INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND COMPUTER-PROGRAM-READABLE RECORDING MEDIUM

An information processing apparatus acquires a plurality of images related to a target person who receives a service and image information added to each of the plurality of images, extracts an identification image including a subject to identify the target person by analyzing the plurality of images, acquires, based on the image information, image capturing information of each of the plurality of images, acquires, based on identification information corresponding to the identification image, service information regarding a service received by a target person associated with the identification information, performs matching between the image capturing information of a target image and the service information, the target image different from the identification image from among the plurality of images, and controls, based on a result of the matching, the identification information to be stored in association with each of the target images.

BACKGROUND

Field

The present disclosure relates to an image management technique.

Description of the Related Art

A technique of registering an image of a patient in association with an electronic medical chart of the patient has been utilized. Japanese Patent Application Laid-Open No. 2009-20547 discusses a technique of simultaneously importing content information and identification information from a paper medium on which the content information and the identification information are printed, and registering the content information in association with the identification information of a patient. Japanese Patent Application Laid-Open No. 2016-42258 discusses a technique of identifying an image including identification information of a patient as a subject, from among a plurality of imported images, and registering an image selected from among images following the identified image in association with identification information of the patient.

In the technique discussed in Japanese Patent Application Laid-Open No. 2009-20547, however, in a case where content information and identification information are imported as separate images in random order, content information and identification information of the patient cannot be correctly associated. In the technique discussed in Japanese Patent Application Laid-Open No. 2016-42258, in a case where the order of image capturing is not uniquely determined, an imported image and identification information of the patient cannot be correctly associated. Thus, an image of a patient has been sometimes associated with wrong patient information.

SUMMARY OF THE INVENTION

In view of the foregoing, the present disclosure is directed to preventing an image of a target person from being associated with identification information of a wrong target person.

According to an aspect of the present disclosure, an information processing apparatus includes one or more memories, and one or more processors in communication with the one or more memories, wherein the one or more processors and the one or more memories are configured to, acquire a plurality of images related to a target person who receives a service and image information added to each of the plurality of images, extract an identification image including a subject to identify the target person by analyzing the plurality of images, acquire, based on the image information, image capturing information of each of the plurality of images, acquire, based on identification information corresponding to the identification image, service information regarding a service received by a target person associated with the identification information, perform matching between the image capturing information of a target image and the service information, the target image different from the identification image from among the plurality of images, and control, based on a result of the matching, the identification information to be stored in association with each of the target images.

DESCRIPTION OF THE EMBODIMENTS

Embodiments of the present disclosure will be described with reference to the drawings. The following embodiments, however, are not intended to be limiting, and not all the combinations of the features described in the present embodiments are essential as solutions to the problem disclosed in the present disclosure. In the following description, same components are denoted with the same reference number. Each of the embodiments of the present disclosure described below can be implemented solely or as a combination of a plurality of the embodiments or features thereof where necessary or where the combination of elements or features from individual embodiments in a single embodiment is beneficial.

FIG.1illustrates an entire configuration example of a medical system according to a first exemplary embodiment. The medical system is a system for managing information regarding a patient. The patient is an example of a target person who receives a medical service. As illustrated inFIG.1, the medical system includes an imaging apparatus101, an electronic medical chart system104, an image management system105, and an image management apparatus106. These apparatuses are connected to each other via a network102. The image management apparatus106controls execution of various types of processing that is performed by an information processing apparatus (not illustrated).

The imaging apparatus101connects to the network102in response to an imaging apparatus operator turning ON the power, and communicates with another apparatus (not illustrated) on the network102. The imaging apparatus101maintains the communication-executable state until the power is turned OFF. In the present exemplary embodiment, the imaging apparatus101is a portable compact camera, such as a commercially available digital camera, and includes a display device for displaying captured images, and an input-output device for inputting various operations, such as a selection of information regarding the imaging apparatus101or information regarding the imaging apparatus operator. The imaging apparatus101generates visible light image data by capturing an image of an affected area107of a patient or an identification object, such as a one-dimensional (1D) code in which a patient ID is embedded. In the following description, an image captured by the imaging apparatus101will be described as visible light image data. The imaging apparatus101adds header information to an image, and transmits the image to the image management apparatus106via the network102.

The image management apparatus106receives an image from the imaging apparatus101. Header information is added to the image. The header information is an example of image information. The header information contains image capturing information. The image capturing information contains an image capturing time, imaging apparatus operator information, and imaging apparatus information. The image management apparatus106analyzes an image received from the imaging apparatus101, and determines whether the image is an affected area image or an identification image. The identification image is an image including an identification object, such as a 1D code or a two-dimensional (2D) code in which a patient ID is stored. The affected area image is an image including the affected area107of a patient. The affected area image is a patient image to be diagnosed, and is an example of a target image obtained by capturing an image of a target person.

The electronic medical chart system104is connected with an electronic medical chart display terminal103via a High-Definition Multimedia Interface (HDMI®) cable such that communication is executable. In response to a request from the electronic medical chart display terminal103, the electronic medical chart system104communicates with the image management apparatus106and the image management system105, and performs transmission and reception of data in electronic medical chart generation and edit processing. The electronic medical chart display terminal103communicates with the electronic medical chart system104, and displays an electronic medical chart, receives entry made when an electronic medical chart is generated, and performs information addition processing on a displayed image.

The electronic medical chart system104is also connected with a medical information database (DB)108such that communication is executable. The medical information DB108stores medical information of a patient in the medical system. In response to a request from another apparatus on the network102, the electronic medical chart system104acquires appropriate medical information from the medical information DB108. The medical information contains patient information, a medical care start time, a medical care end time, a visited diagnosis and treatment department, a position in a body of a past injury or disease, and a diagnosis result. The patient information contains a patient ID, a name, a gender, a birth date, a medical history, and allergy information of a patient. The patient ID is an example of identification information of a patient. The medical information is an example of medical service information in the medical system. The medical information DB108can be stored in a storage device inside the electronic medical chart system104.

In response to an acquisition request of information regarding a patient from the image management apparatus106, the electronic medical chart system104acquires a series of information pieces regarding the patient from the medical information DB108using a patient ID included in the acquisition request as a key. In the present exemplary embodiment, in response to a request from the image management apparatus106, the electronic medical chart system104searches the medical information DB108for medical information using a patient ID and date and time when diagnosis and treatment have been performed, and acquires an applicable patient and information regarding diagnosis and treatment that have been performed at the date and time. The electronic medical chart system104transmits the acquired information to the image management apparatus106.

The electronic medical chart system104is also connected with a facility information DB109such that communication is executable. The facility information DB109stores information regarding a medical staff and an apparatus. In response to a request from another apparatus on the network102, the electronic medical chart system104acquires applicable imaging apparatus operator information and imaging apparatus information from the facility information DB109. The imaging apparatus operator information contains an imaging apparatus operator ID, an imaging apparatus operator job category, an imaging apparatus operator name, and an imaging apparatus operator department. The imaging apparatus operator department indicates a diagnosis and treatment department (hospital department) to which the imaging apparatus operator belongs. The imaging apparatus information contains an imaging apparatus ID, an imaging apparatus management department, an imaging apparatus manager, and an imaging apparatus model name.

The facility information DB109can be stored in a storage device inside the electronic medical chart system104. The electronic medical chart system104searches the facility information DB109for applicable imaging apparatus operator information using an imaging apparatus operator ID as a key, and searches the facility information DB109for applicable imaging apparatus information using an imaging apparatus ID as a key. The electronic medical chart system104transmits retrieved information to a request source.

The image management system105is connected with an image information DB110such that communication is executable. The image information DB110stores an image and information regarding an image. The image management system105receives an image captured by the imaging apparatus101, via the image management apparatus106, and stores the received image into the image information DB110in a state in which a patient ID and image capturing date and time are associated. The image information DB110can be stored in a storage device inside the image management system105. In a case where an image acquisition request is issued from the electronic medical chart system104or the image management apparatus106, the image management system105transmits an image applicable to a designated condition to a request source.

The affected area107of a patient is a diagnosis and treatment target in the medical system. In some cases, a state of an injury or a disease is diagnosed based on the appearance of a symptom of a whole body, and in other cases, a state of an injury or a disease is diagnosed based on the appearance of a symptom of a part of a body. In a case where a state of an injury or a disease is diagnosed based on the appearance of a symptom of a whole body, a large range, such as a head, a body trunk, a lower extremity, or an upper extremity, is set as a diagnosis and treatment target.

Information to be recorded is not limited to an injury or a disease, and a case where the state of a region of a body that is to be observed, such as the inside of a mouth cavity, is recorded is also included. For example, a teeth alignment state or a teeth exfoliation state can also be recorded.

An HDMI® cable or a universal serial bus (USB) are examples of communication interfaces that can be used by the components of the above-described medical system to communicate with each other. These communication interfaces are not seen to be limiting, and any communication interface that would enable practice of the present embodiment is applicable.

In the medical system of the present exemplary embodiment, as illustrated inFIG.1, the imaging apparatus101, the electronic medical chart display terminal103, the electronic medical chart system104, the image management system105, and the image management apparatus106are described as separate components of the medical system. In another exemplary embodiment, functions of two or more of these components can be implemented by one component. For example, the electronic medical chart display terminal103can include a function of the imaging apparatus101.

<Configuration of Image Management Apparatus>

FIG.2illustrates a hardware configuration example of the image management apparatus106. The image management apparatus106includes a central processing unit (CPU)201, a read-only memory (ROM)202, a random access memory (RAM)203, a display204, a hard disk drive (HDD)205, an input device206, and an interface (I/F)207, where these components are connected via a bus208. The CPU201controls operations of the image management apparatus106. The ROM202stores programs and various types of data. The CPU201executes programs stored in the ROM202to achieve processing of various procedures and various functions of the image management apparatus106that are described below.

The RAM203is used as a main memory and a temporary storage area, such as a working memory. The HDD205stores images, an image list (FIGS.4and7) storing information regarding images, and a patient list (FIG.5) storing information regarding a patient that is associated with an identification image. Under control of the CPU201, the display204displays various processing results and a user interface (UI) screen to be operated by an operator. The input device206inputs operation information from the operator. The CPU201controls the I/F207to perform data transmission and reception with another apparatus on the network102.

FIG.3is a flowchart illustrating image registration processing executed by the image management apparatus106. The image registration processing is processing to determine whether a processing target image is an affected area image or an identification image and registering the processing target image. The processing of the flowchart can be started in response to an instruction from the operator or can be started at a predetermined timing.

Before starting the processing of the flowchart, the CPU201acquires a processing target image from the imaging apparatus101.

In step S300, the CPU201substitutes a default value 0 into a counter i for processing all the processing target images.

In step S301, the CPU201determines whether the counter i indicates a value less than the number of processing target images. In a case where the CPU201determines that the counter i indicates less than the number of processing target images (YES in step S301), the processing proceeds to step S302. In a case where the CPU201determines that the counter i indicates greater than or equal to the number of processing target images (NO in step S301), the CPU201determines that a series of processes have been performed on all of the processing target images, and ends the processing of the flowchart.

In step S302, the CPU201acquires image capturing information of an i-th image. The image capturing information is acquired from header information of the i-th image. The image capturing information contains an image capturing time, an imaging apparatus operator ID, and an imaging apparatus ID. The CPU201stores the acquired image capturing information into the RAM203.

In step S303, the CPU201communicates with the electronic medical chart system104via the network102, and acquires imaging apparatus operator information using the imaging apparatus operator ID acquired in step S302, as a key. The imaging apparatus operator information contains the imaging apparatus operator department. The CPU201stores the acquired imaging apparatus operator information into the RAM203.

In step S304, the CPU201communicates with the electronic medical chart system104via the network102, and acquires imaging apparatus information using the imaging apparatus ID acquired in step5302as a key. The CPU201stores the acquired imaging apparatus information in the RAM203.

In step S305, the CPU201performs identification information analysis processing on the i-th image. In the present exemplary embodiment, the identification information analysis processing is 1D code reading processing.

In step S306, the CPU201determines whether the i-th image is an identification image, based on a result of the identification information analysis processing. In a case where 1D code reading processing succeeds, the CPU201determines that the i-th image is an identification image (YES in step S306), and the processing proceeds to step S307. In a case where 1D code reading processing fails, the CPU201determines that the i-th image is an affected area image (NO in step S306), and the processing proceeds to step S309. This processing enables the CPU201to determine whether a processing target image is an identification image or an affected area image.

In a case where the CPU201determines that the processing target image is an identification image (YES in step S306), the CPU201sets an image type to “identification”, and stores a read patient ID in the RAM203.

In step S307, the CPU201communicates with the electronic medical chart system104via the network102, and acquires, using the patient ID read in step S305and the image capturing time acquired in step S302as a key, medical information regarding diagnosis and treatment performed at a corresponding time on a corresponding patient. Specifically, the CPU201acquires medical information containing a patient ID identical to the read patient ID, and an image capturing time falling between a medical care start time and a medical care end time. The medical information contains patient information (patient name), a medical care start time, a medical care end time, and a visited diagnosis and treatment department.

The CPU201stores the acquired medical information in the RAM203.

In step S308, the CPU201registers the information to be stored in the RAM203as a last record of a patient list (FIG.5) stored in the HDD205. The processing then proceeds to step S310.

In step S309, the CPU201sets an image type to an “affected area”.

In step S310, the CPU201registers the set image type and various types of information that is stored in the RAM203as a last record of an image list (FIG.4) stored in the HDD205.

In step S311, the CPU201deletes information regarding the i-th image from the RAM203and increments the counter i. The processing then returns to step S301.

According to the above-described image registration processing, it is determined whether a processing target image is an affected area image or an identification image, and image capturing information of an affected area image, image capturing information of an identification image, and medical information associated with a patient ID obtained from the identification image are acquired, and these pieces of information are stored for each image. Accordingly, information necessary for association processing (FIG.6described below) of a patient and an affected area image, which will be described below, can be managed for each image. In the image registration processing, only information necessary for the association processing inFIG.6can be acquired. For example, in a case where only an imaging apparatus ID is required as imaging apparatus information, the processing in step S305can be skipped.

FIG.4is a diagram illustrating an example of the image list holding information regarding an image. In the present exemplary embodiment, the image list inFIG.4is stored in the HDD205of the image management apparatus106.

In step S310ofFIG.3, the record of each image is added and registered into the image list. Records414to433registered in the image list each contain information regarding an image identification number401, an image type402, an image capturing time403, an imaging apparatus operator ID404, an imaging apparatus operator department405, and an imaging apparatus ID406. The records414to433also each contain information regarding a patient ID407, a patient name408, a medical care start time409, a medical care end time410, a diagnosis and treatment department411, an estimated patient ID412, and a mismatch condition413.

The image identification number401includes an identification number for uniquely identifying a processing target image. In the present exemplary embodiment, an identification number is allocated in the registration order of images. The image type402includes, in a case where the processing target image is determined to be an identification image, “identification”, and in a case where the processing target image is determined to be an affected area image, includes “affected area”. The image capturing time403includes the image capturing time contained in the image capturing information acquired in step S302. The imaging apparatus operator ID404includes the imaging apparatus operator ID contained in the image capturing information acquired in step S302. The imaging apparatus operator department405includes the department of the imaging apparatus operator that is contained in the imaging apparatus operator information acquired in step S303. The imaging apparatus ID406includes the imaging apparatus ID contained in the image capturing information acquired in step S302.

In a case where it is determined that the processing target image is an identification image, information is also registered in the patient ID407, the patient name408, the medical care start time409, the medical care end time410, and the diagnosis and treatment department411. The patient ID407includes the patient ID read in step S305. The patient name408includes the patient name contained in the medical information acquired in step S307. The medical care start time409includes the medical care start time contained in the medical information acquired in step S307. The medical care end time410includes the medical care end time contained in the medical information acquired in step S307. The diagnosis and treatment department411includes the diagnosis and treatment department contained in the medical information acquired in step S307. As illustrated inFIG.4, the records414,419,425, and429with the image type402storing “identification” have information in the patient ID407, the patient name408, the medical care start time409, the medical care end time410, and the diagnosis and treatment department411.

In a case where it is determined that the processing target image is an affected area image, information is registered in the estimated patient ID412and the mismatch condition413by the association processing inFIG.6. In the estimated patient ID412, “unknown” is stored as a default value, and in a case where a patient is estimated in the association processing inFIG.6, a patient ID of the estimated patient is stored. In a case where a patient cannot be estimated in the association processing inFIG.6, an item that is a cause of the mismatch is stored in the mismatch condition413.

Information to be registered in the image list inFIG.4can be limited to information to be used for a matching in the association processing inFIG.6from among various types of information acquired in the image registration processing inFIG.3. In another exemplary embodiment, information to be registered in the image list inFIG.4can be all of the various types of information acquired in the image registration processing inFIG.3. For example, in a case of the matching inFIG.6, the imaging apparatus operator ID404not to be used for the matching can be skipped from the registering into the image list. In another example, an imaging apparatus management department or an imaging apparatus model name can also be registered into the image list.

FIG.5is a diagram illustrating an example of a patient list holding information regarding a patient associated with an identification image. In the present exemplary embodiment, the patient list inFIG.5is stored in the HDD205of the image management apparatus106. In step S308ofFIG.3, the record is added and registered in the patient list for each identification image. Records512to519registered in the patient list each contain information regarding a patient number501, a patient ID502, a patient name503, an image capturing time504, a medical care start time505, a medical care end time506, and a diagnosis and treatment department507. The records512to519each contain information regarding an imaging apparatus operator ID508, an imaging apparatus operator department509, an imaging apparatus ID510, and a processing status511.

The patient number501includes an identification number for sequentially performing the association processing inFIG.6on a processing target patient. The patient ID502is the same as the patient ID407. The patient name503is the same as the patient name408. The image capturing time504is the same as the image capturing time403. The medical care start time505is the same as the medical care start time409. The medical care end time506is the same as the medical care end time410. The diagnosis and treatment department507is the same as the diagnosis and treatment department411. The imaging apparatus operator ID508is the same as the imaging apparatus operator ID404. The imaging apparatus operator department509is the same as the imaging apparatus operator department405. The imaging apparatus ID510is the same as the imaging apparatus ID406. The processing status511includes information indicating whether the association processing inFIG.6has been executed. The processing status511includes “unprocessed” as a default value, and when the association processing inFIG.6is executed, “unprocessed” is updated to “processed”.

Information to be registered in the patient list inFIG.5can be limited to information to be used for the matching in the association processing inFIG.6from among various types of information acquired in the image registration processing inFIG.3as information regarding an identification image. In another exemplary embodiment, information to be registered in the patient list inFIG.5can be all of the various types of information acquired in the image registration processing inFIG.3as information regarding an identification image.

<Association Processing of Patient and Affected Area Image>

FIG.6is a flowchart illustrating the association processing that is executed by the image management apparatus106. The association processing is processing of matching between information regarding an identification image and image capturing information of an affected area image, determining whether a matching result satisfies a condition of association, and associating a patient associated with the identification image and the affected area image based on the determination result. A processing target patient is a patient to be registered in the patient list inFIG.5.

A processing target affected area image is an image with the image type402including an “affected area” from among images to be registered in the image list inFIG.4. The processing of the flowchart can be started in response to an instruction from an operator or can be started at a predetermined timing.

In step S601, the CPU201extracts a processing target patient from unprocessed patients from among patients registered in the patient list inFIG.5. Specifically, the CPU201reads, from the patient list inFIG.5, information regarding a patient with the medical care end time506including a time earlier than a latest image capturing time403. In the present example, the image capturing time403of the record433registered as a last record of the image list is “15:23”. Thus, as a patient with the processing status511including “unprocessed” and the medical care end time506including a time earlier than “15:23”, information regarding the records514to517(hereinafter, referred to as patient data pieces514to517) is read.

In step S602, the CPU201determines whether the number of patients extracted in step S601is greater than 0. In a case where the CPU201determines that the number of extracted patients is greater than 0 (YES in step S602), the processing proceeds to step S603. In a case where the CPU201determines that the number of extracted patients is 0 (NO in step S602), the CPU201determines that there is no processing target patient, and ends the processing of the flowchart.

In step S603, the CPU201substitutes 0 into a counter p for performing a series of processes on a processing target patient.

In step S604, the CPU201determines whether the counter p is a value less than the number of processing target patients. In a case where the CPU201determines that the counter p is a value less than the number of processing target patients (YES in step S604), the processing proceeds to step S605. In a case where the CPU201determines that the counter p is greater than or equal to the number of processing target patients (NO in step S604), the CPU201determines that the matching between affected area image and all processing target patients has been completed, and the processing proceeds to step S618.

In step S605, the CPU201reads information regarding a p-th patient from among the processing target patients.

In step S606, based on the information read in step S605, the CPU201extracts an unprocessed image captured during a medical care time period, during which the processing target patient has received medical care, from among affected area images registered in the image list inFIG.4. Specifically, the CPU201extracts an image with the image type402including an “affected area”, the image capturing time403falling between the medical care start time505and the medical care end time506, and the estimated patient ID412including “unknown”. The CPU201stores the image identification number401of the extracted image in the RAM203. In the above-described processing, the image management apparatus106performs the matching between an image capturing time of an affected area image and a medical care time period during which a patient has received medical care. Based on the matching result, the image management apparatus106sets the processing target affected area image as a candidate to be stored in association with the processing target patient.

An example where a predetermined condition is a condition that an image capturing time falls in a medical care time period of a patient will now be described. In a case where, from among pieces of data of the patients extracted in step S601, the foremost patient data514is read in step S605as information regarding a zeroth patient, the medical care start time505and the medical care end time506of the patient data514are referred to in step S606. Because the medical care start time505of the patient data514is “13:10” and the medical care end time506is “13:30”, three images with the image identification number401storing Nos. 2 to 4 are extracted.

In a case where information regarding a patient that indicates the patient data515, which is the data following the patient data514, is read in step5605as information regarding a first patient, the medical care start time505and the medical care end time506of the patient data515are referred to in step5606. Because the medical care start time505of the patient data515is “13:50” and the medical care end time506is “14:15”, three images with the image identification number401storing Nos. 5, 7, and 8 are extracted. The image with the image identification number401storing No. 6 is not determined as a processing target because the image type402is “identification”.

In step S607, the CPU201determines whether the number of images extracted in step S606is a value greater than 0. In a case where the CPU201determines that the number of extracted images is greater than 0 (YES in step S607), the processing proceeds to step S608. In a case where the CPU201determines that the number of extracted images is 0 (NO in step S607), the CPU201determines that an affected area image associated with the p-th patient has not been found, and the processing proceeds to step S610.

In step S608, the CPU201substitutes 0 into a counter k for sequentially performing subsequent processing on the image extracted in step S606.

In step S609, the CPU201determines whether the counter k indicates a value less than the number of images extracted in step S606. In a case where the CPU201determines that the counter k is less than the number of images extracted in step S606(YES in step S609), the processing proceeds to step S611. In a case where the CPU201determines that the counter k is greater than or equal to the number of images extracted in step S606(NO in step S609), the CPU201determines that the matching of all the extracted affected area images of the p-th patient has been completed, and the processing proceeds to step S610.

In step S610, the CPU201updates the processing status511of the p-th patient data to “processed”. The processing then proceeds to step S614.

In step S611, the CPU201performs the matching between information included in the diagnosis and treatment department507of the p-th patient data and information included in the imaging apparatus operator department405of a k-th affected area image, and determines whether both departments match. In a case where the CPU201determines that the departments match (YES in step S611), the CPU201determines that the k-th affected area image might be associated with the p-th patient, and the processing proceeds to step S612. In a case where the CPU201determines that the departments do not match (NO in step S611), the CPU201determines that the k-th affected area image is not associated with the p-th patient, and the processing proceeds to step S615. In the above-described processing, the image management apparatus106performs the matching between imaging apparatus operator information of an affected area image and medical information of a patient. In the present exemplary embodiment, the image management apparatus106performs the matching between an imaging apparatus operator department of an affected area image and a diagnosis and treatment department visited by a patient. Based on the matching result, the image management apparatus106sets a processing target affected area image as a candidate to be stored in association with a processing target patient.

In step S612, the CPU201determines whether information included in the imaging apparatus ID510of the p-th patient data matches information included in the imaging apparatus ID406of the k-th affected area image. In a case where the CPU201determines that the imaging apparatus IDs match (YES in step S612), the CPU201determines that the k-th affected area image might be associated with the p-th patient, and the processing proceeds to step S613. In a case where the CPU201determines that the imaging apparatus IDs do not match (NO in step S612), the CPU201determines that the k-th affected area image is not associated with the p-th patient, and the processing proceeds to step S616. In the above-described processing, the image management apparatus106performs the matching between imaging apparatus information of an affected area image and imaging apparatus information of an identification image of a patient. In the present exemplary embodiment, the image management apparatus106performs the matching between an imaging apparatus ID acquired from an affected area image and an imaging apparatus ID acquired from an identification image. This enables the image management apparatus106to use medical information of a patient and imaging apparatus information acquired from an identification image of the patient for the matching. In a case where the matching has failed, the image management apparatus106excludes a processing target affected area image from a candidate to be associated with a processing target patient. In steps S611and S612described above, the image management apparatus106performs the matching between information regarding a predetermined item of image capturing information of an affected area image and information regarding a predetermined item of information regarding an identification image. The condition of association is that pieces of matching target information match.

In step S613, the CPU201determines that the k-th affected area image is highly likely to be an affected area image of the p-th patient, and estimates that the k-th affected area image is a target image to be associated with the p-th patient. Specifically, the CPU201stores the patient ID502of the p-th patient in the estimated patient ID412of the k-th affected area image. In the above-described manner, the image management apparatus106performs the matching between time information, diagnosis and treatment department information, and imaging apparatus information acquired from an identification image and time information, diagnosis and treatment department information, and imaging apparatus information acquired from an affected area image. Based on matching results of all of these pieces of information, the image management apparatus106performs control such that the affected area image is associated with a patient ID of the identification image.

In step S614, the CPU201increments the counter p. The processing then returns to step S604. The CPU201then repeats the series of processes for all the patients extracted in step S601.

In step S615, because the pieces of information regarding items used for the matching do not match, the CPU201determines that the k-th affected area image is not an affected area image of the p-th patient, and stores the mismatched item in the mismatch condition413of the k-th affected area image. In the present exemplary embodiment, as information indicating that pieces of diagnosis and treatment department information do not match, the CPU201stores “diagnosis and treatment department” in the mismatch condition413.

In step S616, the CPU201stores, as information indicating that pieces of imaging apparatus information do not match, “camera” in the mismatch condition413. In the above-described processing, the image management apparatus106performs the matching between time information, diagnosis and treatment department information, and imaging apparatus information acquired from an identification image and time information, diagnosis and treatment department information, and imaging apparatus information acquired from an affected area image, and in a case where identification of an estimated patient has failed due to a failure in the matching of partial information pieces of these information pieces, the image management apparatus106stores the item causing the failure in the matching.

The proceeds to step S617following the processing in steps S613, S615, or S616.

In step S617, the CPU201increments the counter k. The processing then returns to step S609, and the CPU201repeats the matching for all the extracted affected area images of the p-th patient.

In step S618, the CPU201stores information indicating that the image capturing time403falls within medical care time periods of none of patients extracted in step S601in the mismatch condition413of an affected area image with the estimated patient ID412including “unknown” and the mismatch condition413storing no data. In the present exemplary embodiment, the CPU201stores “time” in the mismatch condition413. The processing of the flowchart then ends.

A specific example of association of a patient and an affected area image will now be described with reference toFIGS.4to7.FIG.7illustrates an image list obtained after the association processing inFIG.6has executed based on the image list inFIG.4and the patient list inFIG.5. The image list inFIG.7stores an execution result of the association processing inFIG.6. InFIG.7, a corresponding patient ID is stored in the estimated patient ID412as an affected area image where association has been performed by the association processing inFIG.6. A mismatch item is stored as an affected area image where association has failed in the mismatch condition413with “unknown” kept included in estimated patient ID412.

A case where a patient of the patient data514and an affected area image with the image identification number401including No.2are to be processed will be described as a specific example of a case where a matching result satisfies a predetermined condition will now be described. In this case, in step S611, the CPU201performs the matching between the diagnosis and treatment department507of the patient data514and the imaging apparatus operator department405of the affected area image with the image identification number401including No. 2. Because both departments correspond to “intraoral surgery”, and the departments match, the CPU201determines that matching result satisfies the predetermined condition. The affected area image with the image identification number401including No. 2 is set as a candidate to be associated with the patient of the patient data514, and the processing proceeds to step S612. In step S612, the CPU201performs the matching between the imaging apparatus ID510of the patient data514and the imaging apparatus ID406of the affected area image with the image identification number401including No. 2. Because both imaging apparatus IDs indicate “005” and match, the CPU201determines that the matching result satisfies the predetermined condition. The affected area image with the image identification number401including No. 2 is kept set as a candidate to be associated with the patient of the patient data514, and the processing proceeds to step S613. In step S613, the CPU201determines that the affected area image with the image identification number401including No. 2 is associated with the patient of the patient data514, and stores “101”, which is the patient ID502of the patient data514, in the estimated patient ID412of the affected area image with the image identification number401including No. 2.

A case where the patient of the patient data514and an affected area image with the image identification number401including No. 4 are to be processed will not be described as a specific example of a case where the matching has failed due to mismatch of imaging apparatus information. In this case, in step S611, the CPU201performs the matching between the diagnosis and treatment department507of the patient data514and the imaging apparatus operator department405of the affected area image with the image identification number401including No. 4. Because both departments correspond to “intraoral surgery”, and the departments match, the CPU201determines that the matching result satisfies the predetermined condition. The affected area image with the image identification number401including No. 4 is set as a candidate to be associated with the patient indicated by the patient data514, and the processing proceeds to step S612. In step S612, the CPU201performs the matching between the imaging apparatus ID510of the patient data514and the imaging apparatus ID406of the affected area image with the image identification number401including No. 4. Because the imaging apparatus ID510is “005” and the imaging apparatus ID406is “001”, which do not match, the CPU201determines that the matching has failed. In step S616, the CPU201stores “camera” in the mismatch condition413of the affected area image with the image identification number401including No. 4. The estimated patient ID412of the affected area image with the image identification number401including No. 4 is kept to be “unknown”.

A case where a patient of the patient data515and an affected area image with the image identification number401including No. 8 are to be processed will now be described as a specific example of a case where cross-check has failed due to mismatch of diagnosis and treatment department information. In this case, in step S611, the CPU201performs the matching between the diagnosis and treatment department507of the patient data515and the imaging apparatus operator department405of the affected area image with the image identification number401including No. 8. Because the diagnosis and treatment department507is “dentistry” and the imaging apparatus operator department405is “intraoral surgery”, which do not match, the CPU201determines that the matching has failed. Next, in step S615, the CPU201stores “diagnosis and treatment department” in the mismatch condition413of the affected area image with the image identification number401including No. 8. The estimated patient ID412of the affected area image with the image identification number401including No. 8 is kept to be “unknown”.

<UI Screen Representing Correspondence Relationship between Patient and Affected Area Image>

FIG.8illustrates an example of a UI screen representing a correspondence relationship between a patient and an affected area image. In a case where the execution of the association processing inFIG.6has completed, the CPU201of the image management apparatus106performs control to display the UI screen illustrated inFIG.8on the display204of the image management apparatus106. On the UI screen illustrated inFIG.8, images registered in the image registration processing inFIG.3are displayed as a list together with an execution result of the association processing inFIG.6. Based on the image list inFIG.7that stores the execution result of the association processing inFIG.6, the CPU201of the image management apparatus106performs control to display the UI screen illustrated inFIG.8. Using the UI screen illustrated inFIG.8enables the operator to check and correct an association result.

A transmission button800is a display item for issuance of an instruction to transmit an image to the image information DB110. In a case where the operator has selected the transmission button800, the CPU201transmits an affected area image to the image management system105via the network102together with, for example, information regarding the affected area image containing corresponding patient ID, image capturing date and time.

A folder selection button801is a display item for issuance of a folder selection instruction.

In a case where the operator selects the folder selection button801, the CPU201displays a folder selection dialog on the display204. In a case where a folder has been selected on the folder selection dialog, the CPU201reads an image in the selected folder as a processing target image.

In the present exemplary embodiment, the image registration processing inFIG.3has already been executed on the image read as a processing target image.

A text box802displays a path to the folder selected on the above-described folder selection dialog.

A matching button803is a display item for issuance of an execution instruction of the association processing inFIG.6. In a case where the operator selects the matching button803, the CPU201executes the association processing inFIG.6on an affected area image from among images read as processing target images.

An end button804is a display item for issuance of an instruction to close the UI screen illustrated inFIG.8.

A scroll bar805is a display item for issuance of a change instruction of an image display range in a case where a processing target images are not displayed within a screen region. When the operator operates the scroll bar805, the CPU201switches the image display range.

A display region of each image includes an image identification number display region806and a thumbnail image display region807. In the image identification No display region806, an image identification number of the corresponding image is displayed.

The image identification number corresponds to the image identification number401inFIG.7. In place of an image identification number, a file name that can uniquely identify an image can be displayed. In the thumbnail image display region807, a reduced image of a corresponding image is displayed.

A display region of an affected area image where a patient has been estimated in the association processing inFIG.6includes an estimated patient name display region808. An image where a patient has been estimated is an image with a patient ID stored in the estimated patient ID412. In the estimated patient name display region808, a patient name corresponding to the estimated patient ID412of the image is displayed.

A display region of an affected area image where a patient has not been estimated in the association processing inFIG.6includes a mismatch condition display region809and a candidate display button810. An image where a patient has not been estimated is an image with the estimated patient ID412including “unknown”. In mismatch condition display regions809,811, and812, information indicating that identification of a patient to be associated has failed, and items of the mismatch condition413of respective images are displayed. In the mismatch condition display region809, “camera mismatch” is displayed as information indicating that pieces of imaging apparatus information do not match. In the mismatch condition display region811, “diagnosis and treatment department mismatch” is displayed as information indicating that pieces of diagnosis and treatment department information do not match. In the mismatch condition display region812, “time mismatch” is displayed as information indicating that pieces of time information do not match. In the above-described processing, the image management apparatus106displays information notifying that a patient to be associated with the affected area image has failed to be identified and a cause for the failure in identification of the patient in association with an affected area image failed in the matching in the association processing inFIG.6. The notification method is not limited to a method of displaying the information and the cause on the display204, as long as the operator can be notified of the information and the cause.

The candidate display button810is a display item for issuance of a display instruction of a patient candidate. In response to the operator selecting the candidate display button810, the CPU201displays as candidates, from among patients with their medical care time periods matching the image capturing time403of the affected area image, patients with the diagnosis and treatment department507matching the imaging apparatus operator department405of the affected area image. Then, in a case where the operator designates a patient from among the candidates, the CPU201associates a corresponding image and information regarding the designated patient. More specifically, the CPU201stores a patient ID of the designated patient in the estimated patient ID412of the image. The CPU201can display, as candidates, all patients with medical care time periods matching the image capturing time403of the affected area image, and can display, as candidates, all patients with the diagnosis and treatment department507matching the imaging apparatus operator department405of the affected area image. The notification method is not limited to a method of displaying candidates on the display204, as long as the operator can be notified of the candidates.

In the above-described processing, an image management apparatus of the present exemplary embodiment performs the matching between image capturing information of a target image and information regarding an identification image of a target person, and based on the matching result, associates the target image and identification information of the target person. With this configuration, even in a case where the target image is recorded without being associated with the identification information of the target person, or even in a case where the order of image capturing of the target image and an image including the identification information of the target person is not uniquely defined, it is possible to prevent the target image and the identification information of the target person from being wrongly associated. Especially in a medical system, even in a case where an affected area image is recorded without being associated with identification information of a patient, or even in a case where an image capturing order of an affected area image and an identification image of a patient is not uniquely defined, it is possible to prevent the affected area image and identification information of the patient from being wrongly associated. In a case where association has failed, by notifying the operator that a corresponding patient is unknown and notifying the operator of an item with information causing the failure in the matching, the operator is notified of a cause of the association failure. In a case where association has failed, candidate display is performed, at an image capturing time of the affected area image, for an affected area image by displaying a patient who has visited the same diagnosis and treatment department as the diagnosis and treatment department indicated by image capturing information of the affected area image. With this configuration, the operator can easily perform association.

According to the image management apparatus of the present exemplary embodiment, unlike an inspection apparatus in which image capturing is performed after the issuance of an order, even in a case where image capturing is performed without an order, the matching can be performed based on actual medical care start time and end time and a diagnosis and treatment department. For example, in a case where a diagnosis and treatment department to be visited is first determined in at a general internal medicine department, the matching can be performed based on information that is based on a past record. In a case where a patient can be identified afterward, such as the case of an emergency department, it becomes possible to associate identification information of a patient afterward.

As a first modified example of the present exemplary embodiment, in place of the method of displaying a list of association execution results of affected area images as inFIG.8, the operator can manually associate a patient with an affected area image, and the operator can be notified of an affected area image where association might be wrong. In this case, the CPU201performs determination whether a patient designated by the operator and a patient estimated in the association processing inFIG.6match, and displays information regarding an affected area image failed in the matching on the display204. The CPU201can display a UI for prompting the operator to confirm the patient designated by the operator or change the patient to another patient.

As a second modified example of the present exemplary embodiment, the matching can be performed using an imaging apparatus management department in place of an imaging apparatus ID. With this configuration, even in a case where an imaging apparatus that has captured an identification image and an imaging apparatus that has captured an affected area image are different from each other, the matching can be performed. In this case, the CPU201registers an imaging apparatus management department acquired in step S304ofFIG.3in the image list inFIG.4in place of an imaging apparatus ID. The CPU201then performs the matching between imaging apparatus management department information acquired from an affected area image and imaging apparatus management department information acquired from an identification image, and in a case where pieces of matching target information match, sets the affected area image as a candidate to be associated with a patient of the identification image. In a case where a plurality of imaging apparatuses of the same model do not exist in a facility, the matching can be performed using an imaging apparatus model name.

As a third modified example of the present exemplary embodiment, in place of the configuration of acquiring various types of information from the electronic medical chart system104in steps S303, S304, and S307ofFIG.3, a configuration of acquiring various types of information from the HDD205of the image management apparatus106can be employed. In this case, information in each database is stored in the HDD205of the image management apparatus106.

As a fourth modified example of the present exemplary embodiment, inFIG.6, the processing in step S612of the matching between imaging apparatus information of an affected area image and imaging apparatus information of an identification image of a patient can be skipped. In this case, acquisition of imaging apparatus information (imaging apparatus ID) in the processing in step S302or S304ofFIG.3can be skipped. An item related to imaging apparatus information can be omitted from the image list inFIG.4and the patient list inFIG.5. In this case, incorrect association can be reduced by the matching between an image capturing time and a medical care time period and the matching between a department of an imaging apparatus operator who has captured an affected area image and a diagnosis and treatment department visited by a patient.

As a fifth modified example of the present exemplary embodiment, in a case where an imaging apparatus operator of an identification image and an imaging apparatus operator of an affected area image always match, the matching can be performed using an imaging apparatus operator ID. That is, the image management apparatus106performs the matching between imaging apparatus operator information of an affected area image and imaging apparatus operator information of an identification image of a patient. Specifically, the CPU201performs the matching between information regarding the imaging apparatus operator ID508of patient data and information regarding the imaging apparatus operator ID404of an affected area image. In a case where pieces of matching target information match, the CPU201sets the affected area image as a candidate to be associated with a patient of the identification image.

As a sixth modified example of the present exemplary embodiment, in a case where a department of an imaging apparatus operator of an identification image and a department of an imaging apparatus operator of an affected area image always match, the matching can be performed using a department of an imaging apparatus operator. In the fifth modified example, an imaging apparatus operator ID contained in imaging apparatus operator information is used for the matching. In the sixth modified example, a department of an imaging apparatus operator is used for the matching in place of the imaging apparatus operator ID.

As a seventh modified example of the present exemplary embodiment, inFIG.6, the processing in step S611of the matching between imaging apparatus operator information of an affected area image and medical information of a patient can be skipped. In this case, acquisition of imaging apparatus operator information (imaging apparatus operator ID, an imaging apparatus operator department) in the processing in step S302or S303ofFIG.3can be skipped. An item related to imaging apparatus operator information is not required in the image list inFIG.4and the patient list inFIG.5. In this case, incorrect association can be reduced by the matching between an image capturing time and a medical care time period, and the matching between imaging apparatus information of an affected area image and imaging apparatus information of an identification image.

While, in the present exemplary embodiment, a description has been provided using a medical system as an example, an applicable system is not limited to the medical system, and any other type of system, such as a nursing care system or a childcare system, that would enable practice of the present exemplary embodiment is applicable.

An exemplary embodiment of a nursing care system will now be described. In this embodiment the above-described medical information is replaced with nursing care service information. The nursing care service information contains, for example, nursing care target person information, a nursing care service start time, a nursing care service end time, an organization and a department that provide a nursing care service, and service contents. The nursing care target person information contains a nursing care target person ID, and a name, a gender, a birth date, a medical history, and allergy information of a nursing care target person, and a nursing care name. Departments that provide services include a department of rehabilitation and a pressure ulcer care department of a nursing care facility. The service contents include contents of rehabilitation and pressure ulcer care.

An exemplary embodiment of a childcare system will now be described. In this embodiment the above-described medical information is replaced with childcare service information. The childcare service information contains, for example, childcare target person information, a childcare service start time, a childcare service end time, a facility where childcare has been performed, and childcare contents.

The childcare target person information contains a childcare target person ID, and a name, a gender, a birth date, a medical history, and allergy information of a childcare target person, and a guardian name. The facility where childcare is performed includes age-based classes, such as an infant class, and a one-year-old-children class. The childcare contents include, for example, allergy care and dietary education that uses baby food.

By using nursing care service information or childcare service information in the above-described respective exemplary embodiments, an effect similar to the exemplary embodiment of the medical system can be obtained by the matching of service times and departments or facilities provided services.

In a second exemplary embodiment, the description will be given of a method of setting an association rule to be used in association processing of a patient and an affected area image. In the following description, redundant descriptions of components or elements similar to those of the first exemplary embodiment will be omitted.

<Setting Screen of Association Rule>

FIG.9illustrates an example of a setting screen of an association rule. The association rule includes a set of information acquired from an affected area image and information acquired from an identification image, a condition of determination to be performed by comparing the pieces of acquired information, and association-related processing to be executed in a case where the condition of determination is satisfied. In response to a display request from the operator, the CPU201of the image management apparatus106performs control to display the setting screen illustrated inFIG.9on the display204of the image management apparatus106.

An end button901is a display item for issuance of an instruction to close the setting screen illustrated inFIG.9.

In a region930for setting of information to be acquired from an affected area image to be registered (hereinafter, referred to as registered image information), a type list box902and a condition box903are provided.

The type list box902is used for selection of an item of information to be acquired from an image. In the present exemplary embodiment, any item can be selected from among an image capturing time, an imaging apparatus operator ID, an imaging apparatus operator department, an imaging apparatus operator job, an image capturing apparatus ID, an image capturing apparatus management department, and an image capturing apparatus model name. Examples of an imaging apparatus operator job include a doctor, a nurse, a clerk, or a pharmacist.

The condition box903is used for selection of a value of an item selected in the type list box902. In a case where a specific value is not to be designated, ANY is selected. Based on selection operations performed by the operator in the type list box902and the condition box903, the CPU201sets registered image information. In a case where an imaging apparatus operator department and an image capturing apparatus management department are selected in the type list box902, department names of the facility are listed as candidates. In a case where an imaging apparatus model name is selected in the type list box902, model names of imaging apparatuses owned by the facility are listed as candidates. The CPU201can read information to be listed from information pre-registered in the HDD205or can acquire the information from the facility information DB109via the network102.

In a region931for setting of medical information to be acquired from an identification image, a type 1 list box904, an information 1 list box905, a type 2 list box906, and an information 2 list box907are provided.

The type 1 list box904and the type 2 list box906are used for selection of an item of medical information to be acquired from an identification image. In the present exemplary embodiment, any item can be selected from among patient information, a medical care start time, a medical care end time, an inspection start time, an inspection end time, a visited diagnosis and treatment department, a position in a body of a past injury or disease, and a diagnosis result.

The information 1 list box905is used for selection of a value of an item selected in the type 1 list box904. In a case where a specific value is not to be designated, ANY is selected. Based on selection operations performed by the operator in the type 1 list box904and the information 1 list box905, the CPU201sets first information in medical information.

The information 2 list box 907 is used for selection of a value of an item selected in the type 2 list box906. In a case where a specific value is not to be designated, ANY is selected. Based on selection operations performed by the operator in the type 2 list box906and the information 2 list box907, the CPU201sets second information in medical information.

Candidates from among items selected in the type 1 list box904and the type 2 list box906are listed similarly to the condition box903are candidates of values that are preliminary restricted. The CPU201can read information to be listed from information pre-registered in the HDD205or can acquire the information from the medical information DB108via the network102.

Radio buttons908to912are provided in a region932for selection of a condition of determination to be performed by comparing registered image information acquired from an affected area image and a first information and a second information acquired from an identification image.

Based on selection of any of the radio buttons908to912, a condition of determination to be performed by comparing the registered image information and the first information and the second information is set. As a default value, the radio button908is set to ON, and the radio buttons909to912are set to OFF. In response to the operator selecting any of the radio buttons909to912, the CPU201determines that a determination condition change instruction has been issued, switches the pressed radio button to ON, and switches the other radio buttons to OFF.

In a case where the radio button908is set to ON, the CPU201sets, as a determination condition, a condition that the registered image information matches the first information.

In a case where the radio button909is set to ON, the CPU201sets, as a determination condition, a condition that the registered image information is greater than the first information.

In a case where the radio button910is set to ON, the CPU201sets, as a determination condition, a condition that the registered image information is less than the first information.

In a case where the radio button911is set to ON, the CPU201sets, as a determination condition, a condition that the registered image information falls between the first information and the second information.

In a case where the radio button912is set to ON, the CPU201sets processing selected in a region933to be executed without comparing the registered image information with the first information and the second information.

In the region933for selection of processing to be performed in a case where a determination condition set in the region932is satisfied as a result of comparison between the registered image information acquired from the affected area image and the first information and the second information acquired from the identification image, radio buttons913to915are provided. Processing selectable in the region933includes processing related to association between a patient of an identification image from which the first information and the second information are to be acquired and an affected area image from which the registered image information is to be acquired.

Based on selection of any of the radio buttons913to915, processing related to the association is set. As a default value, the radio button913is set to ON, and the radio buttons914and915are set to OFF. In response to the operator selecting any of the radio buttons914and915, the CPU201determines that a setting change instruction of the association-related processing has been issued, switches the pressed radio button to ON, and switches the other radio buttons to OFF.

In a case where the radio button913is set to ON, the CPU201sets the processing to be performed to processing of, in a case where a determination condition selected in the region932is satisfied, associating a patient and an affected area image with each other.

In a case where the radio button914is set to ON, the CPU201sets the processing to be performed to processing of, in a case where a determination condition selected in the region932is satisfied, not associating a patient and an affected area image with each other.

In a case where the radio button915is set to ON, the CPU201sets the processing to be performed to processing of, in a case where a determination condition selected in the region932is satisfied, not performing comparison.

In a rule NO box916, a rule number corresponding to an association rule is displayed.

A rule addition button917is a display item for issuance of a rule addition instruction. In response to the operator selecting the rule addition button917, the CPU201checks that an association rule designated by the operator includes no theoretical failure, and stores the designated association rule into the RAM203. Examples of the theoretical failure include a case where a condition of a magnitude relation is selected for an item with a value in non-number form, and a case where, even though “between information 1 and information 2” is selected as a determination condition, registered image information that can fall between the information 1 and the information 2 is not set. Then, in response to the operator selecting the end button901, the CPU201allocates a rule number to an association rule stored in the RAM203, and stores the association rule into the HDD205. A rule set in the above-described manner is called an existing rule. A plurality of existing rules are stored in the HDD205.

An edit button918is a display item for issuance of a change instruction of an existing rule. In response to the operator selecting the edit button918, the CPU201reads an existing rule from the HDD205and stores it in the RAM203. Existing rules are displayed in a priority order list920. In a default setting, a rule displayed at the top of the priority order list920is selected.

A deletion button919is a display item for issuance of a deletion instruction of an existing rule. In a case where the operator selects the deletion button919, the CPU201deletes the selected existing rule from the HDD205.

A plurality of set existing rules are displayed in the priority order list920. In the priority order list920, a rule number display region921and a rule information display region922are provided for each rule. In the rule number display region921, a rule number allocated to a rule when the rule is added is displayed. In the rule information display region922, information regarding an association rule is briefly displayed.

A rule displayed at a higher position in the priority order list920has a higher priority order and a rule displayed at a lower position in the priority order list920has a lower priority order. The CPU201sequentially executes association-related processing that is based on an existing rule in order of the priority order. All the rules in the priority order list920are executed such that association processing of an affected area image not targeted in the rule with the first priority order is performed based on the rule with the second priority order. In the present exemplary embodiment, determination results of the respective rules are used as an OR condition, but the determination results of the respective rules can be used as an AND condition. The OR condition, the AND condition, or a NOT condition can be made selectable for each rule.

An upward change button924is a display item for issuance of an instruction to change a priority order of a rule selected in the priority order list920to a higher order. In response to the operator selecting the upward change button924, the CPU201changes the orders between the selected rule and a rule placed immediately above the selected rule.

A downward change button925is a display item for issuance of an instruction to change a priority order of a rule selected in the priority order list920to a lower order. In response to the operator selecting the downward change button925, the CPU201changes the orders between the selected rule and a rule placed immediately below the selected rule.

In the above-described processing, the CPU201sets a priority order of an existing rule based on an operation performed by the operator.

In the present exemplary embodiment, in place of the processing in steps S611to S612ofFIG.6, the CPU201executes determination processing using a determination condition of an existing rule. In step S613, the CPU201, based on an existing rule, selectively executes processing of associating a patient and an affected area image, or processing of not associating a patient and an affected area image. While a preset fixed condition is used as an association condition in the first exemplary embodiment, in the present exemplary embodiment, various conditions based on the relation between information acquired from an affected area image and information acquired from an identification image can be used. With this configuration, association processing can be performed using a method suitable for the situation of each facility.

For example, in a case where an imaging apparatus operator department is an emergency department, because the emergency department is not prepared as a value selectable as a diagnosis and treatment department in medical information, processing of not associating a patient and an affected area image can be set. In this case, an imaging apparatus operator department is designated in the type list box902and an emergency department is designated in the condition box903. Then, a rule set by setting the radio button912to ON and setting the radio button914to ON is registered as a topmost rule in the priority order list920. Alternatively, a rule of not using an imaging apparatus operator department in the matching in a case where the imaging apparatus operator department is the emergency department can be set.

For example, a condition that an image capturing time falls between a medical care start time and a medical care end time is set as an association condition in the first exemplary embodiment. In the present exemplary embodiment, a condition that an image capturing time falls between an inspection start time and an inspection end time can also be set as an association condition. In this case, an image capturing time is designated in the type list box902, ANY is designated in the condition box903, an inspection start time is designated in the type 1 list box904, an inspection end time is designated in the type 2 list box906, and ANY is designated in the information 1 list box905and the information 2 list box907. Then, the radio button911is set to ON and the radio button913is set to ON. With this configuration, in a case where image capturing is performed during an inspection time, in place of the matching between an image capturing time and a medical care time period, it becomes possible to perform the matching between an image capturing time and an inspection time period.

For example, a condition that an imaging apparatus operator department and a diagnosis and treatment department match is set as an association condition in the first exemplary embodiment. In the present exemplary embodiment, in consideration of a case where an imaging apparatus operator captures images of patients of a plurality of diagnosis and treatment departments, the setting can be made such that an imaging apparatus operator department can be associated with the plurality of diagnosis and treatment departments.

A description will now be provided of a setting method for performing association with whichever department of a dentistry or an intraoral surgery using a specific example case of an imaging apparatus operator working for both the dentistry and the intraoral surgery. In this case, first to third rules are set as described below.

First, a setting method of the first rule as follows. A department of an imaging apparatus operator is designated in the type list box902and intraoral surgery is designated in the condition box903. A diagnosis and treatment department is designated in the type 1 list box904and dentistry is designated in the information 1 list box905. The radio button908is set to ON and the radio button913is set to ON.

Next, a setting method of the second rule will be described. An imaging apparatus operator department is designated in the type list box902and dentistry is designated in the condition box903. A diagnosis and treatment department is designated in the type 1 list box904and intraoral surgery is designated in the information 1 list box905. The radio button908is set to ON and the radio button913is set to ON.

Lastly, a setting method of the third rule will be described below. An imaging apparatus operator department is designated in the type list box902, ANY is designated in the condition box903, a diagnosis and treatment department is designated in the type 1 list box904, and ANY is designated in the information 1 list box905. The radio button908is set to ON and the radio button913is set to ON.

Using the rules set as described above, even in a case where an imaging apparatus operator captures images of patients of a plurality of diagnosis and treatment departments, enables performance of appropriate association.

In the present exemplary embodiment, it is possible to set a priority order to an existing rule. With this configuration, the CPU201, based on the set priority order, can sequentially execute association-related processing that is based on an existing rule. In other words, the CPU201performs control to perform association-related processing preferentially using a result of determination processing based on a rule having a higher priority order over a result of determination processing based on a rule having a lower priority order. For example, a priority order of the matching that uses an image capturing time and an imaging apparatus operator department is set to a higher priority order, and a priority order of the matching that uses imaging apparatus information is set to a lower priority order. An imaging apparatus operator can be made usable in the matching regardless of whether a job of an imaging apparatus operator is doctor or nurse, or an imaging apparatus operator department can be made usable in the matching only in a case where a job of an imaging apparatus operator is doctor.

According to the above-described image management apparatus of the present exemplary embodiment, a condition to be used in the matching can be changed based on the circumstances of a hospital and a diagnosis and treatment department. By setting an association rule using a method similar to the above-described method in workplaces other than a medical workplace, such as a nursing care workplace or a childcare workplace, it becomes possible to perform appropriate association in accordance with the circumstances of each workplace.

Other Exemplary Embodiments

While exemplary embodiments have been described, it is to be understood that these embodiments are not seen to be limiting. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions.

This application claims the benefit of Japanese Patent Application No. 2022-073358, filed Apr. 27, 2022, which is hereby incorporated by reference herein in its entirety.