automatic zoning is described in further detail inFIG. 12. After the zoning of infrared images is complete at block360, the temperature distribution is calculated for each zone at block362. Block362is followed by block364, where health evaluation system40(shown inFIG. 3) retrieves a desired rule-set364from a medical analysis rule library database366, and runs rule-set comparisons at block368. Such rule-set comparisons may involve rules that determine the health of a patient given a variety of factors including, but not limited to, how a patient's thermal zones relate to a particular temperature range, distribution, or symmetry.

Referring now toFIG. 11B, block368(shown inFIG. 11A) is followed by block370. At block370, a determination is made whether the patient is healthy. If the determination is “No” at block370(i.e., the patient is not healthy), health evaluation system40(shown inFIG. 3) attempts to determine the extent of the unhealthy condition(s) at block372. Block372is followed by block374. If the determination at block370is “Yes” (i.e., that the patient is healthy), then block370is followed by block374where (healthy or unhealthy) analysis results are processed. Block374forwards the analysis results to memory or sharing zone26for access by other modules or to a database376.

FIG. 12illustrates a flowchart describing a process399for thermal mapping and automatic zoning at block360(shown inFIG. 11A). Process399for thermal mapping and automatic zoning is described in relation to the illustrations ofFIGS. 13A,13B,13C,14,15A,15B,16A,16B,17A,17B,18,19A,19B, and19C.FIG. 13Aillustrates an example of an infrared thermal image.FIG. 13Billustrates an example of the human body in the infrared thermal image ofFIG. 13Aremoved.FIG. 13Cillustrates an example of an outline created of the human body in the infrared thermal image ofFIG. 13A.FIG. 14illustrates a point d in an image and direction codes of its eight neighbors.FIG. 15Aillustrates points of a profile image.FIG. 15Billustrates a vectorization of the profile image.FIGS. 16A and 16Billustrate a flowchart of a process450for vectorization of profile points.

FIGS. 19A,19B, and19C illustrate a depiction of the thermal mapping process at different stages ofFIG. 12.

The process399(shown inFIG. 12) for thermal mapping and automatic zoning begins at block400where loading an infrared image, such as shown inFIG. 13A, takes place. The infrared image is processed into mathematical data such that the image can be compared against a standard template and mapped into zones. Examples of zones are shown inFIGS. 17A,17B, andFIG. 18.FIGS. 17A and 17Billustrate an innervation-based zoning template for a front and back view of the human anatomy andFIG. 18illustrates a facial zoning template. Once the infrared image is loaded at block400and the human profile is mapped at block401, the infrared image is vectorized at block402. The infrared image is vectorized to create a vectorized human profile represented in the infrared image, as shown inFIG. 15B.

Once the human profile image is vectorized, at block402, the locations of characteristic reference points are determined at block404. InFIGS. 17A and 17B, the black dots represent characteristic reference points for the innervation-based zoning template for a front and back view of the human anatomy. The black dots inFIG. 18represent the characteristic reference points for the facial zoning template (SeeFIG. 19B). These characteristic reference points are common hot spots which can be found on every human. Once the characteristic reference points are found (SeeFIG. 19A), block404is followed by block406. At block406, a standard zoning template shown inFIGS. 17A and 17BorFIG. 18corresponding to the position code of the infrared image is retrieved. The position code references the image capture positions (also referred to as the “predefined infrared positional images” ofFIGS. 21A-21R). Block406is followed by block408where the standard template zones are scaled to match the infrared image using the characteristic reference points. Once the standard template zones, shown inFIG. 19Bare matched, block408is followed by block410, where the infrared image is divided into mapped zones, as shown inFIG. 19C.

The human infrared thermal mapping zoning involves image processing and mode identification technologies. The zoning is intended to automatically collect the temperatures of the respective zones on the human infrared thermal mapping and to help with medical statistics and diagnosis.

In light of the needs in medical research and clinical diagnosis, the infrared thermal image can be zoned from different medical perspectives, as from the perspectives of anatomy, innervation, and pains. Such zonings are based on a standard human body (anatomy). Each group of zones includes geometrical parameters like profiles, zoning lines, and positioning reference points.

FIGS. 17A and 17Billustrate an innervation-based zoning template for a front and back view of the human anatomy andFIG. 18illustrates a facial zoning template. The facial zoning template ofFIG. 18is based on diseases of the upper respiratory tract. Each template consists of profiles, geometrical zoning lines (shown inFIG. 19Cas white lines), and positioning reference points (shown inFIG. 19Aas white dots). All the parameters can be scaled up or down.FIGS. 17A,17B, and18, as well as other zoning templates, are used as standard zoning graphs (PPG).

The vectorization of the thermal image or human profile begins by capturing a human profile from a thermal image of the patient's body. The vectorial human profile is p from infrared thermal image (I) (where I can be a gray image). There are multiple algorithms for image profile capture. Although several different methods may be utilized, in one example, a threshold-gradient method is used.

The threshold-gradient method is utilized to separate the human body from the background in the thermal image, as shown inFIG. 13B. The threshold-gradient method can then be used to take the boundaries and vectorize them, as shown inFIG. 13B.

The threshold-gradient method is utilized to calculate a threshold V to take the human image in the infrared thermal image I, shown inFIG. 13A, according to equations Eq. (1a) and (1b) defined as

Image G inFIG. 13Bcan be obtained by equation Eq. (2) defined as:

G⁡(x,y)={1,∇⁢I⁡(x,y)≥V0,∇⁢I⁡(x,y)<VEq.⁢(2)
where image G is a two-valued image, of which the white part is 1 (i.e., G1), which covers the body area in the infrared thermal image I (FIG. 13A); and the black part is 0, corresponding to the background. The profile p can then be determined, as shown inFIG. 13C.

To determine the profile p, the following gradient operator G in equation Eq. (3) can be used to convolute G and to get boundary profile image P:

Sx=[-101-101-101]Sy=[-1-1-1000111]Eq.⁢(3)
where Sx and Sy stand for 3×3 convolution templates in the horizontal and vertical directions, and the convolution formula is shown in equations Eq. (4a), (4b), and (4c):

Next, vectorize the P(x,y) to get the body profile p.

As discussed earlier,FIG. 14illustrates a point d in an image and direction codes of its eight neighbors. The vectorization process is described in relation toFIGS. 14,15A,15B. The vectorization process begins by defining the direction denotation code, point d in the image, and the direction codes of its eight neighboring points as illustratedFIG. 14.

FIG. 15Aexemplifies the vectorization of a profile image P. After finding the first point from left to right and from top to down (i.e. bottom), in an counter-clockwise direction (consistent with the changes of the direction code), as shown inFIGS. 14,15A, and15B, vectorial parameters of the boundary profile are obtained. Examples of vectorial parameters are as given in Table 1. The SN 1 is denoted by Ptop and SN 8 is denoted by Pdown. Process450for vectorization of profile points is shown inFIGS. 16A and 16B, and explained below.

InFIG. 16A, process450begins at block452where X, Y, and I are all set to zero (0). The direction code (OC) is set to 3 in this example. However, the OC may change or may be assigned to a different value.

Block452is followed by block454where image points in the skeleton map within the field8of P(x,y) are searched. Block454is followed by block456where a determination is made whether points are found. If the determination is “Yes,” the down coordinates are acquired and noted for point(x,y). The direction code (OC) and Pxand Pyare defined by equations Eq. (5a), (5b) and (5c)
Px(i)=X;Eq. (5a)
Py(i)=Y; and  Eq. (5b)
Ifi>0pd(i−1)=OC.Eq. (5c)

InFIGS. 16A and 16B, X and Y stand for the change coordinates of image points, I for the record index of profile points found, and OC for the direction code corresponding toFIG. 14. The direction code OC changes counter-clockwise. The result of the direction code OC depends on the azimuth relation between the profile point found at a present and the last point (shown inFIGS. 15A and 15B).

Referring again to block456, if the determination is “No,” then X (the X coordinate) is incremented by one (1) at block460. Likewise, block458is followed by block460to increment X. Block460is followed by block462where a determination is made whether X is less than W−1 (width −1). If the determination is “Yes,” block462(shown inFIG. 16B) returns or loops back to block454(shown inFIG. 16A). However, if the determination is “No” at block462, then block462is followed by block464. At block464, X is set to 0 and the Y is incremented by one (1). Block464is followed by block466where a determination is made whether Y is less than H−1 (height −1). If the determination is “No,” process450ends. Otherwise, block466returns or loops back to block454.

The process for block406(shown inFIG. 12) relates to retrieving standard zoning templates corresponding to a position code. The position codes are attribute codes indicating body parts, arbitrarily defined for image collection of the infrared image. It is possible to control the program to take the characteristic positioning marks of the image. The i is an index serial number. From the thermal mapping, take position A(i) according to equation Eq. (6a) defined as
A(i)εG1Eq. (6a)

where A(i) is an element of the set of points in the human image zone, G1. A(i) includes the inner canthus, the upper fossa of the collarbone, the axilla, the umbilicus, the groin, and the lumbosacral portion, which are relatively warmer places in the human body called physiological hot zones. From the human profile, take special points B(i) according to equation Eq. (6b)
B(i)εpEq. (6b)

where B(i) is an element of the set of points in the vectorial human profile, p. B(i) includes points in the head top, the tip of the ear, the neck, the axilla, the femoral-genital joint, the wrist, the tips of the palm, the ankles, the toes, and the heel. Positions A and B may have a data structure comprising position coordinates and corresponding body zone attribute codes.

The process for block408(shown inFIG. 12) relates to scaling standard temperature zones to match infrared image utilizing characteristic reference points. After taking A(i) and B(i), the human infrared thermal mapping can be matched with standard zoning graphs (as shown inFIGS. 19A,19B, and19C). The process begins with selecting and retrieving a standard zoning graph PPG(i) from the database according to the zoning type and position code of the infrared image. A coordinate system CS of the infrared thermal mapping according to A(i) and B(i) is then calculated. After that, the proportional relations Kxand Kyof the body image G1according to A(i) and B(i) are computed. Then the relevant parameters of the standard zoning graph PPG(i), according to Kxand Ky, are scaled to get Pu. Then G1(or g) is matched with Pu-align A(i), and B(i) is matched with Pupositioning reference points.

The process for block410(shown inFIG. 12) relates to dividing infrared images into mapped zones. According to the coordinate system CS, human profile g and zoning lines in Pu, divide G1to get a series of closed areas in CS, and finally get the medical zoning of human infrared mapping.

As explained earlier,FIGS. 19A,19B, and19C illustrate a depiction of thermal mapping and process at different stages ofFIG. 12. Similar to block400(shown inFIG. 12), a thermal image412of a respiratory scan is loaded. The vectorization in block402(shown inFIG. 12) enables the following mathematical processes to take place. Step404(shown inFIG. 12) determines markers414,416a, and416b, which represent some of the determined characteristic reference points for this image. Image418(shown inFIG. 19B) represents the standard zoning template for the respiratory scan which is loaded by step406(shown inFIG. 12). Image418contains several characteristic reference points420,422a, and422b, which correspond to the same characteristic reference points indicated by markers414,416a, and416bon image412(shown inFIG. 19A). Characteristic reference points on the template are used to define the image into zones indicated by sections426a,426b,428a, and428b. Step408(shown inFIG. 12) combines thermal image412with image418and scales the standard zones to best fit zones placed on a mapped image430(shown inFIG. 19C). Mapped image430represents the end result of step410(shown inFIG. 12) by depicting the newly mapped zones represented by areas432a,432b,434a, and434b. Such mapped zones represent key interest areas for which thermal data may be interpreted and analyzed.

FIG. 20illustrates a flowchart depicting ROM86(shown inFIG. 4). ROM86gathers processed information from other modules and allows a user to format and customize the output of a report. ROM86includes a function selection module denoted at block500, which links to a database504and memory or sharing zone26to pool information. Block500is followed by block502where a function selection is determined, which determines how and what information is displayed. The available functions/options include an insert pixel function at block506, a module selection function at block508, a thermal image selection function at block510, a temperature range adjustment function at block512, a color scheme selection function at block514, a text editing function at block516, and a report output function at block518.

Insert pixel function at block506allows the user to insert annotations or mark areas on thermal images. The module selection function at block508allows the user to select a module which has a predefined report layout. The thermal image selection function at block510allows the user to select images to be included in the report. The temperature range adjustment function at block512allows for the specification of an upper and lower range of temperature values that is displayed by colors from the color scheme selection at block514. The color scheme selection function at block514allows for the selection or specification of color palettes in which to represent infrared images. The text editing function at block516permits the user to edit pre-formatted text, or add on additional text to the report. Use of any of the editing and selection modules creates a function preview at block524that displays the customized report. Customized reports are passed to memory or sharing zone26before being stored in database504. The report output module518outputs the report to either a data file520or to an alternative media522(e.g. print job). Blocks506,508,510,512,514, and516, are followed by block524.

FIGS. 21A-21Rillustrate predefined infrared positional images for use in health evaluation system40(shown inFIG. 3).

Referring now toFIG. 21A, a set of positional images550A correspond to the brain blood supply evaluation and includes: front, right side, left side, and back of the head. Set of positional images550A also corresponds to positions for the indications of diseases of the sense organs (eyes, nose, mouth, and ears) and includes the same positional images (550A) as with brain blood supply evaluation.

Referring now toFIG. 21B, a set of positional images550B corresponds to positions for indications of relevant diseases of (anterior) cervical thyroid and mandibular lymph node and includes: front neck and front neck with face up, neck with face to the right and up and neck with face to the left and up.

Referring now toFIG. 21C, a set of positional images550C corresponds to positions for the neck-shoulder syndrome and includes: front and back with hands raised (arms, neck, and head all on screen), and front and back with hands down (shoulders shown).

Referring now toFIG. 21D, a set of positional images550D corresponds to positions for the respiratory system health status evaluation and includes: front face and front with face up (exhaling, inhaling) of head-neck part; front of the chest, back of the chest with hands around the head, and right and left slanting.

Referring now toFIG. 21E, a set of positional images550E corresponds to positions for the myocardial blood supply evaluation and includes: front and back of head, neck, and chest.

Referring now toFIG. 21F, a set of positional images550F corresponds to positions for the heart and brain blood supply evaluation and screening of thoracic diseases and includes the head-face positions in set of positional images550A of brain blood supply evaluation. Set of positional images550F also includes front and back of the chest.

Referring now toFIG. 21G, a set of positional images550G corresponds to positions for the evaluation of mammary diseases and includes: left and right slanting positions of breasts; and left and right sides around the breasts.

Referring now toFIG. 21H, a set of positional images550H corresponds to positions for the digestive system health status evaluation and includes: front, and front with face up of head, neck, and chest; front of the abdomen (with hands around the head), left/right front slanting, and back of trunk.

Referring now toFIG. 21I, a set of positional images550I corresponds to positions for the urogenital system health status evaluation and includes: front/back of abdomen (legs apart); front of lower abdomen, and lower lumbosacral part. For the male only, the front of abdomen (penis in an upright position with testicles exposed, legs apart) is also included.

Referring now toFIG. 21J, a set of positional images550J corresponds to positions for the soft tissue injury and blood supply around the spinal column and includes: front, back and side of trunk; back of cervical vertebra plus back of lumbosacral part; buttocks; and back of two lower limbs.

Referring now toFIG. 21K, a set of positional images550K corresponds to positions for the evaluation of injuries to joints and soft tissues of lower limbs and includes: front/back of lower limbs (umbilicus-toes), and left/right stepping postures of lower limbs.

Referring now toFIG. 21L, a set of positional images550L corresponds to positions for the functional status of blood vessels and peripheral microcirculation of four limbs and includes: front/back of upper/lower body; front/back of hand/foot; and sole.

Referring now toFIGS. 21M,21N,21O,21P,21Q, and21R, sets of positional images550M,550N,550O,550P,550Q, and550R correspond to positions for the whole-body health status evaluation and includes: front/back/side of whole body; front/back of upper body; front/back of lower body; right/left slanting position of upper body; right/left slanting position of lower body; front, face up, right side, back, and left side of the head-face.FIGS. 21O and 21Qrepresent male front and back whole body images550O and550Q for use in set550M.FIGS. 21P and 21Rrepresent female front and back whole body images550P and550R for use in set550M.

FIGS. 22 through 32represent GUIs implemented by health evaluation system40.FIGS. 22-29are examples of GUIs to enable the user to customize and create scans.FIG. 30illustrates one embodiment of a patient report printout1000. The GUIs contain a database of patient files with numerous information fields. Through these options, the user can create new patient files, edit patient files, take IR thermal images of patients, analyze the thermal images, and print a report of the analysis by activating a corresponding GUI. These GUIs' are described later.

FIG. 33illustrates a block diagram of a thermal image mapping process1200, which has four paths identified as four parallel lines: A, B, C, and D. At block1202A, initially the body surface thermal distribution image is first taken. This initial, unmodified thermal image is known as a static or passive thermal image. An example of a body surface thermal distribution image is shown inFIG. 13A.

At path B, once a human thermal image at block1202B is obtained, a human thermal gradient sectional view is generated at block1204B (shown inFIGS. 40A,40B, and40C). After that, a human thermal cascade sectional view is generated at block1206B. Here the image is processed with vectorization to remove the background, as seen inFIG. 13C. The human thermal cascade sectional view at block1206B is the image processed with cascade chromatography to determine areas of abnormal temperature.

In the cascade chromatography process, each thermal image is composed of a plurality of pixels (such as, 320×240), where every pixel contains temperature data and positional data. The temperature data in the pixel is represented in the image by a corresponding color. The user defines which colors represent which temperatures. The positional data positions the pixel at a particular point on the body. InFIGS. 40A,40B, and40C, a series of dynamic thermal images is shown. The cascade chromatography process begins the analysis at the highest temperature detected in the body. InFIG. 40A, the highest temperature is set at 34.80 degrees Celsius, as shown in the image at row R1, column C1. Therefore, 34.80 degrees Celsius is the first reference temperature used for the analysis. The cascade chromatography process begins by organizing the pixels from highest temperature to lowest temperature. All pixels that contain temperature data equal to or greater than the reference temperature (34.80 degrees Celsius in image R1, C1) are compared. In one embodiment, these pixels are compared to pixels with symmetric positional data. The human body is generally symmetric. Therefore, pixels at symmetric positions of the body should have equal temperature data. For example, the pixel at the tip of the index finger in the right hand should have equal temperature data as the pixel at the tip of the index finger in the left hand. The symmetries are defined by preset zones in the program. If the temperature variation ΔT is 0, then there is no abnormality, and the pixels being compared are changed to white (or whatever color is defined by the user for the highest temperature). Otherwise, the pixels are left unaltered. Then the reference temperature decreases by a user-defined amount. For example, inFIGS. 40A,40B, and40C, the temperature decreases by 0.05 degrees. The system then compares the set of pixels with the next highest temperature data in the same manner. The analysis continues until every pixel within the body in the thermal image is scanned.

AsFIG. 33illustrates, the human thermal layer sectional view at block1208B occurs once the human thermal cascade section view at block1206B is complete. Once areas of abnormalities have been identified, the human thermal layer section view at block1208B utilizes a depth algorithm to determine the level at which the temperature abnormality exists within the patient's body. For example, an abnormal temperature on the surface can indicate a skin condition, while an abnormal temperature deeper in the body can indicate a problem with an organ.

At path C, a local surface thermal distribution image at block1202C is obtained only for a specific anatomic zone to be analyzed. Thus, the analysis is localized.

At path D, the local thermal image at block1202D is obtained only for a specific anatomic zone to be analyzed. Block1202D is followed by block1204D where a local thermal gradient view is generated. At block1204D, only the specific anatomic zone is vectorized. At block1206D, a local thermal cascade sectional view is generated and only the specific anatomic zone is compared. Block1206D is followed by block1208D where a local thermal layer sectional view is generated if there is an abnormality in the specific anatomic zone. Health evaluation system40(shown inFIG. 3) also determines whether the abnormality is on the surface or internal. Path D creates the same views as path B. However, the vectorization and cascade chromatography is performed only for a specific zone or location.

When doing depth analysis, system40generates a three-dimensional analysis of a two-dimensional thermal image, as seen inFIGS. 41A,41B,42A,42B,43A, and43B. These thermal images are composed of TMT maps. The term “micro” refers to a specific anatomic zone during the thermal image analysis. The term “texture” is defined, as is used in computer graphics, as an array of pixel data, either in two or three dimensions, where each pixel can contain color, luminance, or other information.

FIG. 34illustrates an example of a block diagram of an auto-analysis1250with heat depth evaluation. Auto-analysis1250with heat depth evaluation begins at block1252where infrared radiation is received from an internal heat source and transmitted to the surface by radiation or conduction. Block1254analyzes the heat depth and shape by electrothermal analog theory. At block1256, the internal heat source is positioned and quantified.

FIG. 35illustrates a flowchart of one embodiment of an auto-analysis1300. Auto-analysis1300begins with a general evaluation at block1302of the thermal image or mapping. Block1302is followed by block1304where analysis of a lymph heat source takes place. Block1304is followed by block1306where a determination of abnormal heat depth is made. Block1306is followed by block1308where an analysis of abnormal local vascular heat source is performed. Block1308is followed by block1310where an analysis of changes of heat conduction status (including special heat source status) is made. Block1310is followed by block1312where an analysis of abnormal heat of tissues organs is made. Block1312is followed by block1314where a determination of relative difference of thermal radiation of tissues and organs is made. Block1314is followed by block1316where a determination of the relative thermal radiation of abnormal areas is made. Block1316is followed by block1318where a dynamic analysis is performed. In various configurations, the flowchart blocks above are performed in the depicted order, or these blocks or portions thereof may be performed contemporaneously, in parallel, or in a different order. Furthermore, one or more of the blocks may be omitted for a particular evaluation and analysis depending on the type of the analysis desired.

Health evaluation system40(shown inFIG. 3) is designed to capture and detect, among other sources, metabolic heat sources of normal cells, tissues and organs; metabolic heat sources of inflammatory tissues and organs; metabolic heat sources of benign tumor tissues; metabolic heat sources of hyperplastic cell tissues; metabolic heat sources of cancerous cells; metabolic heat sources of allergic tissues; metabolic heat sources of functional status; and metabolic heat sources of tissues resulting from other external factors.

Health evaluation system40is also designed to detect surface heat sources, superficial heat sources, deep heat sources, non-planar internal heat sources, tubular heat sources, hollow heat sources, heat sources under hairs, special heat sources, and other heat sources.

FIG. 36illustrates a general flowchart of image processing process1350utilized by health evaluation system40(shown inFIG. 3). One or more of the steps may be omitted as needed. Process1350begins at block1352where the body is scanned or an image is captured. Block1352is followed by block1354where a sub-anatomic zone is scanned. Block1354is followed by block1356where zones in an organ are scanned. Block1356is followed by block1358where depth of an abnormality is scanned.

In one embodiment, health evaluation system40(shown inFIG. 3) is utilized to analyze an anatomic system (digestive system, circulatory system, etc). This analysis cannot rely on symmetry to determine temperature abnormalities since organs are not necessarily symmetric. When analyzing organs, health evaluation system40relies on the energy efficiency of cells to determine whether there are abnormalities. For example, a healthy cell takes organic compounds and metabolizes them, turning the compounds into energy and waste. A healthy cell typically operates around 40% efficiency, with 60% of the energy in the process being output as waste. A cancerous cell, however, has a much lower efficiency, typically around 8-9%, with the rest of the energy in the process being wasted. Cancerous cells thus output more heat than a healthy cell, and cancerous growths appear as areas with abnormally high temperatures.

At block1352, health evaluation system40(shown inFIG. 3) initially captures the static thermal image (human thermal image). Health evaluation system40then analyzes general anatomic zones (chest, upper abdomen, lower abdomen arms, legs, head, and so on) within the patient's body. Some general anatomic zones are naturally hotter or cooler than others. If the average temperature data of the pixels for an anatomic zone in a thermal image is higher than the average temperature data of the pixels for another anatomic zone that is naturally hotter, there is an abnormality. For example, the head is the hottest anatomic zone, and the chest and feet are some of the coolest zones. If the chest or feet zone is hotter than the head zone, then the chest or feet zones are exhibiting abnormalities.

If an abnormality is detected, health evaluation system40(shown inFIG. 3) analyzes the organs within the general anatomic zone containing the abnormality at block1356. Organs also naturally exhibit hotter or cooler temperatures relative to the other organs within the general anatomic zone. This is because each organ in a general anatomic zone is composed of a different type of cell, each with different pathological functions. The different pathological functions result in each cell type producing a different amount of heat output. Within that general anatomic zone, system40compares and analyzes the organs and if an organ is exhibiting abnormal temperatures, system40focuses on that particular organ. Each organ is pre-divided into specific zones such as shown inFIGS. 17A,17B,18,19A,19B, and19C, and the temperatures of each zone are compared against the average overall temperature of the entire organ. If there is a temperature variation (ΔT) greater than zero, there is potentially an abnormality. If an abnormality is detected, then system40performs a thermal depth analysis at block1358to determine whether the abnormality is at the surface of the body or below the surface of the body. If the abnormality is at the surface of the body, a skin abnormality is indicated and not an organ abnormality. If the abnormality is below the surface of the body, the organ has the abnormality, which requires further clinical evaluation.

FIGS. 37A and 37Billustrate thermal images1400A and1400B of a healthy woman. The heat mappings in the image breast area in images1400A and1400B and the heat wrapping in the abdomen area of1400B demonstrate that the heat distribution of the woman is symmetric, which indicates that there are no apparent abnormalities.

FIG. 38Aillustrates a representation of a vectorized thermal image1410. Vectorized thermal image1410is a conventional thermal image that has been vectorized to remove the background image, as described above and shown inFIGS. 13A-13C. On the other hand,FIG. 38Billustrates a representation of an analyzed thermal image1415produced by health evaluation system40(shown inFIG. 3) after analyzing vectorized thermal image1410during the auto-analysis block20ofFIG. 2. Both images are representative of a patient's whole body. The body is in a position facing towards the camera with the patient's arms at the side. Analyzed thermal image1415graphically illustrates problem or suspect areas1416,1417, and1418identified by health evaluation system40as having abnormal temperatures. Abnormal temperatures are generally indicative of a health problem. Health evaluation system40performs the auto-analysis at block20(shown inFIG. 2) by using a depth algorithm.

FIG. 39Aillustrates a representation of a vectorized thermal image1420. Vectorized thermal image1420is a conventional thermal image that has been vectorized to remove the background image, as described above and shown inFIGS. 13A-13C. On the other hand,FIG. 39Billustrates a representation of an analyzed thermal image1425produced by health evaluation system40(shown inFIG. 3) after analyzing the vectorized thermal image1420during the auto-analysis block20ofFIG. 2. Images39A and39B are images of the back of the patient's body. The images of the back allow portions of the body, not visible by viewing the front of the patient, to be analyzed.

FIGS. 40A,40B, and40C illustrate a representation of sectional views from the cascade chromatography process. InFIGS. 40A-40C, sectional view images1430A,1430B, and1430C are generated from the cascade chromatography process (FIG. 10) where the pixel color is assigned either black or white. Sectional view images1430A begin with a captured thermal image in row R1, column C1, which are views of the front whole body. The sectional view images are in order from left to right and then top to bottom. Row R1, column C1, contains the first image, while Row R1, column C2, contains the second image, and so forth.FIG. 40Bdepicts the continued pixel color change in sectional view images1430B for rows R1, R2, and R3. As can be seen from one image of the series to the next adjacent image, some of the pixels are turned white or black.FIG. 40Cdepicts the continued pixel color change in images1430C for rows R1, R2, and R3. The progression of individual sectional view images demonstrates the active change at each step of the cascade chromatography process, and therefore these images are known as dynamic thermal images.

In this embodiment, there are three rows inFIGS. 40A,40B, and40C. However, more or less rows and columns may be utilized. Each row has a series of eight sectional view images. Sectional view images1430A are progressive modifications of the images according to the flowchart ofFIG. 10. Health evaluation system40(shown inFIG. 3) records the temperature of each pixel in one image respectively, and organizes the pixels by highest to lowest temperature into a list of pixels. Health evaluation system40then compares each pixel to the corresponding pre-programmed anatomical position. If the pixel is at a normal temperature, the pixel color is changed to white. Otherwise, the pixel is left unaltered or changed to a non-white pixel (for example, the color black). The next pixel in the list of pixels is then compared. This continues until the list of pixels is exhausted.

FIG. 41Aillustrates a representation of a normal thermal image1440in two-dimensions. The term normal in this context is used to denote a non-vectorized thermal image.FIG. 41Billustrates a representation of a three-dimensional analyzed thermal image1445created from thermal image1440(shown inFIG. 41A). Image1445is created during the auto-analysis block20(shown inFIG. 2). Image1445demonstrates the three-dimensional computations that health evaluation system40(shown inFIG. 3) undergoes when analyzing a thermal image. Thermal image1440is placed upon an x and y-axis. Image1440is then analyzed in three-dimensions for abnormalities as depicted in image1445. Image1445is a representation of the heat output by a patient's body, where each x and y-axis intersection point represents a position in a patient's body. The z-axis represents the temperature at a given depth within the patient's body. Note that at a higher z-axis point1446the color is darker, signifying a cooler temperature, and at a lower z-axis point1447the colors grow lighter, indicating a warmer temperature. This serves to demonstrate increasing temperature when moving from the surface of the body to the inside of the body. Calculations of the body temperature are performed using three-dimensional mathematical formulae. Additionally, as a consequence of viewing the heat output in three dimensions, the contours of the body are discernable in image1445.

FIG. 42Aillustrates a representation of a vectorized thermal image1450in two-dimensions.FIG. 42Billustrates a representation of image1455created from vectorized thermal image1450(shown inFIG. 42A). Image1455is created by health evaluation system40during the auto-analysis block20(shown inFIG. 2). Vectorized thermal image1450depicts a thermal scan (captured thermal image) of the chest and abdomen area of a patient. Image1455(shown inFIG. 42B) is a three-dimensional section of only the abdomen instead of the chest and abdomen (shown inFIG. 42A). The three-dimensional section of the abdomen demonstrates a more detailed view of the various temperatures at different depths1456and1457within the patient's abdomen. A black area1458indicates a depth at which no thermal readings were recorded.

FIG. 43Aillustrates a representation of a vectorized thermal image1460in two-dimensions.FIG. 43Billustrates a representation of a three-dimensional analyzed thermal image1465created from vectorized thermal image1460(shown inFIG. 43A). Image1465is created by health evaluation system40during the auto-analysis block at20(shown inFIG. 2). Image1465is created in a similar manner as described above in relation toFIG. 41B. Image1460depicts a back view of the lower half of a patient's body. The patient's right leg has a large black area1467(shown inFIG. 43B). Large black area1467appears in bothFIGS. 43A and 43Band is darker than the surrounding leg area, indicating a temperature difference that health evaluation system40(shown inFIG. 3) identifies as abnormal. Health evaluation system40then analyzes large black area1467to determine whether or not the area is injured using change in temperature (ΔT) calculations. InFIG. 43B, the depth of large black area1467or area1466(represented by black peaks) is mapped in the z-axis, which helps determine the depth. When performing depth analysis, health evaluation system40(shown inFIG. 3) generates a three-dimensional analyzed thermal image from either a two-dimensional normal thermal image or vectorized thermal image.

FIGS. 22-29are examples of the GUI to enable the user to customize and create scans.FIG. 30illustrates one embodiment of a patient report printout1000. The GUIs described below contain a database of patient files with numerous information fields. Through these options, the user can create new patient files, edit patient files, take IR thermal images of patients, analyze the thermal images, and print a report of the analysis by activating a corresponding GUI described below, which is overlaid upon the main GUI.

In one embodiment, there are two methods of retrieving the patient file editing GUI, either by right clicking a patient file and selecting the third drop down option (FIG. 24), or by clicking an edit button in the main GUI (FIG. 22).

The software enables a user to remotely take photographs of a patient with an infrared (IR) camera. The GUIs provides the user an automatic determination of the colors of a thermal image and automatic analysis of the thermal image to detect abnormalities.

FIGS. 23 through 29are overlaid on a depiction of the main GUI (FIG. 22).

FIG. 22illustrates one embodiment of a main patient database GUI602depicting a patient file600within one embodiment of a database648. File600contains a database item number604corresponding to the position of file600within the database. File600also contains a patient serial number606, a patient's name608, a patient's age610, a patient's gender612, a patient's marital status614, a nationality of the patient616, a patient's address618, a patient's occupation620, and a patient's description622. File600also contains a set of thermal images of a patient undergoing evaluation. In one embodiment, the thermal images in file600are displayed in an area624as depicted in thermal images624aand624b. The user can select a particular patient file (highlighted number132)628by clicking on fields604through622. Clicking on fields606,608,610,612,614,616,618,620, and622highlights a database item number604as depicted in a selected item number628, and selects a field as depicted in a selected field630.

Clicking on database item number604selects the entire line, as depicted in an entire patient line selection720(shown inFIG. 24). Clicking on a field does not otherwise perform any action because database648is read-only. When file600is selected, patient serial number606is displayed in the lower left hand corner of the screen626and thermal images in area624are updated to correspond to data that is stored in file600. With or without selecting file600, a user can create another patient file by left-clicking a new patient file button632, which opens a patient file creation GUI as depicted in one embodiment of a new patient file creation GUI660(shown inFIG. 23). In addition, with or without selecting file600, a user can left-click an update patient file button640which updates database648with any changes that were made. Moreover, with or without selecting a file600, a user can left-click an exit button642which exits main patient database GUI602. After selecting file600, a user can left-click a patient file search button634, a patient report button636, or an IR image taking button638. Without first selecting file600, buttons634through638are inoperable.

Once file600is selected, a user can left-click button634to edit file600, which opens a patient file GUI that is editable as depicted in one embodiment of a patient file GUI750(shown inFIG. 25). In addition, once file600is selected, a user can right-click on GUI602, which opens a menu as depicted in one embodiment of a new patient file sub-menu722(shown inFIG. 24). Furthermore, once file600is selected, a user can left-click the patient report button636to view a preview of a patient report, which opens a patient report preview GUI as depicted in one embodiment of a thermal image analysis GUI890(shown inFIG. 28). Moreover, once file600is selected, a user can also left-click the IR image capture button638to add thermal images to file600, which displays a thermal image capture GUI as depicted inFIG. 26. In one embodiment, when any of GUI buttons632,634,636, and638are left-clicked the resulting displayed GUI is overlaid upon GUI602.

FIG. 23illustrates one embodiment of a new patient file creation GUI660. GUI660creates new file600and stores the information in database648. GUI660appears when button632is selected, regardless of whether file600is selected. GUI660appears overlaid upon GUI602(shown inFIG. 22). GUI660contains both a basic information area662and an additional information area680. All information for both areas662and680is manually entered by the user. Area662contains a patient serial number field664, a name field666, a date of birth field668, a male radio button670, a female radio button672, a marital status checkbox674, a nationality field676and an age field678. Clicking serial number field664allows a user to enter the serial number of the patient. In addition, clicking name field666allows a user to enter the name of the patient. Moreover, clicking a date of birth field668allows a user to enter the date of birth of the patient. In one embodiment of the date of birth field, the date of birth is entered as the year followed by the month and then the day. The user can select either a male or female gender by selecting either field670or field672.

To indicate whether a patient is married, a user can left-click a marital status checkbox674. Clicking checkbox674indicates that the patient is married. Furthermore, left-clicking nationality field676displays a drop down menu with a list of preset nationalities. Left-clicking one of the nationalities in the list enters the selection into field676. Clicking age field678allows a user to enter the age of the patient. Moreover, left-clicking on the arrows in field678either increases or decreases the number in field678by 1. Additional information area680contains an additional information checkbox682, an occupation field684, a location field686, a patient symptoms field688, and a patient medical history field690. To enter additional information beyond the basic information, a user selects checkbox682by left-clicking it whereby field684displays a preset list of occupations. Left-clicking one of the occupations in the list enters the selection into field684. Additionally, left-clicking field686displays a preset list of locations. Left-clicking one of the locations in the list enters the selection into field686. Additionally, selecting field688allows the user to enter information about the patient's symptoms. Moreover, selecting patient field690allows the user to enter relevant medical history information. A clear button692allows the user to clear all entries. Once the user is finished entering patient information, the user left-clicks a confirm button694, which confirms the data, closes GUI660, and saves the entered information into file600in database648. The user then returns to GUI602(shown inFIG. 22).

FIG. 24illustrates an embodiment of a new patient file sub-menu722overlaid on GUI602(shown inFIG. 22). Sub-menu722allows a user to select from several operations to be performed on a list of file600or a single file600. Sub-menu722appears when a user right-clicks any file600. Sub-menu722contains a patient file sort option724, a delete file option726, and an edit file option728. When a user left-clicks option724, the list of file600is sorted according to patients' serial numbers. In one embodiment, files600are sorted in ascending order. When a user left-clicks option726, the information within selected field630, within the file600, is deleted. When a user left-clicks option728, GUI750(shown inFIG. 25) is displayed.

Another embodiment of sub-menu722contains additional options depicted by a view all option730and a close all option732. When selected, option730displays all records for the patient at once. When selected, option732closes all records opened by option730.

FIG. 25illustrates one embodiment of GUI750. GUI750allows a user to edit file600. GUI750is another embodiment of GUI660(shown inFIG. 23), with certain limitations. Fields662through690in GUI750are similar to those of GUI660, with the exception of patient serial number field664. In order to prevent inadvertent deletion of a patient file, patient serial number664in GUI750is read-only, and therefore cannot be changed from the originally assigned number.

FIG. 26illustrates an embodiment of an IR thermal image capture GUI778. GUI778allows the user to capture thermal images of a patient. GUI778is connected to an IR camera. The IR camera transmits a thermal image780to GUI778. The IR camera can be operated remotely by camera movement buttons782. Buttons782operate the camera in the up, down, left, and right directions when the corresponding arrow is left-clicked. The IR camera moves along a plane, remaining parallel to the patient. The user utilizes camera focus buttons800aand800bto focus the IR camera. A thermal image color scheme area784is composed of a Celsius temperature scale814and a thermal color scale816. The colors in scale816correspond to the temperature values in Celsius temperature scale814. In one embodiment, scale816is composed of the color black representing the lowest temperature on scale814, changing to the color white at the highest temperature on scale814. In one embodiment, two methods of changing thermal image color scheme784, manually and automatically, are utilized.

One embodiment of a method for manually changing the color scheme for thermal image780is depicted by a temperature setting arrow786. Scale814can be modified by a sliding arrow786up and down a Celsius temperature scale818. The upper and lower limits relative to arrow786are displayed by a temperature limit bar788. Bar788displays the range of temperatures, relative to arrow786, which appear in area784. Bar788can be modified by changing the value in a temperature range field794. Clicking on a field794allows a user to enter information into the field. Additionally, clicking on the buttons in field794correspondingly increases or decreases the displayed range value in field794. A user can also modify the rate at which the colors change in scale816by changing the value in a thermal color rate change field796. Left-clicking on field796displays a drop-down list of preset rate change values. Left-clicking on one of the preset rate change values changes the rate of change of colors in scale816. Thermal image color scheme784can be changed by clicking a color preset field790. Field790contains a set of 256 colors for use in thermal image780. A different preset is selected according to the thermal imaging standards of various countries.

Another embodiment of a thermal image color scheme utilizes computer generated algorithms to automatically determine the proper temperature color settings. Manually adjusting color temperature scheme784is a cumbersome and inexact process. To determine the color scheme automatically, a user activates the automatic color selection feature by left-clicking an automatic temperature measurement checkbox798. By left-clicking checkbox798, arrow786, field794, and field796are disabled. The user cannot edit or input information using these fields or arrows.

Clicking a thermal image negative checkbox792causes a negative of a camera image to appear in GUI778instead of thermal image780. Clicking checkbox792again returns the camera image to the image's non-negative state. To begin the thermal imaging process, the user clicks an image capturing button802. Once button802is pressed, an IR camera captures a series of thermal images, which are viewable as smaller preview thermal images804in a thermal image preview area806. A user clicks image advancement button810to change thermal image780to the next captured thermal image. Once a user decides to pick a particular image, the user can left-click a save button834. When button834is left-clicked, GUI778closes and a thermal image preview/save GUI860opens.

In one embodiment of an automatic method of capturing IR thermal images, depicted by GUI778, the patient's eyes, nose, and mouth must be within a camera alignment rectangle808. GUI778automatically creates a thermal zone based on the position of the patient's eyes, nose, and mouth in rectangle808. The infrared image is processed into mathematical data such that the image can be compared against a standard template and mapped into zones. To accomplish this, the thermal image is vectorized. Once the image is vectorized, an algorithm determines the location of characteristic reference points. These characteristic reference points are based on the position of the eyes, nose, and mouth of the patient that are within rectangle808. Once the characteristic reference points are found, GUI602(shown inFIG. 22) retrieves a standard zoning template corresponding to the position code of the infrared image. GUI602scales the standard template zones to match the infrared image using the characteristic reference points. Once the standard template zones are matched, GUI602divides the infrared image into mapped zones. Such mapped zones represent key interest areas for which thermal data may be interpreted and analyzed.

In an embodiment of a manual method of capturing IR thermal images, depicted by GUI778, patient position icons838a,838b, and838care used instead of an automatic zoning system. When icon838ais clicked, thermal image780is stored in file600under icon838a. When icon838bis clicked, thermal image780is stored in file600under icon838b. When icon838cis clicked, thermal image780is stored in file600under icon838c.

The user can exit GUI778by clicking an exit button836or a stop button840. Clicking button836closes GUI778and opens GUI860. Before GUI860is opened, thermal image780is vectorized and the background image is removed. Removing the background enables GUI890to analyze thermal image780. Stop button840performs similarly to exit button836. A circle button812enables the user to change the contrast of the picture. A play button840captures thermal image780. The patient's serial number828is displayed in the lower left hand corner of GUI778. The position of thermal image780in relation to the total set of thermal images for the patient is displayed as a thermal image position number830. A lower and upper temperature limit832is displayed in the lower right hand corner of GUI778.

FIG. 27illustrates an embodiment of GUI860. GUI860displays a vectorized thermal image862, a thermal image save prompt866, and a save button864.

In one embodiment, image862can be saved by utilizing prompt866to a selected folder868within a storage device. Left-clicking button864displays prompt866. Image862can be saved as a .jpg, .bmp, or .tds file using file type field870with a user-defined file name872. A user can left-click button874to save image862that uses file type870and user-defined file name872. A user can left-click a cancel button876to abort the save procedure. GUI860also contains a thermal image negative checkbox880, which performs similarly to checkbox792(shown inFIG. 26). Furthermore, GUI860contains a thermal image enhancement checkbox882. Left-clicking checkbox882enhances the resolution of image862by smoothing out any rough edges. Left-clicking checkbox882again undoes the process. Left-clicking a close button878closes GUI860and then opens GUI602(shown inFIG. 22).

FIG. 28illustrates an embodiment of GUI890. GUI890includes an abnormality analysis area902, a TMT analysis area926, and a patient notes area928. TMT analysis area926contains a forehead region condition field892, an eye region condition894, a nose region condition896, a mouth region condition898, and a thorax region condition900. Each of the fields892through900contains either a (+) or a (−) indicating whether a person's temperature in the region is abnormal or not. In one embodiment, a (−) indicates a normal condition, while a (+) indicates an abnormal condition. Based on the values indicated in fields892through900, health evaluation system40performs an analysis and identifies if the patient has an abnormal upper respiratory condition, and if so, what is the specific condition of the patient. The system generates and displays the output in area902. Area928contains the average temperature of the patient's upper respiratory system904, condition of a location of the patient906, whole body condition of the patient908, physical appearance of the patient's body910, and an epidemiology report912. Average temperature904is the average temperature of the patient based on the thermal images in file600. Information in fields906through912is entered by a user. Condition of a location of the patient906describes whether a particular region of the patient's body has abnormalities based on thermal analysis. Whole body condition of the patient908describes whether the patient's body as a whole has abnormalities based on thermal analysis. Physical appearance of the patient's body910describes any physical symptoms the patient exhibits (for example, rashes, lesions, bloating, or being overweight). Epidemiology report912describes where the patient has been, who has come into contact with the patient, and other medical history of the patient. When a user is finished entering information, the user can click a save button914. Clicking button914saves the information displayed into file600. For a user to enter comments into fields906through912, the user must click a comments button916. Clicking button916opens up a new interface where comments can be entered into the fields for906through912. When the new interface is closed, the comments are saved and displayed in fields906through912. The information entered is later displayed in a patient report comments field956(shown inFIG. 29). Clicking a visual report tab920displays a patient report preview GUI950(shown inFIG. 29). Clicking a close button930closes GUI890and opens GUI602(shown inFIG. 22).

One embodiment of a thermal analysis chart922ais displayed in GUI890. Chart922aplots the patient's temperature in Celsius922bagainst the metabolic energy output of the patient922cfor each body region reported in TMT analysis area926.

FIG. 29illustrates an embodiment of GUI950. GUI950is automatically displayed in the event that GUI890(shown inFIG. 28) is closed. GUI950allows a user to preview a patient report952before printing. One embodiment of thermal images for patient report952, which are retrieved from file600(shown inFIG. 22), are depicted by thermal images954aand954b. In addition, patient report952includes a field956, which contains information from fields906through912(shown inFIG. 28). Field956also contains information on any abnormal readings detected by the system, in addition to a description of each body region analyzed and abnormalities, if any, in each body region. Field956also displays a number of plus symbols denoting the number of regions that have abnormalities detected. Furthermore, patient report952contains a patient serial number field958, a patient name field960, a gender field962, an age field964, and an occupation field966. Fields958through966display the information stored in respective fields606,608,610,612, and620(shown inFIG. 22) stored in file600. For example, patient name field960displays field608(shown inFIG. 22) stored in file600. Patient report952contains medical reference pictures that a user can compare to the patient's thermal images. A color preset field972allows a user to change the color scheme of thermal images954aand954bsimilarly to color preset field790(shown inFIG. 26). A thermal image negative button974allows a user to view the negative of thermal images954aand954bsimilarly to thermal image negative button792(shown inFIG. 26). A user can left-click a thermal image enhancement checkbox976to smooth out the rough edges of thermal images954aand954b. Checkbox976is similar to thermal image enhancement checkbox882(shown inFIG. 27). Left-clicking an image background removal checkbox978removes any background thermal readings from thermal images954aand954b. Left-clicking a thermal color editing checkbox980enables a user to change the color scheme of thermal images954aand954b. Left-clicking checkbox980again disables the ability to change the color scheme of thermal images954aand954b. While checkbox980is checked, a user can use a temperature setting arrow and temperature limit bar in area980similarly to the temperature setting arrow786(shown inFIG. 26) and the temperature limit bar788. While checkbox980is checked, a user can also change a temperature range field984, which performs similarly to the temperature range field794. While checkbox980is checked, a user can also change the colors of the thermal image using a thermal color rate change field986similarly to thermal color rate change field796. When the user is satisfied with the results, the user can left-click a print button988, which prints out a hard copy of patient report952, depicted as a patient report printout1000(shown inFIG. 30). The user can also left-click a save button990which saves the report to file600. The user can left-click tab918to switch to GUI890(shown inFIG. 28).

One embodiment of standard medical reference pictures is depicted by reference pictures968a,968b, and968cfor the upper respiratory system. The user can utilize reference pictures968a,968b, and968cto analyze vectorized thermal images954aand954bof a specific patient.

In one embodiment, a user may select a specific part of a patient's body being analyzed by utilizing a body region selection field970(shown inFIG. 29). Field970allows a user to view a different report for each region of the body. Left-clicking field970displays a preset list of body regions. Left-clicking a selection from the preset list changes what is displayed in patient report952to the corresponding body region.

FIG. 30illustrates an embodiment of patient report printout1000. Printout1000depicts a resulting hard copy that is the output generated by health evaluation system40when print button988(shown inFIG. 29) is pressed by a user. All fields in printout1000correspond to the respectively numbered fields in GUI950(FIG. 29).

FIGS. 31 and 32are examples of a partial sectional report of thermal images created by health evaluation system40(shown inFIG. 3). Health evaluation system40is capable of scanning more than the body's surface area. It can pinpoint and analyze deep heat sources that emanate from the body. Health evaluation system40is capable of identifying and locating abnormal internal heat sources from tissues and organs in the body, including the stomach, pancreas, gallbladder, liver, lymph nodes, heart, lungs, brain, blood vessels, and even heat sources under the hair. Health evaluation system40is further capable of mapping all the major areas of a body, including the head, spine, arms, legs, hands, and feet.

FIG. 31is an example of a partial sectional report and a series of thermal mappings of a male. Auto-analysis of the thermal image notes a suspect area which is in circle1100. The auto-analysis of the thermal mapping suggests at least one of a primary carcinoma of liver; and/or liver cirrhosis (decompensation period). The thermal mapping indicates an abnormal distribution of thermal field at the neck and back, asymmetrical at the two sides, with thermal radiation obviously higher at the left neck, ear, and back than at the right. The abnormal distribution suggests high metabolism problems (e.g. carcinoma) of the hepatic bile. There are pathological changes of the lung, pleura, left neck, and retroauricular lymph node.

Referring now toFIG. 32, a series of thermal mappings of a male. Auto-analysis of the thermal image notes a suspect area which is circled in circle1110. The auto-analysis of the thermal mapping suggests at least one of a primary carcinoma of liver; and/or liver cirrhosis (decompensation period). The thermal mapping indicates an abnormal distribution of the thermal field at the surface level of the back side of the patient, asymmetrical at the two sides, and thermal radiation at right hypochondria obviously higher than at the left. The report also indicates an increased thermal radiation at the upper chest, left axilla, and lower left abdomen. There is indication of a high metabolism problems (e.g. carcinoma) of the hepatic bile. The analysis does not rule out pathological changes of the lung and pleura, and the left axillary lymph node. The analysis also does not rule out pathological changes of the colon and left iliac fossa.

The TMT system's design presents the body's internal heat temperature details in digital data and colored images on a GUI. Different colors that appear in the images correspond to different temperatures throughout the body. The image data produced is three-dimensional (shown inFIGS. 41B,42B, and43B), unlike traditional or current thermal imaging technology which utilizes two-dimensional images.

In one embodiment, health evaluation system40(shown inFIG. 3) receives metabolic thermal radiation status and functional imaging of cells, tissues, organs and the body as a whole, and makes qualitative and quantitative analysis and evaluation of the following: 1) texture imaging; 2) tissue status imaging with changes of tissue texture; 3) tissue status/function imaging with changes of tissue texture and functions; 4) function imaging; and 5) function/status imaging with changes of functions and status.

Health evaluation system40(shown inFIG. 3) evaluates the thermal intensity of cell, organ, and patient's system metabolism. The human body has a natural thermal balance according to the thermally balanced entity-balance principle. The human body is an entity symmetrical along the central axis according to the central axis-symmetry principle. Thus, basic standards based on the normal positions of body parts and these principles of relative difference may be used. Metabolism changes under external intervention and is dynamic.

Health evaluation system40(shown inFIG. 3) provides real-time dynamic prediction, prevention, early warning, and clinical treatment monitoring. Health evaluation system40is safe, reliable, efficient, easy to operate, cost-effective, and capable of detecting most abnormalities. Health evaluation system40utilizes digital medical imaging technology featuring compact memory and large information volume. Health evaluation system is capable of evaluating a human respiratory system abnormalities, otorhinolaryngological abnormalities, cardiovascular system abnormalities, reproductive system abnormalities, respiratory system abnormalities, digestive system abnormalities, urinary system abnormalities, endocrine system abnormalities, and lymphatic system abnormalities.

FIG. 44is an embodiment of a flow diagram for a fitness evaluation process1500that is implemented utilizing health evaluation system40(shown inFIG. 3). Fitness evaluation process1500has the ability to make determinations as to the anatomy of the human body. Process1500is used to analyze the effectiveness of various fitness processes, including fitness training (shown inFIG. 47A), muscle metabolism, body fat content (shown inFIG. 48A), human microcirculation system and/or human vascular system (shown inFIG. 49A), muscle endurance, muscle regeneration, and mental stress. As is seen from the description below, process1500may be utilized in the area of sports medicine, physical training, physical therapy, etc.

FIG. 44illustrates that process1500begins once block1502is selected. Block1502is followed by one of the following processes: a Qi (flow) evaluation process at block1504, a thermal muscle metabolism evaluation process at block1506, a fat mapping process at block1508, a thermal microcirculation metabolism evaluation process at block1510, an anatomical structures and systems evaluation process at block1512, a muscle endurance evaluation process at block1514, or a psychological evaluation process at block1516. As can be appreciated, fitness evaluation process1500may perform some or all of the above processes.

Anatomical structures and systems evaluation process at block1512is selectively followed by one of block1520for the digestive system, block1522for the nervous system, or block1524for the lymphatic system. Block1512for anatomical structures and systems evaluation process may be followed by other blocks in addition to blocks1520,1522, and1524. Block1514for muscle endurance is also followed by block2000as shown inFIG. 52A.

FIG. 45Aillustrates a flowchart for the Qi evaluation process at block1504. The process requires a thermal image to be captured at block1550. Once the image is captured, temperature variations are determined according to the flow of Qi in meridians. Block1552is followed by block1554where the temperature variations are auto-analyzed (such as at block20shown inFIG. 2) according to Chinese medicine criteria. Block1554is followed by block1556where the results of the analysis are generated (such as at block22shown inFIG. 2). By way of example, the results may be displayed on a monitor or printed in the form of a report.

FIG. 45Billustrates a human Qi channel diagram template1570for use in traditional Chinese medicinal evaluation. Template1570is generally used for the zone template. The human Qi channel diagram template1570comprises a series of paths “Jingluo” (represented by template lines1572) in the human body used in Chinese Medicine. Lines1572, which are called the meridians, represent the flow of blood and “Qi” (pronounced “Chi”) within the human body. Qi is a body's vital energy that flows through the meridians. However, one embodiment of a thermal imaging system is used to record thermal images that correspond to the flow of Qi in meridians that can be used in traditional Chinese medicine analysis. When an abnormality in an otherwise healthy body blocks the flow of Qi, such blockage causes an area of the body to become very hot or very cold, which can be measured and reported by health evaluation system40(shown inFIG. 3).

FIG. 45Cillustrates a thermal image1575corresponding to the flow of Qi. In this embodiment, for illustrative purposes, thermal image1575is abnormal and is hereinafter referenced as an “abnormal thermal image1575.” Abnormal thermal image1575indicates increased temperatures in certain areas, which indicate abnormalities. Abnormal thermal image1575contains increased temperature in a head1576, indicating an abnormality. Moreover, abnormal thermal image1575contains elevated temperatures in right chest area1577(left part of the chest in the picture), which likely indicates abnormality of the lungs. The abnormality in head1576combined with the abnormality in right chest area1577, denoted by abnormal thermal image, signifies that the patient is suffering from an upper respiratory condition. The findings also suggest an abnormality in a pelvic area1578denoted by abnormal thermal image in that area indicating an elevated temperature. However, this may not be because of an abnormality; it may be because the subject is either wearing underpants, or has just recently removed them.

FIGS. 46A and 46Beach illustrate an embodiment of front and back anatomy reference images1590and1595, respectively. The front anatomy reference image1590is an embodiment of one position in which patient stands. The patient in the front anatomy reference image1590is required to stand in front of and facing a thermal camera with his or her arms at the side. Similarly, the patient in the back anatomy reference image1595is required to have his or her back towards the camera, with arms at the side. The front anatomy reference image1590and back anatomy reference image1595are used as a reference to demonstrate how a healthy muscular system should be symmetric. The images also demonstrate how muscular structures are coordinated.

FIG. 47Aillustrates a flowchart of the thermal muscle metabolism evaluation process at block1506. The process ofFIG. 47Ais described in combination withFIGS. 47B and 47C.FIGS. 47B and 47Cillustrate a front anatomy image1690and a back anatomy image1695similar to reference images1590and1595. The thermal muscle metabolism evaluation process identifies user selected muscles and compares their growth in order to determine whether or not a training regimen is effective, and/or what needs to be changed, if necessary.

In one embodiment of the thermal muscle metabolism evaluation process, the patient is first required to stand nude, and still in front of the camera (or thermal imaging device) for approximately fifteen minutes. Then at the end of the fifteen minute-period, a thermal image is taken (the “passive image”) at block1600. At this time the muscles are not stimulated. Block1600is followed by block1602(shown in phantom) to stimulate a selected muscle area. The stimulation may be achieved by performing exercise that stimulates the selected muscle area. Other types of muscle stimulation may be used such as applying electrical or other stimuli. Block1602is followed by block1604where a second subsequent thermal image of the stimulated muscle area is taken (the “active thermal image”).

By way of example, a patient may be directed to do crunches or sit-ups for the abdominal area, or push-ups for pectoral areas1692A and1692B (shown inFIG. 47B). The patient may be directed to perform exercise that stimulates the chest area when comparing the muscle areas1692A and1692B (shown inFIG. 47B). The patient may also be directed to perform exercises that stimulate the gluteus area when comparing muscle areas1697A and1697B (shown inFIG. 47C). After such stimulation, the active thermal image of the stimulated or exercised muscle area is captured at block1604.

Referring back toFIG. 47A, block1604is followed by block1606where temperature variations (ΔT) between the passive and active thermal images in the muscle areas (1692A and1692B or1697A and1697B) are compared. Block1606is followed by block1608where a determination is made whether the muscle area is symmetric. If the determination at block1608is “Yes,” block1608is followed by block1610. If the determination is “No,” block1608is followed by block1612. Block1608is optional if only symmetrical muscles areas are evaluated. Nevertheless, block1608allows each muscle to be evaluated independently, if desired by the user.

At block1610, the temperature variations (ΔT) of the symmetric sides of the muscle area are compared. Block1610is followed by block1612where the effectiveness of the stimulation or training (exercise) of the muscle area is auto-analyzed. The results of the analysis are generated at block1614. Thus, muscle area1692A is compared to1692B. Muscles are composed of cells. When cells are active, they consume energy and generate heat. A stronger muscle area has more muscle cells, while a weaker muscle area has fewer muscle cells. Therefore, a weaker muscle area generates less heat than a stronger muscle area. The difference in heat, and therefore temperature, can be calculated as the temperature variation ΔT (Block1606). The temperature variation ΔT is the absolute value of the difference of the temperatures of the muscle areas being compared. The ΔT is calculated comparing the right pectoral box (muscle area1692A) in the passive image against the right pectoral box (muscle area1692A) in the active image. Similarly, the temperature variation ΔT is calculated comparing the left pectoral box (muscle area1692B) in the passive image against the left pectoral box (muscle area1692B) in the active image. The process (shown inFIG. 47A) then computes the absolute value of the difference between the temperature variation ΔT of right pectoral box (muscle area1692A) and the temperature variation ΔT of the left pectoral box (muscle area1692B).

Since the human body is symmetric, the muscle areas should generate the same amount of heat, and the temperature variation ΔT of the muscle areas should be zero. If the result is greater than zero, the muscle masses are not symmetric and an abnormality exists. The process (shown inFIG. 47A) then compares the right pectoral box to the left pectoral box in the active image. The muscle area with the lower temperature indicates a weaker muscle mass. A physical trainer or physical therapist may interpret the results to find that the smaller muscle area needs more exercise to develop the area more quickly, and can adjust the fitness training or physical therapy regimen accordingly.

The above process may be performed on other muscle areas including symmetrical muscle areas.

FIG. 48Aillustrates a flowchart for the fat mapping evaluation process at block1508. The process ofFIG. 48Ais described in combination withFIGS. 48B and 48C.FIGS. 48B and 48Cillustrate a front anatomy image1790and a back anatomy image1795similar to images1590and1595(shown inFIGS. 46A and 46B). The fat mapping evaluation process determines and compares the fat content of certain areas. Fat is located closer than muscle to the skin surface of a person's body. Fat also has more heat resistance than muscle, and tends to absorb more heat than muscle. Therefore, an area that outputs less heat than the corresponding symmetric area has more fat and less muscle. The fat mapping evaluation process at block1508(shown inFIG. 44) analyzes front anatomy image1790and back anatomy image1795by utilizing a depth analysis algorithm to identify heat at a shallower depth.

Block1508(shown inFIG. 44) is followed by block1700(shown inFIG. 48A) wherein a passive thermal image is captured. Block1700is followed by block1702(shown in phantom) to stimulate a selected anatomical area which may contain muscle and fat. The stimulation may be achieved by performing exercise that stimulates the selected anatomical area. Other types of stimulation may also be used such as applying electrical or other stimuli to stimulate the anatomical area (1792A and1792B or1797A and1797B). Block1702is followed by block1704where a second subsequent thermal image of the stimulated anatomical area is captured (hereinafter referred to as the “active thermal image”).

Block1704is followed by block1706where temperature variations (ΔT) between the passive and active thermal images in the anatomical areas (1792A and1792B shown inFIG. 48B, or1797A and1797B shown inFIG. 48C) are determined. The temperature variations (ΔT) are determined utilizing a three-dimensional thermal image depth analysis described above.

Block1706is followed by block1708where a determination is made whether the anatomical area is symmetric. If the determination at block1708is “Yes,” block1708is followed by block1710. If the determination is “No,” block1708is followed by block1712. Block1708is optional if only symmetrical anatomical areas are evaluated. Nevertheless, block1708does permit one area to be evaluated independently, away from any other area.

At block1710, the temperature variations (ΔT) of the symmetric sides of the anatomical area are compared. Block1710is followed by block1712where the temperatures variations are auto-analyzed (such as in block20as shown inFIG. 2) for fat content and mapping in the anatomical area at block1712. Block1712is followed by block1714where the results of the analysis are generated (such as in block22as shown inFIG. 2).

FIG. 49Aillustrates a flowchart for the thermal microcirculation metabolism evaluation process at block1510(shown inFIG. 44). The process ofFIG. 49Ais described in combination withFIGS. 49B and 49C.FIGS. 49B and 49Cillustrate a human arterial system image1890and a human venous system image1895with the microcirculation areas denoted by blocks1892A,1892B,1893,1894, and1897A,1897B,1898, and1899. The microcirculation areas, denoted by blocks1892A and1892B, correspond to right and left hands. As a frame of reference, the right hand is on the left side of the page. Microcirculation areas1893ofFIGS. 49B and 1898ofFIG. 49Ccorrespond to the head. Microcirculation areas1894ofFIGS. 49B and 1899ofFIG. 49Ccorrespond to the feet.

The thermal microcirculation metabolism evaluation process at block1510(shown inFIG. 44) determines whether a patient has an abnormal vascular condition based upon analysis of the micro-capillary or microcirculation system in a patient's hands and feet (1892A,1892B,1897A,1897B,1894, and1899). Problems in a person's vascular system often appear initially in the micro-capillary or microcirculation system of a patient's hands and feet. When blood first enters the small capillaries in the hands and feet, the blood flows at a normal rate. A healthy vascular system has an even heat distribution throughout the (micro-capillary) microcirculation system. Additionally, veins and arteries do not distinguish themselves in the thermal scan unless there is blockage or infection. Differences in heat distribution are used to determine the types of problems that a patient is suffering from.

For example, in the case of a diabetic condition, the patient generally has an elevated blood sugar level, which can cause an infection in the (micro-capillary) microcirculation system. When the body responds to the infection, the heat in the infected area rises. Therefore, a higher heat in a particular point in the micro-capillary system indicates that the point is inflamed or infected. In another case, blockages in the blood may be determined. If the blood in the (micro-capillary) microcirculation system is blocked, the flow of blood is disrupted and the slower flow of blood generates less heat. On the other hand, the area, in which the blood flow is blocked, increases in temperature. If the circulation in the head is normal, normal heat mappings are viewed in the captured thermal image.

Returning again toFIG. 49A, block1510(shown inFIG. 44) is followed by block1800inFIG. 49A. At block1800, a thermal image of the microcirculation system is captured. Block1800is followed by block1806where the temperature variations are determined for the microcirculation system. Here, the symmetric sides are compared with each other. For example, as shown inFIG. 49B, hand1892A is compared to hand1892B. InFIG. 49C, hand1897A is compared to hand1897B. InFIG. 49B, box1894includes both the left and right feet. Thus, the right and left feet in area1894or1899are compared with each other. The right and left sides of the head/brain in areas1893or1898are compared. Block1806is followed by block1810where the temperature variations (ΔT) are compared for the symmetric microcirculation areas. Block1810is followed by block1812where the results are auto-analyzed (such as in block20as shown inFIG. 2) for thermal microcirculation metabolism or vascular conditions. Block1812is followed by block1814where the results of the analysis are generated (such as in block22inFIG. 2).

The microcirculation metabolism evaluation process calculates and compares the temperature variations ΔT similarly to the thermal muscle metabolism evaluation process. However, the evaluation usually focuses on the hands, feet, and head areas. Evaluation of thermal microcirculation metabolism relies on the natural symmetry of the body to compare a right hand against a left hand, and a left foot against a right foot. When higher or lower points of heat appear in right hand (1892A) and not in left hand (1892B), the process described underFIG. 49Adetects an abnormality. Similarly, if there is temperature differentiations in the left foot compared to the right foot, health evaluation system40(shown inFIG. 3) detects and identifies abnormalities.

FIG. 54Aillustrates a physiological reference image2290for use in the psychological evaluation process at block1516(shown inFIG. 44). Generally, abnormalities in different sections of the brain result in different psychological conditions. Stress and certain psychological conditions cause different parts of the brain to be more active, which, in turn, increases the metabolic rate of cells in the stressed part of the brain, which then increases the temperature of the stressed brain area. The process at block1516is essentially the same as that of the process described underFIG. 49A. The right and left sides of the brain images in block2298are captured and evaluated. While, inFIG. 49A, the auto-analysis is run for microcirculation or vascular conditions, whereas in the psychological evaluation process at block1516, the auto-analysis at block1812is for areas of abnormal temperature, which indicates potential psychological conditions.

Human beings use different parts of their brain when contemplating different functions. When a human being utilizes the brain, the portions of the brain generates heat beyond the normal heat level of the brain. This heat takes approximately eight hours to travel through the bone of the skull, which is easily detectable by thermal imaging. If a person is experiencing stress, the stress may be attributed to excessively concentrating on a particular part of the brain. A thermal image reveals abnormal levels of heat in a particular area of the brain. The brain areas that are evaluated correspond to one of the areas in a brain diagram template2295(shown inFIG. 54B). The process calculates the temperature changes (ΔT) between the left side and right side of the brain. If there is any ΔT greater than zero, an abnormality in that brain area is determined and reported.

FIG. 50Aillustrates a digestive system reference image1900.FIG. 50Billustrates a nervous system reference image1910.FIG. 50Cillustrates a lymphatic system reference image1920. The anatomical structures and system evaluation process of block1512(shown inFIG. 44) evaluates the human digestive system at block1520, the nervous system at block1522, and the lymphatic system at block1524. As can be determined from the description below, other systems may be evaluated as well.

FIG. 51Aillustrates a flowchart for an anatomical structure evaluation process for the digestive system. Block1520(shown inFIG. 44) is followed by block1930where at least one thermal image is captured for a predetermined anatomical structure, such as the digestive system, according to digestive system reference image1900. A different position (shown inFIG. 50A) is adopted for analysis of the digestive system. For this analysis, the patient's body faces the camera, while the person's head is turned to one side, as depicted in digestive system reference image1900(shown inFIG. 50A). Block1930is followed by block1932where abnormally high temperatures that correspond to the position of digestive system are located in digestive system reference image1900. Block1932is followed by block1934where the results of block1932are auto-analyzed (such as in block20inFIG. 2). Block1934is followed by block1936where the results of the auto-analysis are generated. (such as in block22inFIG. 2)

FIG. 51Billustrates a flowchart for an anatomical structure evaluation process for the nervous system. Block1522(shown inFIG. 44) is followed by block1940, where a surface thermal image of the patient's nervous system is captured. A normally functioning nervous system does not display any temperature discrepancies. However, a damaged nerve is inflamed, and therefore generates more heat, and appears as a hot point in the thermal scan. Block1940is followed by block1942where a pixel and its corresponding temperature in the image are obtained. Block1942is followed by block1944where an average temperature of a region associated with the pixel is determined. Block1944is followed by block1946where the temperature variation ΔT between each pixel in the thermal image and a particular region of the body associated with the pixel is determined. If the temperature variation ΔT is greater than zero, as determined at block1948, then the area associated with the pixel is auto-analyzed (such as in block20as shown inFIG. 2) for abnormalities and the results are generated (such as in block22as shown inFIG. 2). Block1950is followed by block1952where a determination is made whether the pixel analyzed is the last pixel. If the determination is “Yes,” the process ends. However if the determination is “No”, then block1952is followed by block1954. At block1954, the next pixel is obtained and the process loops back to block1942. The process is complete when all pixels are evaluated based on nervous system reference image1910(shown inFIG. 50B). Returning again to block1948, if the temperature variation ΔT is not greater than zero, as determined at block1948(i.e. determination is “No”), then block1948is followed by block1952and so on.

FIG. 51Cillustrates a flowchart for an anatomical structure evaluation process for the lymphatic system. Block1524(shown inFIG. 44) is followed by block1960, where a thermal image of patient's lymphatic system is captured. The lymphatic system is composed of certain points called lymph nodes connected by lymph vessels, lymph capillaries, and lymph ducts. Infected or inflamed lymph nodes generate higher temperature, and are indications of problems in the lymphatic system. Block1960is followed by block1962, where the lymphatic system, according to a lymphatic system reference image1920(shown inFIG. 50C), first identifies the temperature points at which lymph nodes exist. Block1962is followed by block1964where a determination is made whether a lymph node has a high temperature. If the determination at block1964is “No,” then block1964is followed by block1966where a determination is made whether the last node is reached. If the determination at block1966is “Yes,” the process ends. If the determination at block1966is “No,” then block1966is followed by block1967where the next lymph node is obtained. Block1967returns to block1962until all lymph nodes are analyzed.

At block1964, if the determination is “Yes,” then a pixel and its corresponding temperature are obtained at block1968. Block1968is followed by block1970where the temperature variation (ΔT) between the pixel(s) in the thermal image and temperatures of the paths according to the lymphatic system reference image1920are calculated and compared. Block1970is followed by block1972. At block1972, a determination is made whether temperature variation ΔT is greater than zero. If the determination is “No,” block1972is followed by block1976where a determination is made whether the last pixel is reached. If the determination at block1976is “Yes,” the process ends. However, if the determination at block1976is “No,” block1976loops back to block1968to get the next pixel in the image. Returning again to block1972, if the determination regarding the temperature variation ΔT is “Yes”, then block1972is followed by block1974. Block1974auto-analyzes and generates results. For example, an alert for an abnormality is generated, if necessary.

FIG. 52Aillustrates a flowchart for a muscle endurance evaluation process at block1514(shown inFIG. 44). The muscle endurance evaluation process is described in combination withFIG. 52B.FIG. 52Billustrates a front anatomy reference image2090. Block1514is followed by block2000where a passive thermal image is captured of the patient according to front anatomy reference image2090. However, a back image may also be used alone or in combination with the front anatomy reference image2090.

Block2000is followed by blocks2002and2004shown in parallel. At block2002, the muscle area under evaluation, such as shown in boxes2092A and2092B, is stimulated. At block2004, active thermal images are captured of the stimulated muscle area. Evaluation of the muscle endurance determines the endurance and fitness of different types of muscle areas. There are two types of muscles in the human body. Type I muscle is a slow oxidative, slow twitch, or red muscle. Type I muscle carries more oxygen and is used for sustained aerobic activities, such as long-distance running. Type II muscle is a fast twitch muscle, which generally contracts and expands more rapidly than Type I muscle, and is used for rapid anaerobic activities, such as sprinting. Evaluation of muscle endurance is used to gauge muscle growth in a patient, which gives a trainer or physical therapist an overview of the effectiveness of the training program or therapy.

In one embodiment, at block2002, the patient is instructed to exercise for fifteen minutes. While the patient is performing exercise or the muscle area is stimulated through other means, thermal images of the patient are captured every few minutes (“active images”) at block2004. A separate set of images must be taken for each session. Blocks2002and2004are followed by block2006where the temperature variations (ΔT) between the passive and active images are determined. The system compares the temperature of each muscle area of the active images against each muscle area of the passive images to calculate the ΔT.

While the patient exercises or the patient's muscle area is stimulated by other means, the temperature variation (ΔT) from the muscles at rest increases until temperature variation (ΔT) reaches a constant value. The constant value once reached is maintained until the patient stops exercising. Block2006is followed by block2008where a determination is made whether the final ΔT is reached. If the determination is “No,” block2008loops back to blocks2002and2004so that the exercise or stimulation continues, and active images continue to be captured. If the final ΔT is reached and the determination at block2008is “Yes,” then block2008is followed by block2010. At block2010, the rate of change of the temperature variation (ΔT) is determined.

The temperature variation (ΔT) combined with the final ΔT maintained determines whether the muscle areas of a patient are composed of more Type I or Type II muscles. The rate of change in the temperature variation (ΔT) of the muscles demonstrates whether the muscles are burning energy quickly or slowly. A high rate of change in the temperature variation (ΔT) of a patient, coupled with a higher final ΔT indicates that the muscles developed are more suited for quick activities that need to rapidly burn energy, which in turn, indicates a greater growth in Type II muscle. A slow rate of change in the temperature variation (ΔT), coupled with a lower final ΔT, indicates that the muscles developed are more suited for prolonged activities which use energy slowly and evenly, which in turn, indicates a greater growth of Type I muscle.

Block2010is followed by block2012where a determination is made whether the temperature variation (ΔT) combined with the final ΔT maintained are both high. If the determination at block2012is “Yes,” block2012is followed by block2014where the muscle area is indicated as a Type II muscle. However, if the determination at block2012is “No,” then the muscle area is indicated as a Type I muscle at block2016.

In one embodiment, the evaluation of the muscle endurance is repeated for several months, during which the trainer or physical therapist can evaluate whether the status of muscle growth against its intended purpose.

InFIG. 52B, only one set of symmetrical muscles is shown. However, other muscle areas are also evaluated. InFIG. 52B, the muscles in box2092A include at least one of the pectoral muscle areas, and the biceps brachii located on the right upper arm. The muscles in box2092B also include at least one of the pectoral muscle areas, and the biceps brachii located on the left upper arm. The gluteus area inFIG. 47Ccan also be evaluated as well as with other muscle areas.

The evaluation of muscle endurance can also be used to determine whether a patient's muscles are damaged. This evaluation, in turn, is useful for trainers or physical therapist to determine whether their regimen is overly intense. The process for evaluating damaged muscles is similar to the process described inFIG. 47A. However, in one embodiment, the active thermal image is taken approximately 12 hours after stimulation. Normally, after a person exercises or the person's muscles are stimulated, it takes approximately 12 hours for the muscles to return to their “at rest” temperature without any additional relaxants or therapies, such as hot showers and saunas. As can be appreciated, the amount of time necessary to return to “at rest” temperature may vary from individual to individual.

In one embodiment to evaluate damaged muscles, a passive thermal image of the patient “at rest” is first captured. Then, the muscle is stimulated through exercise or other means of stimulation for a predetermined time such as one hour. The patient returns the following day, approximately 12 hours later. An active image is captured of the patient after the patient is undressed. This active thermal image is then compared to the original passive image taken the previous day. By way of example,FIG. 53illustrates a front anatomy reference image2190for muscle damage evaluation. InFIG. 53, the pectoral muscle area in boxes2192A and2192B are selected for evaluation.

Based on the evaluation utilizing the process depicted inFIG. 47A, a higher temperature for a muscle area in the more recent image (active image) indicates that the heat in the muscle area is dissipating more slowly than normal. If heat dissipates more slowly, or has not changed back to normal, it indicates that the muscle is likely damaged.

As can be readily seen from the above, health evaluation system40(shown inFIG. 3) utilizes TMT mapping technology capable of providing warnings and locating degenerative diseases. Health evaluation system40also provides an on-going monitoring of one's physical health. A core aspect of health evaluation system40is that it scans and analyzes below-the-surface areas of the head and body. A patient's fat, muscle distribution, and other functions are also analyzed utilizing the mapping technology. The positions and scope of an individual's pains and inflammations can also be observed.

FIG. 55illustrates an overview of the TMT mapping technology assembly2200for use in health evaluation system40(shown inFIG. 3). TMT mapping technology assembly2200includes, in one embodiment, technologies that enable health evaluation system40to perform the functions described above. TMT mapping technology assembly2200includes a TMT analysis technology module2201constructed and arranged to analyze the texture of the thermal images. TMT mapping technology assembly2200further includes a thermal structure analysis technology module2202, a thermal sequence mapping technology module2204, and a thermal signature analysis technology module2206. In the context herein, “structure” is actually the three-dimensional view of the thermal image, as shown inFIGS. 41B,42B, and43B, as used in the depth analysis. On the other hand, “signature” is the two-dimensional view of a thermal image, such as best seen inFIGS. 41A,42A, and43A. Thermal structure analysis technology module2202analyzes and processes three-dimensional views of thermal images for abnormalities. On the other hand, thermal signature analysis technology module2206analyzes and processes two-dimensional views of thermal images for abnormalities.

The thermal sequence mapping technology module2204includes a software, hardware and/or firmware to perform the cascade chromatography process. In general, the cascade chromatography process creates a series of thermal images that start with the small white area(s), and end with a larger white area, as shown inFIGS. 40A,40B, and40C. It is not uncommon to produce a sequence of 30 or more series of thermal images.

Module2204is part of sectional view module90that contains the depth analysis and also displays the sequence of thermal images of the cascade chromatography analysis to the user. This involves thermal sequence mapping technology, which generates the sequence or series of images with a small white spot and ends with a larger white spot.

While performing the cascade chromatography analysis, the longer the analysis takes (when more thermal images result from the cascade chromatography analysis), the deeper is the source of the heat. For example, if there are only 5 images before the cascade chromatography analysis is completed, the heat is shallower. Alternatively, if there are 50 images, the abnormal heat is coming from a deeper area of the body.

Areas of abnormally high temperature, as determined in the analysis, conform to general shapes. The shapes formed by the analysis are known as a “signature” and vary according to a particular anatomical area and the abnormality that exists within that anatomic area. In one embodiment of a signature, an illness within the vascular system would show abnormal temperatures in the thermal image. The pixels that correspond to abnormal temperatures in the vascular system would form a tube-like shape.

The TMT mapping technology assembly2200includes a TMT data collection technology module2208, a thermal database and management technology system module2210, a thermal data transmission technology module2212, and a TMT structure analysis technology module2214. Module2208allows users and operators to collect data for carrying out the processes described herein. Module2210develops and manages the database data and constructs. Module2212enables users and operators to transmit, receive, and retrieve data from remote sites. Module2214provides the hardware for carrying out the instructions from Module2202.

FIG. 56illustrates preventive medicine treatment through a treatment process2250. Process2250begins with a fatigued status phase2251, which involves a potentially ill or fatigued patient. The illness either stems from a physical status2252relating to physical abnormalities or illness, or a mental status2254which is related to psychological abnormalities or illness. A patient in fatigued status phase2251then seeks a diagnosis under an initial status phase2256. Initial status phase2256indicates whether a patient is undergoing TMT scanning for the first time. Under initial status phase2256, an initial thermal scan of the patient is captured. If no abnormalities are detected in the initial scan, the patient has a normal status2258and does not need further treatment or analysis. If abnormalities are detected, then the patient has an abnormal status2260. After the initial scan, a patient under abnormal status2260is relaxed using various methods, such as a series of massages or saunas, or floating in a small pool of water. After relaxation, the patient then undergoes TMT scanning again.

If no abnormalities are detected, then the abnormalities were likely due to stress. Stress often causes psychological conditions, and can also induce actual or perceived physical illness. If there are any abnormalities after relaxation, then the abnormalities are most likely physical and the person may be admitted to a hospital or a clinic to be treated, and the patient proceeds to a final status phase2262. The patient is then treated for any illness. If the treatment is successful, the patient is in a healthy status2264and needs no further treatment. If the initial treatment is not successful, then the patient is in a sick status2266.

A patient in sick status2266then moves to the dependent status phase2268. A patient in phase2268either has an integrated status2270or a stable status2272. A patient with status2270undergoes constant treatment, involving periodic scans with TMT technology to determine the effectiveness of the treatment. One embodiment of a patient with status2270is a person who has cancer and is treated with chemotherapy or radiotherapy. The cancer is treated over a period of time and generally requires periodic TMT scans to determine the effectiveness of the treatment. A patient in status2272successfully undergoes further treatments, is now healthy, and needs no further treatment.

FIG. 57illustrates a TMT database structure overview. A TMT database2300is in the center of a plurality of concentric rings. The concentric rings include a remote diagnosis ring2302, an Internet ring2304, and a world TMT terminal ring2306. Each ring provides the database information and management for remote diagnosing, Internet communications, and TMT operations worldwide according to a variety of international medical standards. This provides the necessary information for the human anatomy based on race, color, age, environment, etc.

FIG. 58illustrates a TMT database assembly2350. Assembly2350provides and archives information for tracking, monitoring and evaluation of various patients. Assembly2350is used in many processes, including but not limited to: a group screening2352, a disease monitoring2354, a curative effect evaluation2356and a drug optimization2358. In one embodiment, group screening2352stores information pertaining to one or more patients' diseases and treatments in assembly2350. The patient information in assembly2350is used in monitoring2354, evaluation2356, and optimization2358. Monitoring2354is a process that enables a user to track a patient's diseases. Evaluation2356is a process that records the effect of different treatments on patients and stores the treatment information in assembly2350. Optimization2358is a process that retrieves information pertaining to the effect of different treatments from assembly2350and determines which treatment is best for the patient.

FIG. 59illustrates a database structure relating to one of the components of system40. A Report object2400contains fields that correspond to values and settings for the thermal image analysis report. A BaseInf object2402contains fields for information associated with a patient record. A Comp object2404contains fields for information regarding types of tests and comparisons. An IRData object2406contains information about the thermal image. A Polygon object2408contains information for the polygons contained in a three dimensional thermal image. A Coordinate object2410contains the x and y coordinates of a point within Polygon object2408. DotTemp objects2412and2414contain information for the pixels in a thermal image. A RectTemp object2416contains information about a particular area within a thermal image defined by the two pairs of x and y coordinates.

FIG. 60illustrates a block diagram for a remote TMT analysis process2450. Process2450begins with data collection at block2452. The collected data is transmitted via data transmission block2454. Block2454is followed by a data analysis center block2456. Block2456is followed by three parallel blocks—2458for sectional view analysis, block2460for analysis of heat source distribution, and block2462for heat depth analysis. Blocks2458,2460, and2462are followed by block2464where the report of the analysis is generated. Block2464returns the information to block2456(data analysis center), which transmits the results through block2454to block2466for digital reporting.

FIG. 61illustrates a block diagram for remote TMT health screening system. The system includes image capturing at block2500. The captured information is sent to the screening division of a data assessment center at block2514. The data assessment center accesses data from a plurality of databases. The database includes complaint database2502, a sign database2504, an assay database2506, an imaging database2508, a μ-MRA database2510, and a TMT database2512.

FIG. 62illustrates a network for remote TMT health screening or analysis2550. Network2550supports a satellite communication2552, a modem communication2554, a cable communication2556, and a wireless communication2558. The remote sites S1, S2, S3, and S4include a plurality of distinct health evaluation systems40(shown inFIG. 3) that are not necessarily locally adjacent. Each health evaluation system40at site S1is capable of transmitting and receiving data from a central database site2560.

The user of any one health evaluation system40(shown inFIG. 3) can access a central database2560which contains patient information and medical information. Users can potentially access database2560through a satellite communication2552, Intranet or Internet networks via modem2554, or cable communication2556, or wireless communication2558.

FIG. 63illustrates a network diagram for multiple networks through which a user can transmit analysis data to and from the patient database. In one embodiment, data stored in a database2600is transferred over the Internet through various servers, facilitated by different communication protocols2602. In another embodiment, data stored in a database2604or behind a firewall as sensitive data in various databases2606is transmitted through an internal corporate network and accessible through various communication protocols2608. Data in a corporate network is accessible through remote sites2610using various communication protocols.

In one or more configurations, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and without limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technology such as infrared, radio, and microwave is included in the definition of medium.

Disk and disc, as used herein, include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and blu-ray disc, where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

A person skilled in the art would recognize that other components and/or configurations might be utilized in the above-described embodiments, if such other components and/or configurations do not depart from the intended purpose and scope of the present invention. Moreover, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms, comprises and comprising, should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced.

While the present invention has been described in detail with regards to the above described embodiments, it should be appreciated that various modifications and variations may be made in the present invention without departing from the scope or spirit of the invention. In this regard, it is important to note that practicing the invention is not limited to the applications described hereinabove. Many other applications and/or alterations, including alterations to graphical user interfaces, may be utilized provided that such other applications and/or alterations do not depart from the intended purpose of the present invention.

Also, features illustrated or described as part of one embodiment can be used in another embodiment to provide yet another embodiment such that the features are not limited to the specific embodiments described above. Thus, it is intended that the present invention cover all such embodiments and variations as long as such embodiments and variations come within the scope of the appended claims and their equivalents.