Determining a presence of an object

Methods, computing devices, and computer-readable medium are described herein related to producing detection signals configured to induce an excited state of an object. A computing device may receive reflection signals, where the reflection signals correspond to at least one detection signals reflected from the object. Based on the received reflection signals, a presence of the object in the excited state may be determined. Further, an output device may provide an indication of the presence of the object in the excited state.

BACKGROUND

Non-invasive procedures may involve making observations underneath the skin of a mammal without breaking the skin of the mammal. Various non-invasive procedures today face challenges with the detection of an object underneath the skin. For example, an object may include a foreign object such as a catheter or a stent. In other instances, an object may include a gall stone, a salivary duct stone, various tissues, a blood vessel, plaque, and/or a bone fragment, among other examples.

In one particular area of study, minerals and salts in kidneys may cluster and form crystals in urine, accumulating into kidney stones. Small kidney stones may be able to pass out of the body with urine, possibly unnoticed. However, larger kidney stones may block, stretch, and/or irritate a tube called the ureter that connects the kidney to the bladder. Passing larger kidney stones through the ureter may cause excruciating pain. Notable symptoms have been described as radiating pain starting in the lower back and then continuing on to the groin and genitals as the kidney stone passes with urine out of the body.

The prevalence of kidney stone disease is increasing in humans. Considerable studies have shown a moderate growth in the percentage of the population affected by the disease. Further, additional studies have indicated that approximately half of newly diagnosed patients will have a recurrent stone within five to ten years of detecting a first kidney stone. In particular, recurrent stones may develop due to residual crystals continuously growing over time.

SUMMARY

Various embodiments set forth herein provide ways of detecting objects in tissue based on signals. These embodiments are provided herein for purposes of illustration and are not meant to be limiting in any way.

In one aspect, a computer-implemented method may include producing one or more detection signals configured to induce an excited state of an object. Further, the method may include receiving one or more reflection signals, where the one or more reflection signals correspond to at least one of the one or more detection signals reflected from the object. Yet further, based on the received one or more reflection signals, the method may include determining a presence of the object in the excited state. In addition, the method may include causing an output device to provide an indication of the presence of the object in the excited state.

In another aspect, a computing device may include a processor and a non-transitory computer-readable medium configured to store program instructions that, when executed by the processor, cause the computing device to carry out functions. The functions may include producing one or more detection signals configured to induce an excited state of an object. Further, the functions may include receiving one or more reflection signals, where the one or more reflection signals correspond to at least one of the one or more detection signals reflected from the object. Yet further, based on the received one or more reflection signals, the functions may include determining a presence of the object in the excited state. In addition, the functions may include causing an output device to provide an indication of the presence of the object in the excited state.

A non-transitory computer-readable medium including program instructions that, when executed by a processor, cause the processor to perform functions including producing one or more detection signals configured to induce an excited state of an object. Further, the functions may include receiving one or more reflection signals, where the one or more reflection signals correspond to at least one of the one or more detection signals reflected from the object. Yet further, based on the received one or more reflection signals, the functions may include determining a presence of the object in the excited state. In addition, the functions may include causing an output device to provide an indication of the presence of the object in the excited state.

In yet a further aspect, a system may include: (a) a means for producing one or more detection signals configured to induce an excited state of an object (b) a means for receiving one or more reflection signals, where the one or more reflection signals correspond to at least one of the one or more detection signals reflected from the object, (c) based on the received one or more reflection signals, a means for determining a presence of the object in the excited state, (d) a means for causing an output device to provide an indication of the presence of the object in the excited state.

DETAILED DESCRIPTION

In an example embodiment, a computing device may produce detection signals that may be used to detect an object. In some instances, the computing device may produce detection signals from a probe coupled to the computing device. The detection signals may penetrate through a medium and reflect off an object in the medium. Some of the reflected signals may return to the computing device and/or the probe, or possibly another device coupled to the computing device. The reflected signals may be used to detect the presence of the object. For example, a computing device positioned outside of a mammal may produce detection signals that penetrate through the mammal's skin, reflect off a kidney stone in the mammal's kidney, and return to the computing device. As such, the reflection signals returned to the probe may provide information indicating the presence of the kidney stone in the mammal's kidney.

In an additional embodiment, the computing device may produce detection signals that excite the object. For example, the computing device may produce detection signals, such as excitation pulses, that interact with and/or excite the object. In some instances, excitation pulses may be amplified signals may interact with the object. Further, amplified signals may interact with reflection items on the object, such as bubbles inside and/or on the surface of the object. In particular, the amplified signals may cause the bubbles to get bigger and change shape. The excited object may be referred to as a twinkling artifact.

Further, in an additional embodiment, the computing device may receive reflection signals from an excited object. Such reflection signals may be used to detect the excited object. In particular, such reflection signals may have different characteristics than signals reflected from objects that are not excited. By observing such differences, excited objects may be detected. As such, in some examples, detection signals may be configured to induce the excited state of an object and the reflection signals may detect the excited object.

In some instances, characteristics of the detection signals such as amplitude may be configured to induce an excited state of the object. Further, it should be noted that various terms referring to respective objects such as a kidney stone, a twinkling artifact, an excited object, and an object induced to an excited state may be used interchangeably, as described herein. Further, exciting the object, interacting with a bubble on the object, exciting a bubble on the object, oscillating the bubble on the object, and/or other similar expressions may also be used interchangeably.

In addition, it should also be noted that the examples of bubbles on an object in the above description are provided for illustrative purposes and should not be construed as limiting. Inducing an excited state of an object may depend on other reflection items as well. For example, cavitation of the object may include impurities where bubbles appear and grow. Further, reflection items may include calcification, crevices, cracks, and/or concretions associated with the object.

In some instances, an object may be naturally created in the medium. For example, an object may be a kidney stone originated from the accumulation of substances such as minerals and salts in a mammal's kidneys. Yet further, objects may be formed from the clustering of crystals in the mammal's urine. However, it should be noted that objects may also be foreign and/or artificial objects found in the mammal's body. Other possibilities may also exist.

In some embodiments, an indication of the excited object may be provided on an output device (e.g., a graphical display) and the output device may provide further information regarding the excited object. In particular, harmonic imaging of the object may provide information regarding the location of a kidney stone within the kidney, any movements of the kidney stone within the kidney, characteristics of the kidney stone (e.g., size, shape, and/or composition), among other possibilities.

2. Example Architecture

FIG. 1shows a simplified block diagram of an example communication network in which at least one embodiment can be implemented. It should be understood that this and other arrangements described herein are set forth only as examples. Those skilled in the art will appreciate that other arrangements and elements (e.g., medical devices, laboratory machines, interfaces, functions, orders, and groupings of functions, etc.) can be used instead and that some elements may be omitted altogether. Further, many of the elements described herein are functional entities that may be implemented as discrete or distributed components or in conjunction with other components, and in any suitable combination and location. Various functions described herein as being performed by one or more entities may be carried out by hardware, firmware, and/or software. And various functions described herein may be carried out by a processor executing instructions stored in memory.

As shown inFIG. 1, example network100includes various network-access devices102A-102D, network104such as the Internet, and server106. As illustrated, network-access devices102A,102B,102C, and102D may be a computing device (e.g., a portable medical device), a tablet computer, a laptop computer and/or a desktop personal computer (PC), and a mobile phone, respectively. It should be noted that network-access device102A may be described as a computing device for carrying out process, methods, and functions further described herein. As such, network-access devices102B-102D, network104, and server106may be described for purposes of illustrating that various processes, steps, and/or functions may be distributed and performed by other devices, networks, and/or servers. For example, network-access devices102B-102D may be stand-alone devices or may be coupled to network-access device102A for carrying out various processes. Thus, it should be noted that additional entities and devices not depicted inFIG. 1could be present as well.

Network104may be a public network or a private network (e.g., a local network in a laboratory, a clinic, and/or a doctor's office). As an example, there could be more network-access devices and more servers in communication with network104. Other network elements may be in communication with network104as well. Also, there could be one or more devices and/or networks making up at least part of one or more of the communication links depicted inFIG. 1. As an example, there could be one or more routers, switches, or other devices or networks on the communication links between network-access devices102A-102D, network104, and/or server106. Each of network-access devices102A-102D may be any network-access device arranged to carry out the network-access device functions described herein.

Systems and devices in which example embodiments can be implemented will now be described in greater detail. In general, an example system may be implemented in and/or can take the form of a computing device. In an example embodiment, network-access device102A may be described as a computing device including an engine capable of producing detection signals and receiving reflection signals. Further, the computing device may be portable, hand-held, and/or transferrable by a single person.

FIG. 2shows a simplified block diagram of a computing device arranged to implement aspects of at least one embodiment. For example, network-access device102A may include processor202, data storage204, and network interface210, all linked together via system bus, network, or other connection mechanism218.

Processor202may include one or more general purpose microprocessors, central processing units (CPUs), and/or dedicated signal processors. In addition, processor202may include one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), and may be integrated in whole or in part with network interface210. Data storage204may include memory and/or other storage components, such as optical, magnetic, organic or other memory disc storage, which can be volatile and/or non-volatile, internal and/or external, and integrated in whole or in part with processor202. Data storage204may be arranged to contain (i) program instructions206and (ii) program logic208, executable by processor202. Data storage204may also store data that may be manipulated by processor202to carry out the various methods, processes, or functions described herein.

In some embodiments, these methods, processes, or functions can be defined by hardware, firmware, and/or any combination of hardware, firmware and software. Therefore, data storage204may include a tangible, non-transitory computer-readable medium, having stored thereon program instructions that, upon execution by one or more processors, cause computing device102A to carry out any of the methods, processes, or functions disclosed in this specification or the accompanying drawings.

Although these components are described herein as separate data storage elements, the elements could just as well be physically integrated together or distributed in various other ways. For example, program instructions206may be maintained in data storage204separate from program logic208, for easy updating and reference by program logic208.

Network interface210may enable network-access device102A to send communication and receive communication. Network interface210typically functions to communicatively couple network-access device102A to networks, such as network104. As such, network interface210may include a wired (e.g., Ethernet) and/or wireless (e.g., Wi-Fi, BLUETOOTH®, or a wide-area wireless connection) packet-data interface, for communicating with other devices, entities, and/or networks.

Input/output function212may facilitate user interaction with an example computing device100. Input/output function212may comprise multiple types of input devices, such as a keyboard, a mouse, a touch screen, a probe, a transducer, a sensor, and/or any other device that is capable of receiving input. Similarly, input/output function212may comprise multiple types of output devices, such as a graphical display, a printer, one or more light emitting diodes (LEDs), speaker configured to generate audible sounds, or any other device that is capable of providing output discernible to a user. Additionally or alternatively, example computing device102E may support remote access from another device, via network interface210or via another interface (not shown), such an RS-132 or Universal Serial Bus (USB) port.

Probe214may produce one or more radio frequency pulses, radio frequency pulses produced within a first time period (e.g., 333 microseconds), a sequence of substantially similar radio frequency pulses produced within a time period different than the first time period, a sound wave, a sound pressure wave, and/or an oscillating sound pressure wave. In the examples above, the first time period may be 200-400 microseconds, among other possible ranges. In particular, probe214may produce such pulses in response to executing program instructions206stored in data storage204and communicating to probe214via other connection mechanism218. Probe214may also produce signals within one or more time periods. Yet further, in some instances, any one of the signals may be produced within a given time period and other detection signals may be produced within a different time period. In some instances, probe214may produce, ultrasound propagation or arrays, Doppler signals, among other possibilities. In particular, probe214may produce one or more pulses that contain a series of 10-30 identical pulses or bursts, 1-10 cycles of such bursts, and where the pulses are transmitted with a central frequency of 2 to 8 MHz. In some instances, the pulses may have a 1-5 kHz pulse-repetition frequency (PRF). It should be noted that a probe, such as probe214, may be similar to a transducer such that a probe and a transducer may be used interchangeably herein.

In some instances, probe214may produce detection signals such as excitation pulses. Further, in some instances, detection signals may have 2 to 5 cycles. Yet further, in some instances, positive pressures (P+) and negative pressures (P−) of pressure detections signals may be 1 to 5 MPa and −5 to −1 MPa, respectively. Probe214may also receive signals reflected from external objects back to probe214. Computing device100may also receive signals through a sensor or another device, possibly connected through input/output function212. As noted, detection signals may be configured to induce an excited state of an object. As such, it should be understood that the above-characteristics of detection signals may be configured to induce the excited state of an object.

It should be noted that probe214may be removable so as to operate while being physically separate from computing device100. For example, probe214may communicate remotely with computing device110through input/output function212. In some instances, there may be several probes similar to probe214that may move remotely, controlled by computing device110.

Reflected signals received by probe214may be converted to digital signals through analog-to-digital converter (ADC)216. ADC216may be a 12-24 bit analog-to-digital converter configured to sample signals at a 10-30 MHz frequency. For example, signals transmitted by probe214may be received by probe214and converted to digital signals through ADC216. In some instances, digitized signals from ADC216may also be processed in real-time using mathematical software platforms. In some instances, unmodified signal outputs from ADC216may identify characteristics of objects for detecting the objects. It should be noted that computing device102A may also include one or more digital-to-analog converters (not illustrated) that may be configured to transmit signals to probe214. As such, probe214may produce detection signals as described herein.

In some instances, computing device102A may modify the reflected signals received by probe214. In some instances, signals may be modified by band-pass filters, analog filters, amplifiers, and clipping diodes (not shown inFIG. 2). In particular, signals may be modified by an anti-aliasing band-pass filter with a 0.7 to 17 MHz bandwidth. Further, signals may be amplified using time-gain compensation. Yet further, signals may be limited and/or clipped by a diode. In some instances, the modification described herein may be implemented through signal processing software. It should be noted that the above-referenced modifications to the reflected signals may occur before being sampled by ADC216.

Server106may be any network server or other computing system arranged to carry out the server functions described herein including, but not limited to, those functions described with respect toFIGS. 5-10. In particular, reflection signal received by probe214may be communicated to server106for analysis, possibly to detect an excited object. As such, network-access device102A and server106may share processes, methods, and/or functions described herein for determining the presence of the excited object.FIG. 3shows a simplified block diagram of a server arranged to implement aspects of at least one embodiment. As such, as shown inFIG. 3, server106may include processor302, data storage304including program data306and program logic308, and network interface310, all linked together via system bus, network, and/or other connection mechanism312. Processor302, data storage304, program data306, program logic308, and network interface310may be configured and/or arranged similar to processor202, data storage204, program instructions206, program logic208, and network interface210, respectively, as described above with respect to network-access device102A.

Data storage304may contain information used by server106in operation. For example, date storage304may include instructions executable by the processor for carrying out the server functions described herein including, but not limited to, those functions described below with respect toFIGS. 5-10. As another example, data storage304may contain various design logic and/or design data used for determining a test result, such as the logic and data described below with respect toFIGS. 5-10. Generally, data storage304may contain information used by server106to provide information accessible by various network-access devices, such as network-access device102A, over network104.

Returning toFIG. 1, network104may also include one or more wide area networks, one or more local area networks, one or more public networks such as the Internet, one or more private networks, wired networks, wireless networks, and/or networks of any other variety. Devices in communication with network104(including, but not limited to, network-access devices102A-102D and server106) may exchange data using a packet-switched protocol such as IP, and may be identified by an address such as an IP address.

As noted above, in some embodiments, the disclosed methods may be implemented by computer program instructions encoded on a physical and/or non-transitory computer-readable storage media in a machine-readable format, or on other non-transitory media or articles of manufacture.FIG. 4is a schematic illustrating a conceptual partial view of an example computer program product that includes a computer program for executing a computer process on a network-access device, arranged according to at least some embodiments presented herein.

In one embodiment, the example computer program product400is provided using a signal bearing medium402. The signal bearing medium402may include one or more programming instructions404that, when executed by one or more processors may provide functionality or portions of the functionality described herein. In some examples, the signal bearing medium402may encompass a computer-readable medium406, such as, but not limited to, a hard disk drive, a Compact Disc (CD), a Digital Video Disk (DVD), a digital tape, memory, etc. In some implementations, the signal bearing medium402may encompass a computer recordable medium408, such as, but not limited to, memory, read/write (R/W) CDs, R/W DVDs, etc.

In some implementations, the signal bearing medium402may encompass a communications medium410, such as, but not limited to, a digital and/or an analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.). Thus, for example, the signal bearing medium402may be conveyed by a wireless form of the communications medium410. It should be understood, however, that computer-readable medium406, computer recordable medium408, and communications medium410as contemplated herein are distinct mediums and that, in any event, computer-readable medium408is a physical, non-transitory, computer-readable medium.

The one or more programming instructions404may be, for example, computer executable and/or logic implemented instructions. In some examples, a computing device such as the network-access device102A ofFIG. 2may be configured to provide various operations, functions, or actions in response to the programming instructions404conveyed to the network-access device102A by one or more of the computer readable medium406, the computer recordable medium408, and/or the communications medium410.

The physical and/or non-transitory computer readable medium could also be distributed among multiple data storage elements, which could be remotely located from each other. The computing device that executes some or all of the stored instructions could be a network-access device such as the network-access device102A illustrated inFIG. 2. Alternatively, the computing device that executes some or all of the stored instructions could be another computing device, such as a server, for instance server106illustrated inFIG. 3.

3. Example Method for Detecting an Object

FIG. 5shows a simplified flow chart depicting aspects of an example method for detecting an object as described herein. For purposes of example and explanation, aspects of such example methods are described with reference to an example computing device. It should be understood, however, that the example methods described herein may apply just as well to any suitable computing device including, but not limited to, a computing device integrated with a computer, a mobile computing device, a medical device, and/or other computing system, among other examples.

FIGS. 6A and 6Bdepict aspects of example computing devices in accordance with one or more example embodiments. More particularly,FIGS. 6A and 6Bdepict aspects of a computing device illustrated inFIG. 5for carrying out the method for detecting an object. For example, computing device602depicts aspects of an example computing device detecting an object. Various respective features, characteristics, and/or functionality of the computing devices depicted inFIGS. 6A and 6Bare discussed further below with respect to the example methods described herein.

InFIG. 5, method500is described by way of example as being carried out by a computing device, possibly a computing device coupled to a probe. For example, method500may be carried by network-access device102and/or computing device602. Further, example methods, such as method500, can be carried out by devices other than a computing device and/or can be carried out by sub-systems in a computing device. For example, method500may also be carried out by network-access devices102B-102D, network104, and/or server106. In some instances, an example method can be carried out by a computing device which is programmed to display an excited object on a graphical display.

As shown inFIG. 5, method500begins at block502with a computing device, such a computing device coupled to a probe, which may carry out functions for producing one or more detection signals configured to induce an excited state of an object. At block504, the computing device receives one or more reflection signals, where the reflection signals correspond to at least one of the detection signals reflected from the object. At block506, based on the received one or more reflection signals, the computing device determines a presence of the object in the excited state. At block508, the computing device causes an output device to provide an indication of the presence of the object in the excited state.

The steps of method500are explained in the following subsections. Although method500may be carried out by network-access device102A, this is not required. Various steps illustrated by these flow charts may be carried out by other types of devices or systems, such as server106. Further, it may be possible to distribute aspects of individual steps between network-access devices102A-102B, network104, and server106. For instance, network-access device102A may produce detection signals and receive reflection signals and server106may determine the presence of the object in the excited state.

As noted,FIGS. 6A and 6Bdepict aspects of example computing devices in accordance with one or more example embodiments.FIG. 6Adepicts aspects of a computing device in accordance with one or more example embodiments. InFIG. 6A, scenario600provides a computing device602that may be positioned adjacent to medium604. In some instances, computing device602may be similar as computing device102A inFIGS. 1 and 2. Yet, further, computing device602may be configured to communicate with other computing devices, such as another computing device described in further detail inFIG. 6B.

In some embodiments, medium604may be part of a human body or an organ encompassing object610. Further, object610may be a kidney stone that may be 1 to 15 mm in diameter and medium604may be a kidney. In other embodiments, object610may be a foreign object (e.g., a bullet from a handgun, a catheter, or a stent), a gall stone, a salivary duct stone, tissue, a blood vessel, plaque, and/or a bone fragment, among other possibilities. Yet further, in some instances, object610may be a mass or a buildup of minerals, such as a concretion, for example. Other examples of mediums and objects may exist.

In some embodiments, object610may include reflection items that may be used to help detect the presence of object610in medium604. In some instances, reflection items may include a bubble, a calcification, a crevice, a crack, and/or a concretion associated with the object. For example, a reflection item may be bubble612on object610. In some instances, bubble612may be in a crack and/or crevice of object610. As a general matter, it should be noted that bubbles may also be formed in free fluid, concretions, and/or tissues in a mammal. For example, bubble610may be formed on any of the example objects described above for object610. Further, in some instances, a bubble, such as bubble612, may include trapped air, a gas pocket, and/or air emboli. In addition, bubble612may be stationary or in motion while on the surface of object610.

It should be noted that bubble612is illustrated inFIG. 6Aas a growing bubble. As shown, the dotted lines inFIG. 6Aillustrate that bubble612has grows from a smaller bubble to the current size illustrated by the solid line surrounding the dotted lines. In particular, the dotted lines may resemble the outer surface of bubble612as it grows. As such, it should be understood that detection signals may interact with bubble612, causing it to grow. In addition, it should be also noted that detection signals may interact with bubble612to drive it into instability. For example, the detection signals may vary the size and/or shape of bubble612and change the properties of bubble612to detect the reflective properties of bubble612, as described further with respect to block506ofFIG. 5.

FIG. 6Bdepicts aspects of another computing device in accordance with one or more example embodiments. InFIG. 6B, scenario650provides a computing device660that may be positioned adjacent to medium664. In some instances, computing device660may be similar to computing device102A and/or computing device602. InFIG. 6B, medium664may be a human body or the body of some other living mammal. As a general matter, object670may be similar to object610and bubble672may be similar to bubble612. For example, bubble672may also be a growing bubble. Further, object670may be a kidney stone that is 5-12 mm in diameter with reflection items to detect the presence of object670in medium664.

a. Produce One or More Detection Signals

As noted for block502ofFIG. 5, a computing device may carry out functions for producing one or more detection signals configured to induce an excited state of an object. As illustrated inFIG. 6A, computing device602may produce detection signals. For example, computing device602may produce pulses in a direction606toward medium604and object610. In some instances, computing device602may produce pulses that penetrate the surface of medium604and reflect off of object610. Further, computing device602may increase or decrease the amplitude of detection signals to interact with bubble612on object610and induce an excited state of object610. As noted, the detection signals may drive bubble612into oscillation and/or instability.

In some embodiments, computing device602may produce detection signals that are focused on a region of object. In some instances, detection signals may be focused on a reflection item. For example, computing device602may produce detection signals focused or directed to bubble612. For instance, referring back toFIG. 2, detection signals may be focused or directed toward a given bubble by positioning probe214in a given manner. In some instances, probe214may be angled in such a way to direct detection signals towards the given bubble. As such, the detection signals may be focused on the left side of bubble612. In some instances, detection signals may be directed towards the left side of bubble612and then the signals may be directed towards to the right side of bubble612. Other possibilities may also exist.

In some embodiments, computing devices602and660may produce different types of detection signals.FIG. 6Cdepicts aspects of signals produced from the computing devices602and660inFIGS. 6A and 6B, respectively, in accordance with one or more example embodiments. InFIG. 6C, signal680may be a Doppler signal with a multiple pulses. Further, signal682may be a B-mode with plane waves. Yet further, signal684may be a pulse sequence with peak positive pressures (P+) and peak negative pressures (P−). In addition, signal686may be a shock wave pulse.

As a general matter, detection signals may include one or more bursts such that each burst includes a number of pulses. For example, as illustrated by signal680, a single burst may include 14 pulses. It should be noted that signal680may also have one or more of cycles such that each cycle includes a burst and a time period before or after the burst. In particular, signal680may have a 160 microsecond cycle with a burst of 5 microseconds. As such, 155 microseconds may be a time period after the burst. It should be noted that detection signals may include a range of 7 to 21 bursts. Yet further, detection signals may include 2 to 7 cycles of bursts and time periods without bursts.

In some embodiments, various modes may be employed by computing devices602and606to produce the detection signals. For example, Doppler mode may be used produce signal680. As noted above, signal680may include 14 identical pulses such that the pulses are produced consecutively by a probe and/or a transducer (such as probe214). It should be noted that Doppler mode may be implemented to produce the 14 pulses in signal680. In some instances, such pulses may be produced with a 3 kHz pulse-repetition frequency (PRF). Further, the PRF may be adjusted and/or modified according to the dimensions of object610and/or bubble612. It should be noted that signal680may have varying amplitudes to provide an initial excitation pulse with greater amplitudes followed by lower amplitude pulses.

In some instances, B-mode may be used to produce signal682. As noted above, signal682may include a series of plane waves. In some instances, signal682may include a one micro-second plane wave in a 160 micro-second cycle. It should be understood that B-mode may be implemented to produce the plane waves in signal682. Further, in some instances, a Push mode may produce signal684. As illustrated, signal684may include a 3 millisecond cycle with a burst of pulses over a 100 microseconds.

Yet further, in some instances, a Shock mode may produce686. Signal686may have characteristics similar, in some respects, to signals produced by lithotripters for breaking up object610. However, it should be understood that computing devices602and606are not the same as conventional lithotripters. As described above, computing device602and606may produce a variety of different signals, including those produced by lithotripters.

In some embodiments, detection signals may include pressure waveforms, possibly excitation signals and/or pulses. As noted, signal684may have positive pressures (P+) and negative pressures (P−) of pressure waveforms. In some instances, signal684may also be re-produced in three cycles and a central frequency of 5 MHz. In some instances, positive pressures and negative pressures of signal684may be 2 MPa and −1 MPa, respectively. As such, signal684may excite object670such that bubble672in and/or on object670grows with each signal interacting with bubble672. It should be noted that the positive and negative pressures of signals684may be adjusted. In particular, the pressures may be raised to drive bubble672into oscillation. Further, in some instances, the pressures may be lowered to prevent saturation of the oscillation effect.

In some embodiments, a variation of the different signals may be produced. For example, signal684may be produced to interact with bubble672, possibly driving bubble672into oscillation. In addition, signal680may be produced and reflection signals may be received to indicate the presence of object670. In particular, the reflection signals may include phase variations or phase variability indicative of the presence of object670. Thus, as further described below for block506ofFIG. 5, the presence of object670may be determined. In some instances, signal686may be produced to break object670into fragments. As such, signal684may be produced to oscillate bubbles on object670and signal680may be produced to receive reflection signals indicative of the presence of object670. Other possibilities may also exist.

In some embodiments, detection signals may be produced and directed to a human body. For example, referring back toFIG. 6B, computing device660may produce detection signals in a direction666toward medium664and object670. In some instances, computing device660may produce pulses that penetrate the surface of medium664to reflect off of object670, possibly returning in a direction668toward computing device660.

As noted, detection signals may be configured to induce an excited state of an object. For example, computing device660may produce detection signals configured to induce an excited state of object670. In some instances, computing device660may produce amplified signals that interact stochastically with bubble672on object670, possibly driving bubble672into oscillation. It should be noted that detection signals with certain characteristics described above may excite object670. For example, the negative pressure phases of the detection signals produced by computing device660may induce an excited state of object670. In particular, negative pressure phases may create tension that oscillates bubble672.

In some instances, bubble672may be in the bulk of object670and/or on the surface of object670. As such, detection signals may excite bubble672in the bulk of object670or cracks inside object670. In some instances, detection signals may interact with internal calcifications in object670to produce an excited state of object670. In other instances, detection signals may excite bubble672on the surface of object670, particularly if there are microscopic crevices on the surface of object670. In particular, detection signals may induce an excited state of object670when there are gas pockets on the surface of object670. It should be noted that bubbles such as bubble672may be micron or submicron size so as to be invisible and detectable only by inducing the excited state of object670.

b. Receive One or More Reflection Signals

As noted for block504ofFIG. 5, the computing device receives one or more reflection signals, where the reflection signals correspond to at least one of the detection signals reflected from the object. As noted forFIG. 6A, computing device602may produce detection signals in a direction606toward medium604and object610. The reflected signals may return in a direction608toward computing device602so as to be received by computing device602. In some instances, computing device602may be placed 5-15 centimeters away from medium604when sending and receiving pulses and in other instances, computing device602may be farther away from, or closer to, medium604. In other instances, computing device602may make contact with the outer surface of medium604when sending and receiving pulses.

In a similar manner,FIG. 6Billustrates reflected signals returning in a direction668toward computing device660. Further, reflection signals may indicate the presence of bubble672, possibly indicating the presence of object670. It should be noted that one or more pressure waveforms produced by computing device660may be measured by a hydrophone associated with computing device660, possibly integrated within computing device660. In other instances, the waveforms produced by computing device660may be measured by a broadband hydrophone having a sensitivity of 48 nV/PA at 5 MHz.

c. Determine a Presence of an Object

As noted for block506ofFIG. 5, based on the received one or more reflection signals, the computing device determines a presence of the object in the excited state. As noted forFIGS. 6A and 6B, computing devices602and660may receive reflection signals after exciting bubbles612and672, respectively.

As a general matter, computing devices may determine the presence of exited object by analyzing the reflection signals. As noted above, reflection signals from an excited object may have different characteristics than signals reflected from objects that are not excited. Such differences may help, facilitate, and/or aid in detecting the excited object. In particular, various measurements of the reflection signals may indicate the presence of an excited object. For example, a variance in the reflection signals may be measured to determine the excited object. In further examples, bubbles may be driven into oscillation and the oscillation may be determined by measuring phase variability, amplitude, and/or harmonics associated with the reflection signals. Thus, by determining the oscillation, the presence of the object and/or the bubble in the excited state may be determined. Additional examples of determining an object in the excited state are described below.

In some embodiments, an object in the excited state may be determined by analyzing reflection signals.FIG. 7Adepicts aspects of reflection signals associated with a computing device in accordance with one or more example embodiments. Further,FIG. 7Amay illustrate reflection signals including 12 signals, signals701-712. For example, signals701-712may be reflection signals reflected from an excited object and received by a computing device. The signals may be measured by amplitude on the y-axis and time on the x-axis, with sample rate of 50 nanoseconds per sampling point. As illustrated, signals701-712may be represented on the same graph inFIG. 7Asuch that each signal overlaps one another. It should be noted that signals701-712may have similar characteristics such that overlapping the signals over one another creates the appearance of a single signal inFIG. 7A.

In some embodiments, the power of signals may be used to determine the presence of the excited object. As one example, Doppler power calculated from Doppler signals may be used to identify an object.FIG. 7Bdepicts aspects of signals indicative of an excited object in accordance with one or more example embodiments. In particular,FIG. 7Billustrates the power of the signals illustrated inFIG. 7A. Further,FIG. 7Billustrates Doppler power calculated on a decibel scale (dB) on the y-axis and time on the x-axis, with a sampling rate of 50 nanoseconds per sampling point.

As illustrated inFIG. 7B, a spike in the data occurs approximately 2-3 microseconds after receiving signals reflected off the excited object. In some instances, such spikes indicate that portions of pulses inFIG. 7Afluctuate from pulse to pulse. Such spikes in power, or fluctuations from pulse to pulse, may be used to determine the presence of an excited object. It should be noted that the Doppler power may be calculated relative to the background noise level.

In some embodiments, computing devices602and660may determine that an excited object is not present. For example, computing devices may make such determinations based on receiving artificial signals simulating those of reflection signals. For example,FIG. 7Cdepicts aspects of artificial signals that simulate the reflection signals inFIG. 7Ain accordance with one or more example embodiments. Further,FIG. 7Cmay illustrate artificial signals including 12 signals, signals721-732. For example, signals721-732may be produced by a waveform generator and received by a computing device. The signals may be measured by amplitude on the y-axis and time on the x-axis, with sample points at 50 nanoseconds per sampling point. As illustrated, signals721-732may be represented on the same graph inFIG. 7Csuch that each signal overlaps one another. It should be noted that signals721-732may have similar characteristics such that overlapping the signals over one another creates the appearance of a single signal inFIG. 7C. It should be noted that signals721-732may be produced using a mathematical modeling software and a function generator.

FIG. 7Ddepicts aspects of different signals than those inFIG. 7Bin accordance with one or more example embodiments. In particular,FIG. 7Dillustrates the power of the simulated signals illustrated inFIG. 7C. Similar toFIG. 7B,FIG. 7Dillustrates Doppler power calculated on a decibel scale (dB) on the y-axis and time on the x-axis. Further, the Doppler power may also be calculated relative to the background noise level. As illustrated, there is no spike in the data after receiving the simulated signals inFIG. 7C. Therefore, no excited objects are detected from the simulated pulses ofFIG. 7C. Instead, excited objects may only be detected from reflection signals reflected from the excited object and received by the computing device.

In some embodiments, an excited object may be detected without signal processing. Recall thatFIG. 7Billustrates detecting the excited object without signal processing. In particular,FIG. 7Billustrates the excited object based on signals output from an analog-to-digital converter (ADC) of the computing device, possibly ADC216inFIG. 2. Moreover, the excited object may be based on raw RF data from ADC216and not from signal processing of the RF data. SinceFIG. 7Billustrates an excited object andFIG. 7Ddoes not, the excited object may be detected from reflection signals (e.g., raw RF data) and not from artificial signals mimicking reflection signals. Thus, in such instances, the excited object may be identified solely by the RF data signals received by the computing device, without any signal processing of the reflection signals.

In some embodiments, various modes for producing detection signals may be used to determine an excited object. For example, referring back toFIG. 6A-6C, computing devices may determine the presence of an object using the various modes for producing the detection signals. As noted, Doppler mode and B-mode may be employed to produce detection signals. Based on such modes, reflection signals may be received and processed accordingly by the analog-to-digital converter, such as ADC216. Further, such signals may determine a presence of object610in the excited state. In some instances, digital signals output from the ADC216may further be filtered, amplified, and/or clipped through further signal processing and the presence of excited object610may be determined.

In some embodiments, spikes in amplitude of reflection signals may be used to determine an excited object. For example,FIG. 8Adepicts aspects of Beamformed Doppler pulses in accordance with one or more example embodiments. Further,FIG. 8Bdepicts aspects of a variance (e.g., phase variability of one or more reflection signals) and Doppler power in accordance with one or more example embodiments. As illustrated, residual amplitudes may be measured on the y-axis and imaging depth may be measured on the x-axis. As shown inFIG. 8A, residual amplitudes may vary from pulse to pulse. For instance, some pulses in area802show spikes in residual amplitude which occur at the same depth as the spike in the corresponding Doppler power, indicating the presence of an excited object. As illustrated, area802ofFIG. 8Acorresponds to the spike in the Doppler power inFIG. 8Bfor detecting an excited object. It should also be noted that the variance may determine the presence of the excited object.

In some embodiments, the Doppler power may be calculated based on the residual amplitude. As such, the Doppler power may be calculated to determine the presence of an excited object. For example, the residual amplitude Anmmay be calculated for each Doppler pulse within a series of Doppler pulses. Further, Doppler power Wmmay be calculated by the following equation:

Wm=1N⁢∑n=1N⁢An⁢⁢m2
As such, calculating the Doppler power using the equation above may determine the presence of an excited object found in a given medium.

In some embodiments, the appearance of a spike in residual amplitude may be considered an “abnormal event,” indicating the presence of an excited object. To determine an abnormal event, a maximum residual amplitude or a threshold amplitude may be determined for reflection signals. For example, the maximum residual amplitude for a series of pulses may be 3 dB over the averaged maximum residual amplitude for the series of pulses.FIG. 9depicts aspects of an abnormal event in accordance with one or more example embodiments. As illustrated inFIG. 9, the amplitudes of twelve pulses are measured on the y-axis and the imaging depth is measured on the x-axis. The distribution of the amplitude may show that the abnormal event appears uniformly over all the pulses in the series of pulses, indicating the presence of an excited object.

In some embodiments, a threshold may be applied to determine the presence of an excited object. For example, as illustrated inFIG. 9, threshold902may be applied to the amplitudes inFIG. 9. In particular, an amplitude that exceeds threshold902may determine the presence of an excited object. It should be noted that thresholds, such as threshold902, may be applied toFIGS. 7B, 8A, and 8Bin a similar manner to determine an excited object. In addition, it should be understood that thresholds may not be linear as shown with threshold902. In particular, thresholds may take the form of a function and may also change dynamically with respect to different signals and amplitudes.

In some embodiments, signal processing may be used to display an image of the excited object. For example, B-mode images combined with Doppler-mode images may be generated to display an excited object. Further, such images may be generated using signal processing algorithms that utilize Doppler thresholds. For instance, color information of reflected signals may be based on a comparison between the Doppler power of reflected signals and a Doppler power threshold or a maximum Doppler power. In some instances, the maximum Doppler power may be decreased to a minimum level (e.g., a level just above the level background noise.) Further, color-write priority may be set to the highest level such that color information, rather than the B-mode information, may always be plotted on a graphical display. Further examples of displaying an excited object is described for block508ofFIG. 5below.

In some embodiments, signal processing may involve a numerical computation environment to determine the presence of an excited object. For analyzing reflection signals of an excited object, the signal processing may be based on mathematical codes and/or computational algorithms. In particular, characteristics of reflection signals may be calculated and these characteristics may indicate a presence of the excited object. For example, the Doppler residual and Doppler power may be characteristics that may be calculated by a numerical computation environment to determine an excited object.

In some embodiments, pulses of the reflection signals may be analyzed to determine the presence of an excited object. For example, consider a signal Un(t), n=1, 2, . . . , N, where N pulses represent reflections signals in the form of a series of pulses received by a computing device. For purposes of illustration, consider N=12 such that there are twelve pulses in each series of pulses. However, it should be noted that a general Doppler series may include fourteen pulses. In some instances, a Doppler shift may be measured by the following equation:
Un(t−nT), for differentnpulses, where

T=1/pulse-repetition frequency (PRF), and where T is the period for the series of pulses.

As such, a Doppler shift may be indicative of the presence of an excited object. Yet further, the Doppler shift may be related to phase variability also giving rise the presence of an excited object.

In some instances, reflected signals may be received uniformly and no Doppler shift may be determined. However, any differences from pulse to pulse may be determined in the above-referenced equation, possibly determining the presence of an excited object. For instance, Un((t−nT) for different n pulses, may indicate pulses reflecting off an object and arriving to the computing device with a time shift. Further, a velocity of an object may be calculated from the time shift, possibly indicating the presence of an excited object. Yet further, in some instances, Un(t) may not indicate the time shift, but may instead indicate a fluctuation based on the reflections signals. In such instances, a velocity of the object may also be calculated such that the presence of the excited object may be determined.

In some embodiments, additional signal processing may be implemented to determine the presence of an excited object. For example, after analog-to-digital conversion, the signal, Un(t), may be transformed to digital signals characterized by the following equation:
Unm=Un(tm−mAτ), where

Δt is the signal sampling step (e.g., 50 ns for a 20 MHz sampling frequency), and wherem=1, 2, . . . M, and where

M is the total number of samples recorded in one period of a Doppler series. In some instances, M=1024 but it should be noted that M may be other values as well. In some instances, beamformed signals may be calculated and processed for each channel. Such signals may be formed by a “delay-and-sum” beamforming method. For example, consider Unm, the digitized signal for either non-beamformed or beamformed channel data. In some instances, signal processing of the channel data may calculate the quadrature components of the signals Unm. Further, calculating the quadrature components of the signals Unmmay involve using the Hilbert transform. The Hilbert transform may be made using real-time mathematical software platforms such that Q=Hilbert (U). As a result, for each of the n pulses, a complex (“analytic”) signal may be characterized by the following equation:
Vnm=Unm+iQnm, where

the quadrature signal, Qnm, is the Hilbert transform of Unmand i is an imaginary unit. As such, the analytic signal may be used to determine the presence of an excited object through additional signal processing.

In some embodiments, “wall filtering” may be used to determine a presence of an excited object. In some instances, wall filter may be used to reduce signal fluctuations of the reflection signals, possibly due to slow-moving reflection signals. For example, a first order regression filter may be applied to the analytic signal Vnm. In particular, for each fast time-moment m, the corresponding signals from different pulses within the reflection signals may be considered as a function of the n pulses. For example, for the n pulses and the function may characterized as a linear expression:
Vnm=am+n bm.

The expression may provide for Vnmusing a least squares estimation (where amand bmmay be some coefficients that do not depend on the pulse number n.) Further, the residual signal may be the wall-filtered signal, {tilde over (V)}nm=nm−Vnm. Yet further, the absolute value of that signal may be the residual amplitude, Anm=|{tilde over (V)}nm|. Thus, Anmmay be used to detect fluctuations in the reflection signals to determine the presence of an excited object. Further, the average power may provide the Doppler power at the time tm=mΔt using the following equation.

Wm=1N⁢∑n=1N⁢V~⁢n⁢⁢m^2
As noted, calculating the Doppler power may determine the presences of an excited object found in a given medium.

In some embodiments, it may be possible to distribute aspects or individual steps for determining the presence of the object in the excited state. For example, referring back toFIG. 6B, computing device660may send detection signals and receive reflection signals from excited object670. Further, computing device660may communicate with server652through communication link658such that server652may determine the excited object (e.g., determining the Doppler power of the reflection signals). In addition, server652may communicate with computer656through communication link654such that server652and computer656may share processes for determining the excited object. In some instances, computing device660may communicate with computer656through communication link662such that computer656may determine the excited object (e.g., provide a graphical display of the Doppler power). Other possibilities may also exist.

It should be noted that communication links658,654, and662may be physically wired communication links such as serial bus connections and/or parallel bus connections. Alternatively, these communication links may be wireless communications, e.g., Bluetooth® radio technology, Cellular technology (such as GSM, CDMA, or WiMAX), or Zigbee® technology, among other possibilities.

d. Cause an Output Device to Provide an Indication

As noted for block508ofFIG. 5, the computing device causes an output device to provide an indication of the presence of the object in the excited state. In some embodiments, a computing device may communicate with one or more other computing devices to display an indication of the object in the excited state.

In some embodiments, computing device660may communicate with computer656to display characteristics of object670. Further, computer656may display data indicative of the material surrounding object670, the size of object670, the position of object670(e.g., coordinates in a three-dimensional layout), among other possibilities. As such, computer656may provide information indicating of the presence of object670in medium664. As described in further detail herein, computer656may provide graphical representations indicating the presence of object670in medium664. In some instances, computer656may display a harmonic image of object670in the excited state. Further, computer656may include a speaker to generate an audible sound corresponding to one or more detection signals, possibly indicative of detecting object670.

It should be noted that although computer656is illustrated as a laptop computer, computer656may also be a smaller computing device such as network-access device102D, for example. Yet further, it should be noted that various embodiments described herein may be combined or interchangeable. For example, a smaller version of the graphical display on computer656may be incorporated with computing device660to display the characteristics of object670and to detect the presence of object670. Other possibilities may also exist.

4. Additional Features and Functions

In some embodiments, a pressure within a medium encompassing the object may be determined. In some instances, determining the pressure of the medium may aid, facilitate, and/or help to detect the object within the medium. For example, reducing the static pressure in the medium may help to reduce any suppression of twinkling or excitation such that the object may be detected. It should be noted that the examples below are provided for purposes of illustration and should not be interpreted as limiting. For example, one or more of the processes, methods, and/or functions below may be performed or similarly performed on a mammal, such as a human.

FIG. 10illustrates monitoring pressure of a medium, according to an example embodiment. InFIG. 10, transducer1002(e.g., a probe) may be placed in water tank1004and above high pressure chamber1004. It should be noted that transducer1002may be the same transducer as probe214inFIG. 2. High pressure chamber1006may be cylindrical in shape with an inner diameter of 11.2 cm and a height of 7 cm. High pressure chamber1006may have walls, a bottom, and upper lid made of aluminum. The walls may be 4.5 cm thick, and the bottom and the lid may be 3.6 cm thick, to sustain high pressures.

In some embodiments, absorber1008may be a 1 cm thick acoustic rubber placed on the bottom of high pressure chamber1006to dampen possible reverberations during stone imaging. Stone1010may be immersed in water1012and fixed on the tip of a brass needle 1.6 mm in diameter that is attached to a wall of high pressure chamber1006by stone holder1016. Acoustic window1014may be a polystyrene puck fixed in the middle of the lid to serve as an acoustic window for better ultrasound transmission.

In some embodiments, on top of the lid of high pressure chamber1004, a plastic cylinder of 8.8 cm diameter and 5.1 cm height may be attached to form an external water tank, where transducer1002may immersed. Transducer1002may be fixed on the positioning system with its axis oriented perpendicularly to the lid of high pressure chamber1004. The surface of the transducer1002may be close (less than 1 mm) but may not touch acoustic window1014during experimentation. As such, transducer displacement caused by acoustic window1014bending under high-pressure may be prevented. The transversal position of transducer1002may be adjusted by the positioning system to find the optimal location on the stone for detecting the excited characteristics.

In some embodiments, high static pressure may be generated inside high pressure chamber1004by a piston screw pump (not shown inFIG. 10). This pump may be capable of producing pressure up to 200 MPa. However, lower pressures (less than 9 MPa) may be used since higher pressures may exceed several times the peak negative pressure of the ultrasound pulses. A gauge of maximum scale of 13.8 MPa may be used for determining pressure in high pressure chamber1005.

In some embodiments, Doppler imaging may illustrate that pressure in high pressure chamber1006may suppress the twinkling or excitation of stone1010. Compared to ambient pressures, the high pressure applied may suppress the twinkling or excitation of stone1010almost completely. Further, by releasing the pressure, the twinkling or excitation of stone1010may reappear immediately.

In some embodiments, a pressure threshold may be determined for detecting an excited object. For example, the pressure of high pressure chamber1006may be monitored such that if the pressure exceeds the pressure threshold for detecting stone1010, an indication may be provided. In some instances, a pressure threshold may vary from 0.34 MPa to 1.38 MPa under conditions shown inFIG. 10. Further, in some instances the pressure threshold may be 0.34 MPa to 1.72 MPa. As such, the pressure threshold may vary according to different stones and/or different conditions.

In some embodiments, monitoring the pressure of a medium encompassing a stone may determine the positive and negative pressures for a transducer. For example, under a given pressure, positive pressures (P+) and negative pressures (P−) of pressure detections signals may be 2 MPa and −1 MPa, respectively, to induce an excited state of an object. As such, it should be noted that the pressure of a medium encompassing the stone may be monitored and used to produce detection signals to induce the excited state of stone1010.

The examples discussed hereafter are for purposes of illustrating how the subject matter of the present application may be implemented for different applications, such as for medical and/or diagnostic applications. In particular, the examples discussed hereafter provide illustrations regarding possibly ways to implement and utilize features described in this application. The following examples are not meant to be limiting or restrictive of the scope of the present application.

Real human kidney stones were either embedded in a degassed gel block, or in degassed water. The human kidney stones consisted of more than 90% calcium oxalate monohydrate and were 5-12 mm in diameter with submicron bubbles trapped in crevices on the stone surface. The kidney stones were placed in gel and in water. The gel used was polyacrylamide hydrogel, which mimicked tissue structure. The liquid mixture was first degassed for at least one hour in a desiccant chamber before commencing experimentations.

An ultrasound engine was used to determine the presence of the kidney stone. The ultrasound engine achieved the results below by utilizing a 128 element linear ultrasound array with a 5 MHz central frequency with a clinical probe. The reflection signals were received by a broadband calibrated hydrophone with a sensitivity of 48 nV/Pa at 5 MHz. The acoustic pulse was similar to the transducer voltage with a form of a 3-cycle tone burst with a central frequency of 5 MHz.

The kidney stones were positioned 4 cm from the ultrasound probe and were immersed within the tissue-mimicking gel. At the location 4 cm away from the transducer in water, the measured peak positive and negative pressures were 2 MPa and −1 MPa, respectively. These values aided choosing sufficiently high levels of the static pressure in an overpressure test. The imaging was performed in a “flash” transmitting mode when all the array elements were excited simultaneously to emit a quasi-plane wave in the direction orthogonal to the radiating surface (zero degrees incident angle). Such a mode simplified the analysis of the reflection signals without limiting the possibility of stone imaging. Both B-mode and Doppler mode were employed. In the Doppler mode, the array elements were excited by a series of 14 identical pulses emitted one-after-another with 3 kHz pulse-repetition frequency (PRF). The PRF was adjustable. Each pulse in the 14 pulse was a tone burst consisting of three cycles at the central frequency 5 MHz.

The reflection signals were received when the detection signals reflected from the kidney stone and returned to the probe. The corresponding reflection signals of the array elements went through an anti-aliasing band-pass filter of 0.7-17 MHz bandwidth, an amplifier with the time-gain compensating (TGC) feature, a clipping diode (to limit excessive signals), and were sampled at a 20 MHz frequency by a 12-bit analog-to-digital convertor (ADC). The digitized signals were processed in real-time using in-house code written in a mathematical software platform. The signals were also stored in a buffer and were able to be post-processed at a later time. The saved signals were radio-frequency (RF) data output from the ADC's for each channel. Access to this RF data provided a possibility to study the “raw” ultrasound signals associated with the excited kidney stone.

FIG. 7Ashows typical signals that were analyzed to reveal the features of the excited kidney stone.FIGS. 7A and 7B, describe data for imaging the natural kidney stones, which were placed in the gel. As noted,FIG. 7Aoverlays12successive reflection signals701-712of the Doppler ultrasound pulses reflected from the stone and recorded at the central element of the array. The imaging depth d corresponded to the time delay of the reflected signal t in accordance with the formula d=c*t/2, where c=1540 m/s. The signals701-712that were plotted on top of each other are barely distinguishable, because the corresponding changes are small.

To easier reveal the difference between reflection signals701-712, the Doppler power was calculated from those waveforms. The Doppler power is shown inFIG. 7B. The Doppler power was provided on a dB scale, relative to the background noise level. The essential spike occurred about 2-3 microseconds after the arrival of the front of the reflection signals701-712, which indicated that the corresponding part of the signal within the Doppler signal was fluctuating from pulse to pulse. Such a spike was observed for all studied stones and corresponded to exciting the kidney stone of the color Doppler image. This illustrated detecting the excited kidney stones.

FIG. 7Cshows signals obtained for a simulated acoustic source test. The simulated Doppler signals shown inFIG. 7Cprovide 12 signals that were plotted on top of each other. The signals depicted respectively inFIGS. 7C and 7Awere nearly identical, which indicated a high quality of the mimicking procedure. The artificial Doppler signals721-732were sent through the same signal path inside the machine as the signals701-712.

FIG. 7Drepresents the result for the Doppler power calculated from the signals721-732. No obvious spike was seen, as shown inFIG. 7D. This test was repeated for six kidney stones, and the result was repeatable. This observation provided the conclusion that the origin for determining the presence of an excited kidney stone is not related to a machine or signal processing. Therefore, detecting the excited kidney stone resulted from an acoustic effect.

The results indicated that the kidney stones were detected from bubbles on the kidney stones. The gas bubbles interacted stochastically with ultrasound. The bubbles were either present in the bulk of propagation medium, or they may were resting on the stone surface, especially if there were microscopic crevices. From the pressure tests, there was a strong indication that the reflection signals determined the excited kidney stones from gas bubbles, presumably shrunken but stabilized in crevices on the stone surface. These bubbles shrunk with an increase in pressure but returned when the pressure is released.

From these experiments, the conclusion is that 1) the detection signals excited the kidney stone and analyzing the reflection signals determined the kidney stone in the excited state, 2) detecting an excited kidney stone was related to acoustic effects and not by abnormal responses of a machine's electronic circuitry or improper signal processing; and 3) detection was suppressed by overpressure and by better wetting of the stone surface. These results further conclude that detecting the kidney stone in the excited state was caused by small bubbles that sit on the irregularities or in crevices on the stone surface.

The above detailed description describes various features and functions of the disclosed systems, devices, and methods with reference to the accompanying Figures. In the Figures, similar symbols typically identify similar components, unless context dictates otherwise. It will be readily understood that the aspects of the present disclosure, as generally described herein, and illustrated in the Figures, can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein.

With respect to any or all of the diagrams, scenarios, and flow charts in the Figures and as discussed herein, each block and/or communication can represent a processing of information and/or a transmission of information in accordance with example embodiments. Alternative embodiments are included within the scope of these example embodiments. In these alternative embodiments, for example, functions described as blocks, transmissions, communications, requests, responses, and/or messages can be executed out of order from that shown or discussed, including substantially concurrent or in reverse order, depending on the functionality involved. Further, more or fewer blocks and/or functions can be used with any of the ladder diagrams, scenarios, and flow charts discussed herein, and these ladder diagrams, scenarios, and flow charts can be combined with one another, in part or in whole.

A block that represents a processing of information can correspond to circuitry that can be configured to perform the specific logical functions of a herein-described method or technique. Alternatively or additionally, a block that represents a processing of information can correspond to a module, a segment, or a portion of program code (including related data). The program code can include one or more instructions executable by a processor for implementing specific logical functions or actions in the method or technique. The program code and/or related data can be stored on any type of computer readable medium such as a storage device including a disk or hard drive or other storage medium.

The computer readable medium can also include physical and/or non-transitory computer readable media such as computer-readable media that stores data for short periods of time like register memory, processor cache, and random access memory (RAM). The computer readable media can also include physical and/or non-transitory computer readable media that stores program code and/or data for longer periods of time, such as secondary or persistent long term storage, like read only memory (ROM), optical or magnetic disks, compact-disc read only memory (CD-ROM), for example. The computer readable media can also be any other volatile or non-volatile storage systems. A computer readable medium can be considered a computer readable storage medium, for example, or a tangible storage device.