Analysis apparatus, ultrasound diagnostic apparatus, and program

Abstract

To efficiently select a cross section suitable for desired analysis.SOLUTION: According to one embodiment, an analysis apparatus includes an acquisition unit, a specification unit and a selection unit. The acquisition unit acquires a thumbnail of each of multiple pieces of cross-section image data related to first cross-section image data selected by a user and showing a cross-section of an organ. The specification unit specifies, using the multiple thumbnails acquired, a cross-section of an organ included in each of the multiple thumbnails. The selection unit selects a cross-section for use as a target of analysis other than a cross-section selected by the user from the specified cross-sections based on a degree of association between the first cross-section image data and each of the multiple pieces of cross-section image data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The embodiments disclosed in the present specification and drawings relate to an analysis device, an ultrasound diagnostic device, and a program. [Background technology]

[0002] Conventionally, when collecting multiple cross sections of an organ (e.g., the heart) to be used for a desired analysis (e.g., myocardial analysis) using an ultrasound probe, there is a function (collection assist function) that automatically collects the cross sections required for myocardial analysis by having the user specify the order of the cross sections to be collected. There is also a function (AI acquisition function) that uses AI (artificial intelligence) to estimate the type of cross section from the multiple cross sections of the heart collected by the user and automatically acquires the cross sections required for myocardial analysis.

[0003] However, these functions have the following issues. For example, the acquisition assistance function may not be able to acquire cross sections in the order that is optimal for the user, which can be a burden for the user. Furthermore, for example, the AI ​​acquisition function requires that images be generated and analyzed from DICOM (Digital Imaging and Communication in Medicine) data for all cross sections when acquiring the required cross sections. This can take time because images are also generated and analyzed for unnecessary cross sections. As a result, with conventional functions, it can take a long time to select the cross sections appropriate for analysis. Therefore, there is a need for technology that can efficiently select the cross sections appropriate for the desired analysis. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-197967 Summary of the Invention [Problem to be solved by the invention]

[0005] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to efficiently select a cross section suitable for a desired analysis. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be positioned as other problems. [Means for solving the problem]

[0006] An analysis device according to an embodiment includes an acquisition unit, an identification unit, and a selection unit. The acquisition unit acquires thumbnails of multiple cross-sectional image data related to first cross-sectional image data selected by a user, the first cross-sectional image data indicating a cross section of an organ. The identification unit uses the acquired thumbnails to identify a cross section of the organ included in each of the multiple thumbnails. The selection unit selects a cross section to be used as an analysis target from the identified multiple cross sections, other than the cross section selected by the user, based on the degree of association between the first cross-sectional image data and each of the multiple cross-sectional image data. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of an ultrasonic diagnostic apparatus according to the first embodiment. [Figure 2] FIG. 2 is a flowchart for explaining the operation of the processing circuit that executes the analysis target extraction process in the first embodiment. [Figure 3] FIG. 3 is a flowchart illustrating the user-selected cross-section processing of FIG. [Figure 4] FIG. 4 is a flowchart illustrating the other cross section selection process of FIG. [Figure 5] FIG. 5 is a flowchart illustrating the selected cross-section determination process of FIG. [Figure 6] FIG. 6 is a diagram illustrating a display screen of the myocardial function analysis application according to the first embodiment. [Figure 7]FIG. 7 is a diagram for explaining the state of the thumbnail image display area in which thumbnail images of analysis candidates are highlighted in the first embodiment. [Figure 8] FIG. 8 is a diagram for explaining the state of the thumbnail image display area in which the analysis order is displayed for the thumbnail images of analysis candidates in the first embodiment. [Figure 9] FIG. 9 is a diagram for explaining the state of the thumbnail image display area in which the name of the cross section is displayed on the thumbnail image of the analysis candidate in the first embodiment. [Figure 10] FIG. 10 is a diagram for explaining the state of the thumbnail image display area in which the thumbnail image to be analyzed is highlighted in the first embodiment. [Figure 11] FIG. 11 is a diagram illustrating a display screen after analysis by the myocardial function analysis application in the first embodiment. [Figure 12] FIG. 12 is a diagram for explaining the state of the thumbnail image display area in which the analysis candidates have been rearranged in the first modified example of the first embodiment. [Figure 13] FIG. 13 is a diagram illustrating the state of the thumbnail image display area in which thumbnail images other than analysis candidates are displayed in an unselected state in the second modified example of the first embodiment. [Figure 14] FIG. 14 is a block diagram showing an example of the configuration of an analysis device according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, embodiments of an ultrasonic diagnostic apparatus and an analysis apparatus will be described in detail with reference to the drawings.

[0009] (First embodiment) Fig. 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus 1 according to the first embodiment. The ultrasound diagnostic apparatus 1 of Fig. 1 includes an apparatus main body 100 and an ultrasound probe 101. The apparatus main body 100 is connected to an input device 102 and an output device 103. The apparatus main body 100 is also connected to an external device 104 via a network NW. The external device 104 is, for example, a server equipped with PACS (Picture Archiving and Communication Systems).

[0010] The ultrasonic probe 101 performs an ultrasonic scan of a scan region in a living body P, which is a subject, under the control of, for example, the device main body 100. The ultrasonic probe 101 has, for example, a plurality of piezoelectric vibrators, a matching layer provided between the plurality of piezoelectric vibrators and a case, and a backing material that prevents ultrasonic waves from propagating backward in the radiation direction from the plurality of piezoelectric vibrators. The ultrasonic probe 101 is, for example, a sector-type electronic scanning probe. The ultrasonic probe 101 is detachably connected to the device main body 100. The ultrasonic probe 101 may be provided with a button that is pressed for offset processing, an operation to freeze an ultrasound image (freeze operation), etc.

[0011] The multiple piezoelectric transducers generate ultrasonic waves based on a drive signal supplied from an ultrasonic transmission circuit 110 (described later) included in the device main body 100. This causes ultrasonic waves to be transmitted from the ultrasonic probe 101 to the living body P. When ultrasonic waves are transmitted from the ultrasonic probe 101 to the living body P, the transmitted ultrasonic waves are reflected successively by discontinuous surfaces of acoustic impedance in the body tissue of the living body P and received as reflected wave signals by the multiple piezoelectric transducers. The amplitude of the received reflected wave signals depends on the difference in acoustic impedance at the discontinuous surfaces from which the ultrasonic waves are reflected. Furthermore, when a transmitted ultrasonic pulse is reflected by a moving blood flow or the surface of a heart wall, etc., the reflected wave signal undergoes a frequency shift due to the Doppler effect, depending on the velocity component of the moving object in the direction of ultrasonic transmission. The ultrasonic probe 101 receives the reflected wave signal from the living body P and converts it into an electrical signal.

[0012] 1 illustrates an example of the connection relationship between one ultrasonic probe 101 and the device main body 100. However, it is possible to connect multiple ultrasonic probes to the device main body 100. Which of the multiple connected ultrasonic probes is to be used for ultrasonic scanning can be arbitrarily selected, for example, by using a software button on a touch panel, which will be described later.

[0013] The device main body 100 is a device that generates an ultrasound image based on a reflected wave signal received by an ultrasound probe 101. The device main body 100 has an ultrasound transmission circuit 110, an ultrasound reception circuit 120, an internal storage circuit 130, an image memory 140, an input interface 150, an output interface 160, a communication interface 170, and a processing circuit 180.

[0014] The ultrasonic transmission circuit 110 is a processor that supplies a drive signal to the ultrasonic probe 101. The ultrasonic transmission circuit 110 is realized by, for example, a trigger generation circuit, a delay circuit, and a pulser circuit. The trigger generation circuit repeatedly generates rate pulses for forming transmitted ultrasonic waves at a predetermined rate frequency. The delay circuit provides each rate pulse generated by the trigger generation circuit with a delay time for each of the multiple piezoelectric transducers required to focus the ultrasonic waves generated from the ultrasonic probe into a beam and determine the transmission directivity. The pulser circuit applies drive signals (drive pulses) to the multiple ultrasonic transducers provided in the ultrasonic probe 101 at a timing based on the rate pulse. By changing the delay time provided to each rate pulse using the delay circuit, the transmission direction from the surfaces of the multiple piezoelectric transducers can be freely adjusted.

[0015] Furthermore, the ultrasound transmission circuit 110 can arbitrarily change the output intensity of the ultrasound waves using the drive signal. In the ultrasound diagnostic device, increasing the output intensity can reduce the influence of ultrasound attenuation within the living body P. By reducing the influence of ultrasound attenuation, the ultrasound diagnostic device can acquire a reflected wave signal with a high S / N ratio during reception.

[0016] Generally, when ultrasound propagates through a living body P, the strength of the ultrasound vibration (also called acoustic power), which corresponds to the output intensity, attenuates. The attenuation of acoustic power occurs due to absorption, scattering, reflection, and the like. The degree of reduction in acoustic power depends on the frequency of the ultrasound and the distance in the direction of ultrasound radiation. For example, the degree of attenuation increases as the frequency of the ultrasound increases. Furthermore, the longer the distance in the direction of ultrasound radiation, the greater the degree of attenuation.

[0017] The ultrasonic receiving circuit 120 is a processor that performs various processes on the reflected wave signals received by the ultrasonic probe 101 to generate received signals. The ultrasonic receiving circuit 120 generates received signals based on the reflected wave signals of ultrasound acquired by the ultrasonic probe 101. Specifically, the ultrasonic receiving circuit 120 is realized by, for example, a preamplifier, an A / D converter, a demodulator, and a beamformer. The preamplifier amplifies the reflected wave signals received by the ultrasonic probe 101 for each channel and performs gain correction processing. The A / D converter converts the gain-corrected reflected wave signals into digital signals. The demodulator demodulates the digital signals. For example, the beamformer applies a delay time required to determine the reception directivity to the demodulated digital signals and adds together the multiple digital signals with the applied delay time. The addition processing of the beamformer generates a received signal in which the reflection components from the direction corresponding to the reception directivity are emphasized.

[0018] The internal storage circuitry 130 includes a processor-readable storage medium, such as a magnetic storage medium, an optical storage medium, or a semiconductor memory. The internal storage circuitry 130 stores a program for transmitting and receiving ultrasound waves, a program related to myocardial function analysis (described later), and various data. The various data include, for example, parameters and a look-up table (LUT) used during program execution. The program and various data may be pre-stored in the internal storage circuitry 130. Alternatively, the program and various data may be stored in a non-transitory storage medium, distributed, read from the non-transitory storage medium, and installed in the internal storage circuitry 130. The internal storage circuitry 130 stores, for example, B-mode image data, contrast image data, and ultrasound image data related to blood flow images generated by the processing circuitry 180 in, for example, a DICOM format, in accordance with operations input via the input interface 150. Ultrasound image data stored in the DICOM format may be referred to as, for example, medical image data. The medical image data may also be, for example, video data. Various information may be added to the medical image data as additional information. The internal storage circuitry 130 can also transfer the stored image data or video data to an external device 104 or the like via the communication interface 170.

[0019] The internal storage circuit 130 may be a drive device that reads and writes various information from and to a portable storage medium such as a CD drive, a DVD drive, or a flash memory. The internal storage circuit 130 can also write stored data to the portable storage medium and store the data in the external device 104 via the portable storage medium.

[0020] The image memory 140 has a processor-readable storage medium, such as a magnetic storage medium, an optical storage medium, or a semiconductor memory. The image memory 140 stores image data corresponding to a plurality of frames immediately before a freeze operation, which are input via the input interface 150. The image data stored in the image memory 140 is, for example, continuously displayed (cine display).

[0021] The internal storage circuit 130 and the image memory 140 do not necessarily have to be realized by independent storage devices. The internal storage circuit 130 and the image memory 140 may be realized by a single storage device. Furthermore, the internal storage circuit 130 and the image memory 140 may each be realized by multiple storage devices.

[0022] The input interface 150 accepts various instructions from an operator (user) via the input device 102 (input unit). The input device 102 is, for example, a mouse, a keyboard, a panel switch, a slider switch, a trackball, a rotary encoder, an operation panel, or a touch panel. The input interface 150 is connected to the processing circuitry 180 via, for example, a bus, converts operation instructions input by the user into electrical signals, and outputs the electrical signals to the processing circuitry 180. Note that the input interface 150 is not limited to those connected to physical operation components such as a mouse and a keyboard. For example, a circuit that receives electrical signals corresponding to operation instructions input from an external input device provided separately from the ultrasound diagnostic apparatus 1 and outputs the electrical signals to the processing circuitry 180 is also included as an example of an input interface.

[0023] The output interface 160 is an interface for outputting, for example, an electrical signal from the processing circuit 180 to the output device 103. The output device 103 is any display such as a liquid crystal display, an organic EL display, an LED display, a plasma display, or a CRT display. The output device 103 may be a touch panel display that also serves as the input device 102. In addition to the display, the output device 103 may further include a speaker that outputs audio. The output interface 160 is connected to the processing circuit 180 via, for example, a bus, and outputs the electrical signal from the processing circuit 180 to the output device 103.

[0024] The communication interface 170 is connected to the external device 104 via, for example, a network NW, and performs data communication with the external device 104 .

[0025] The processing circuitry 180 is, for example, a processor that functions as the core of the ultrasound diagnostic apparatus 1. The processing circuitry 180 executes a program stored in the internal storage circuitry 130 (storage unit) to realize a function corresponding to the program. The processing circuitry 180 has, for example, a B-mode processing function 181, a Doppler processing function 182, an image generation function 183, an acquisition function 184 (acquisition unit), an identification function 185 (identification unit), a calculation function 186 (calculation unit), a selection function 187 (selection unit), a display control function 188 (display control unit), and a system control function 189 (control unit).

[0026] The B-mode processing function 181 is a function that generates B-mode data based on the received signal (echo signal) received from the ultrasound receiving circuit 120. In the B-mode processing function 181, the processing circuit 180 performs, for example, envelope detection processing and logarithmic compression processing on the received signal received from the ultrasound receiving circuit 120, and generates data (B-mode data) that expresses the signal strength (echo reflection strength) of the received signal as a brightness value (luminance value). The generated B-mode data is stored in a RAW data memory (not shown) as B-mode RAW data on a two-dimensional ultrasound scan line (raster).

[0027] Furthermore, the processing circuitry 180 can perform harmonic imaging using the B-mode processing function 181. Harmonic imaging is an imaging method that utilizes not only fundamental wave components contained in reflected ultrasonic wave signals but also harmonic components (harmonic components). Harmonic imaging includes, for example, tissue harmonic imaging (THI), which does not use a contrast agent, and contrast harmonic imaging (CHI), which uses a contrast agent.

[0028] THI can extract harmonic components using an imaging method called the Amplitude Modulation (AM) method, the Phase Modulation (PM) method, or the AMPM method, which is a combination of the AM and PM methods.

[0029] In the AM, PM, and AMPM methods, ultrasonic waves with different amplitudes and phases are transmitted multiple times along the same scan line. This allows the ultrasonic receiving circuitry 120 to generate multiple pieces of reflected wave data for each scan line and output the generated reflected wave data. The processing circuitry 180 extracts harmonic components by performing addition and subtraction processing of the multiple pieces of reflected wave data for each scan line using the B-mode processing function 181 in accordance with the modulation method. The processing circuitry 180 then performs envelope detection processing and the like on the reflected wave data of the harmonic components to generate B-mode data.

[0030] Furthermore, in CHI, for example, harmonic components are extracted using a frequency filter. The processing circuitry 180 can separate reflected wave data (harmonic components) whose reflection source is the contrast agent from reflected wave data (fundamental wave components) whose reflection source is tissue within the living body P using a B-mode processing function 181. As a result, the processing circuitry 180 can select harmonic components from the contrast agent using a filter and generate B-mode data for generating contrast image data.

[0031] The B-mode data for generating contrast image data is data that represents the echo reflection intensity from the contrast agent as a reflection source, expressed as a brightness value. The processing circuitry 180 can also extract the fundamental wave component from the reflected wave data of the living body P to generate B-mode data for generating tissue image data.

[0032] The Doppler processing function 182 is a function that generates data (Doppler information) that extracts motion information based on the Doppler effect of a moving object within a ROI (Region Of Interest) set in a scan area by performing frequency analysis on the received signal received from the ultrasound receiving circuit 120. The generated Doppler information is stored in a RAW data memory (not shown) as Doppler RAW data (also referred to as Doppler data) on a two-dimensional ultrasound scan line.

[0033] Specifically, the processing circuitry 180 uses the Doppler processing function 182 to estimate, for example, the average velocity, average variance, average power, etc., as motion information of a moving object at each of a plurality of sample points, and generates Doppler data indicating the estimated motion information. The moving object is, for example, blood flow, tissue such as a heart wall, or a contrast agent. The processing circuitry 180 according to this embodiment uses the Doppler processing function 182 to estimate, for each of a plurality of sample points, the average velocity of blood flow, the variance of blood flow velocity, the power value of blood flow signals, etc., as motion information of blood flow (blood flow information), and generates Doppler data indicating the estimated blood flow information.

[0034] The image generation function 183 is a function that generates B-mode image data based on data generated by the B-mode processing function 181. For example, in the image generation function 183, the processing circuitry 180 converts (scan converts) a scan line signal sequence of an ultrasound scan into a scan line signal sequence of a video format typified by a television or the like, and generates image data for display (display image data). Specifically, the processing circuitry 180 performs RAW-to-pixel conversion on the B-mode RAW data stored in the RAW data memory, for example, by performing coordinate conversion according to the ultrasound scanning form of the ultrasound probe 101, thereby generating two-dimensional B-mode image data (also referred to as ultrasound image data) composed of pixels. In other words, the processing circuitry 180 generates a plurality of ultrasound images (medical images) corresponding to a plurality of consecutive frames by transmitting and receiving ultrasound waves using the image generation function 183.

[0035] Furthermore, the processing circuitry 180 generates Doppler image data in which blood flow information is visualized, for example, by performing RAW-to-pixel conversion on the Doppler RAW data stored in the RAW data memory. The Doppler image data is mean velocity image data, variance image data, power image data, or image data combining these. The processing circuitry 180 generates, as the Doppler image data, color Doppler image data in which blood flow information is displayed in color, and Doppler image data in which one piece of blood flow information is displayed in a grayscale waveform.

[0036] Furthermore, the processing circuitry 180 may use, for example, medical image data stored in the internal storage circuitry 130 to generate thumbnail images that allow a user to identify the medical image data on a GUI (Graphical User Interface). For example, the processing circuitry 180 may automatically generate thumbnail images when the medical image data is stored in the internal storage circuitry 130. For example, the processing circuitry 180 may use the medical image data to generate preview images with a higher resolution than the thumbnail images. For example, the processing circuitry 180 may use the medical image data to generate medical images with a higher resolution than the preview images. In this embodiment, thumbnail images and preview images may be referred to as low-resolution images or thumbnails, and medical images may be referred to as high-resolution images.

[0037] In addition, when medical image data shows a cross section of an organ, the thumbnail of the medical image data may be displayed so that it is visually and analytically recognizable as a cross section of the organ. Here, "visually recognizable" means, for example, that a user with medical knowledge, such as a doctor or technician, can visually recognize that the content of the thumbnail shows a cross section of the organ. In addition, "analytically recognizable" means, for example, that the processing circuitry 180 can analyze the thumbnail and determine that the content of the thumbnail shows a cross section of the organ. In other words, the thumbnail is information related to the cross section of the organ. Specifically, when the medical image data is video data, the thumbnail may be generated based on the first frame of the video data. In addition, medical image data showing a cross section of an organ may be called "cross-sectional image data."

[0038] The acquisition function 184 is a function for acquiring medical image data (or low-resolution images of medical image data) required for myocardial function analysis processing. For example, in the acquisition function 184, the processing circuitry 180 acquires a plurality of medical image data related to the first medical image data selected by the user, or low-resolution images of each of the plurality of medical image data. For example, the low-resolution images are attached to the medical image data as auxiliary information. The low-resolution images are, for example, thumbnail images or preview images.

[0039] More specifically, the processing circuitry 180 may acquire, as a plurality of medical image data related to the first medical image data or a low-resolution image of each of the plurality of medical image data, a plurality of medical image data acquired in the same mode as the mode of the ultrasound diagnostic device in which the first medical image data was acquired, or a plurality of low-resolution images of the plurality of medical image data. The modes of the ultrasound diagnostic device include, for example, a "2D Single" mode for observing cross sections, a "4D" mode for observing 3D images with movement, and a "Doppler" mode for observing blood flow.

[0040] The identification function 185 is a function for identifying a cross section of an organ from an image related to medical image data. For example, in the identification function 185, the processing circuitry 180 uses a plurality of acquired low-resolution images to identify a cross section of an organ included in each of the plurality of low-resolution images. For example, in the case of the heart, the cross sections of the organ include an apical two-chamber view (Apical-2Ch: A2C), an apical three-chamber view (Apical-3Ch: A3C), an apical four-chamber view (Apical-4Ch: A4C), a parasternal long-axis view (LAx), and a parasternal short-axis view (SAx). For example, a known image recognition technique may be used to identify the cross section of the organ.

[0041] Furthermore, the processing circuitry 180 may identify a first cross section included in a first low-resolution image of the first medical image data selected by the user. Furthermore, the processing circuitry 180 may identify multiple cross sections of the multiple low-resolution images in order of the acquisition time of each of the multiple medical image data closest to the acquisition time of the first medical image data. Information on the acquisition time is, for example, attached to the medical image data as attached information.

[0042] Furthermore, the processing circuitry 180 may use a plurality of high-resolution images corresponding to a plurality of low-resolution images to identify cross sections of organs included in each of the plurality of high-resolution images.

[0043] The calculation function 186 is a function that calculates the degree of association between the first medical image data and each of the multiple medical image data. For example, the calculation function 186 causes the processing circuitry 180 to calculate the degree of association based on the acquisition time of the first medical image data and each of the multiple medical image data. For example, the degree of association based on the acquisition time increases as the difference between the acquisition time of the first medical image data and the acquisition time of the other medical image data decreases.

[0044] Furthermore, the processing circuitry 180 may calculate the degree of association based on the heart rate and the type of probe (e.g., probe ID) attached to the medical image data in addition to the collection time. The degree of association based on the heart rate, for example, increases as the difference between the heart rate of the first medical image data and the heart rate of the other medical image data decreases. The degree of association based on the type of probe, for example, increases if the type of probe that collected the first medical image data is the same as the type of probe that collected the other medical image data.

[0045] In this way, the calculation of the degree of association may be appropriately set so that the value of the degree of association between the first medical image data selected by the user and the medical image data to be analyzed used in the myocardial function analysis process becomes large.

[0046] The selection function 187 is a function for selecting a cross section to be used as an analysis target from among the multiple identified cross sections. For example, the selection function 187 causes the processing circuitry 180 to select other cross sections belonging to the analysis target, including the first cross section included in the first low-resolution image of the first medical image data, from among the multiple identified cross sections based on the degree of association. The analysis target is, for example, a group of cardiac cross sections. For example, in the case of myocardial function analysis processing for obtaining a global longitudinal strain (GLS), the group of cardiac cross sections is an apical two-chamber view, an apical three-chamber view, and an apical four-chamber view.

[0047] The display control function 188 is a function that displays images based on various ultrasound image data generated by the image generation function 183 on a display serving as the output device 103. Specifically, for example, the processing circuitry 180 uses the display control function 188 to control the display of images based on B-mode image data, Doppler image data, or image data including both generated by the image generation function 183 on the display. The processing circuitry 180 may also display a medical image display area that displays ultrasound images and a thumbnail image display area that displays thumbnail images of the medical image data.

[0048] More specifically, the processing circuitry 180 uses the display control function 188 to convert (scan convert) a scan line signal sequence of an ultrasound scan into a scan line signal sequence of a video format typified by a television or the like, and generates image data for display. The processing circuitry 180 may also perform various processes on the image data for display, such as dynamic range, brightness, contrast, and gamma curve correction, and RGB conversion. The processing circuitry 180 may also add information such as text information of various parameters, scales, and body marks to the image data for display. The processing circuitry 180 may also generate a user interface (GUI: Graphical User Interface) for an operator to input various instructions via an input device, and display the GUI on a display.

[0049] The processing circuitry 180 may also display multiple thumbnail images of the first medical image data and the multiple medical image data in the thumbnail image display area in chronological order according to the acquisition time of each medical image data. The processing circuitry 180 may also display the multiple thumbnail images in order of the acquisition time of each of the multiple medical image data, rearranged in descending order of the acquisition time of the first medical image data.

[0050] Furthermore, the processing circuitry 180 may change the display format of multiple thumbnail images depending on whether they are medical image data related to the analysis target. Medical image data related to the analysis target is, for example, medical image data necessary for myocardial function analysis processing. The change in display format may, for example, highlight or emphasize thumbnail images of medical image data necessary for myocardial function analysis processing, or deselect thumbnail images of medical image data other than medical image data necessary for myocardial function analysis processing (for example, marking the thumbnail images with an X or masking the thumbnail images). In this embodiment, the processing circuitry 180 highlights thumbnail images of the analysis target and highlights thumbnail images of analysis candidates. The highlighting and emphasis may be expressed by assigning different colors to the thumbnail images, respectively.

[0051] The processing circuitry 180 may have an analysis function (analysis unit) that executes myocardial function analysis processing. The processing circuitry 180 may generate a GLS analysis result by analyzing a group of medical image data related to the analysis target using the analysis function. This group of medical image data includes, for example, medical image data selected by the user.

[0052] The system control function 189 is a function that controls the overall operation of the ultrasound diagnostic apparatus 1. For example, in the system control function 189, the processing circuitry 180 controls the ultrasound transmission circuitry 110 and the ultrasound reception circuitry 120 based on parameters related to the transmission and reception of ultrasound.

[0053] The configuration of the ultrasound diagnostic apparatus 1 in the first embodiment has been described above. Next, the operation of the analysis target extraction process in the first embodiment will be described. The analysis target extraction process in the first embodiment includes processing of a cross section selected by the user (user-selected cross section processing), processing of selecting other cross sections based on the user-selected cross section (other cross section selection processing), and processing of determining the selected cross section (selected cross section determination processing).

[0054] 2 is a flowchart for explaining the operation of the processing circuit 180 that executes the analysis target extraction process in the first embodiment. The analysis target extraction process in FIG. 2 is started, for example, when a user executes a myocardial function analysis application and selects (or determines) first medical image data. As a specific example, it is assumed below that a myocardial function analysis application that calculates GLS is executed.

[0055] (Step ST110) When the myocardial function analysis application is executed and the first medical image data is selected by the user, the processing circuitry 180 executes user-selected cross section processing. A specific example of the user-selected cross section processing will be described below with reference to the flowchart of FIG.

[0056] FIG. 3 is a flowchart illustrating the user-selected cross-section processing of FIG.

[0057] (Step ST111) When the user-selected cross-section processing is executed, the processing circuitry 180 executes the acquisition function 184. When the acquisition function 184 is executed, the processing circuitry 180 acquires a first low-resolution image of the first medical image data selected by the user. Note that the first low-resolution image is a thumbnail attached to or associated with the first medical image data, and is generated before the user selects it or before the myocardial function analysis application is executed. The same applies to low-resolution images associated with other medical image data.

[0058] (Step ST112) After acquiring the first low-resolution image, the processing circuitry 180 executes the identifying function 185. When the identifying function 185 is executed, the processing circuitry 180 identifies a cross section (first cross section) of an organ included in the first low-resolution image. The display screen after the first cross section is identified will be described below with reference to FIG. 6.

[0059] 6 is a diagram illustrating a display screen 600 of the myocardial function analysis application in the first embodiment. The display screen 600 in FIG. 6 includes a thumbnail image display area 610 and a medical image display area 620.

[0060] The thumbnail image display area 610 displays 14 thumbnail images arranged in small areas of 10 rows and 2 columns. These thumbnail images are displayed in chronological order according to the time at which the corresponding medical image data was acquired. The thumbnail images are arranged in chronological order in the thumbnail image display area 610, from the left side of the first row, to the right side of the first row, to the left side of the second row, and to the right side of the second row, and so on. That is, the thumbnail images are arranged so that the medical image data corresponding to the thumbnail image in the upper left of the thumbnail image display area 610 is the oldest, and the medical image data corresponding to the thumbnail image in the lower right is the newest.

[0061] The user selects any thumbnail image in the thumbnail image display area 610 and checks the preview screen to determine the cross section to be used in the myocardial function analysis. The processing circuitry 180 identifies the cross section of the organ (first cross section) for the medical image data (first medical image data) corresponding to the thumbnail image selected by the user. In the example of FIG. 6, the processing circuitry 180 identifies the cross section "A4C" for the thumbnail image 611 selected by the user, and therefore "A4C" is displayed on the thumbnail image 611. Furthermore, the thumbnail image 611 selected by the user is highlighted in dark gray.

[0062] The medical image display area 620 is divided into four divided areas: a divided area 621, a divided area 622, a divided area 623, and a divided area 624. The divided area 621 is set to display, for example, a medical image of the cross section "A4C." In the example of Fig. 6, the thumbnail image 611 selected by the user represents the cross section "A4C," and therefore the medical image corresponding to the thumbnail image 611 is displayed in the divided area 621.

[0063] Further, for example, divided area 622 is set to display a medical image of cross section "A2C," divided area 623 is set to display a medical image of cross section "A3C," and divided area 624 is set to display the GLS analysis results (bullseye diagram). In the example of Fig. 6, since only cross section "A4C" is set, nothing is displayed in divided areas 622 and 623, and only a bullseye diagram template is displayed in divided area 624.

[0064] (Step ST113) After identifying the first cross section, the processing circuitry 180 acquires additional information about the first low-resolution image. The additional information includes, for example, the acquisition time of the first medical image data, the heart rate, and the type of probe. After step ST113, the user-selected cross section processing ends, and the process proceeds to step ST120.

[0065] (Step ST120) The processing circuitry 180 executes another cross section selection process. A specific example of the other cross section selection process will be described below with reference to the flowchart in Fig. 4. The other cross section selection process may also be called a first-stage discrimination process.

[0066] Fig. 4 is a flowchart illustrating the other cross section selection process of Fig. 2. The flowchart of Fig. 4 transitions from step ST110 of Fig. 2.

[0067] (Step ST121) When the other cross-section selection process is executed, the processing circuitry 180 acquires low-resolution images of medical image data related to the first medical image data using the acquisition function 184. At this time, the processing circuitry 180 may search for medical image data in ascending order of acquisition time relative to the acquisition time of the first medical image data. This allows the processing circuitry 180 to acquire low-resolution images of medical image data in ascending order of acquisition time relative to the acquisition time of the first medical image data. Furthermore, the processing circuitry 180 may acquire low-resolution images of medical image data acquired in the same mode (e.g., "2D Single" mode) of the ultrasound diagnostic device that acquired the first medical image data. This allows the processing circuitry 180 to exclude medical image data acquired in a mode different from the mode to be analyzed.

[0068] (Step ST122) After acquiring the low-resolution image, the processing circuit 180 uses the identification function 185 to identify the cross-section of the organ contained in the low-resolution image.

[0069] (Step ST123) After identifying the cross section of the organ, the processing circuitry 180 determines whether the number of acquired low-resolution images satisfies a predetermined condition. The predetermined condition is, for example, 10 medical image data sets before and after (20 in total) the acquisition time of the first medical image data set selected by the user (i.e., the number of low-resolution images of medical image data). If the number of medical image data sets is less than 20, the predetermined condition is the number of existing medical image data sets. If it is determined that the number of acquired low-resolution images does not satisfy the predetermined condition, the process returns to step ST121. On the other hand, if it is determined that the number of acquired low-resolution images satisfies the predetermined condition, the process proceeds to step ST124. Below, the state of the thumbnail image display area after the number of acquired low-resolution images satisfies the predetermined condition will be described with reference to FIG. 7. Note that FIG. 7 shows only 14 small areas in which thumbnail images exist in the thumbnail image display area. This also applies to FIGS. 8, 9, 10, 12, and 13.

[0070] 7 is a diagram illustrating the state of the thumbnail image display area in which thumbnail images of analysis candidates are highlighted in light gray in the first embodiment. Fig. 7 shows the thumbnail image display area 610 and a thumbnail image display area 710 at the time of transition from step ST123 to step ST124. In addition to the thumbnail image 711 selected by the user, eight thumbnail images are highlighted in light gray as analysis candidates in the thumbnail image display area 710. Note that, at the time of highlighting the eight thumbnail images (at the time of transition from step ST123 to step ST124), the cross sections associated with each thumbnail image have been identified, but for convenience of explanation, the names of the cross sections are not displayed on the thumbnail images.

[0071] (Step ST124) After determining in step ST123 that the number of acquired low-resolution images satisfies a predetermined condition, the processing circuitry 180 executes the calculation function 186. Using the calculation function 186, the processing circuitry 180 calculates the degree of association between the first medical image data and each of the multiple medical image data. Specifically, the processing circuitry 180 calculates the degree of association using the supplementary information of each medical image data. Below, the state of the thumbnail image display area after the degree of association is calculated will be described with reference to FIG. 8.

[0072] 8 is a diagram illustrating the state of the thumbnail image display area in which the analysis order is displayed for thumbnail images that are analysis candidates in the first embodiment. Fig. 8 shows the thumbnail image display area 710 and a thumbnail image display area 810 after the relevance has been calculated. In the thumbnail image display area 810, numbers are displayed on eight highlighted thumbnail images as the analysis order based on the collection time of the relevance. These numbers are determined based on the time interval between the collection time of the thumbnail image 811 selected by the user and the collection time of each thumbnail image.

[0073] (Step ST125) After calculating the degree of association, the processing circuitry 180 executes the selection function 187. When the selection function 187 is executed, the processing circuitry 180 selects other cross sections belonging to the analysis target based on the degree of association. Specifically, the processing circuitry 180 performs the selection process in order of the acquisition times of the multiple medical image data closest to the acquisition time of the selected medical image data (i.e., the above-mentioned analysis order). In the selection process, the other cross sections to be selected are based on the group of analysis targets associated with the myocardial function analysis application. That is, the processing circuitry 180 selects an analysis target different from the analysis target selected by the user based on the group of analysis targets. After step ST125, the other cross section selection process ends, and the process proceeds to step ST130. The state of the thumbnail image display area during the selection process will be described below with reference to FIG. 9.

[0074] FIG. 9 is a diagram illustrating the state of the thumbnail image display area in which the names of cross sections are displayed on thumbnail images of analysis candidates in the first embodiment. FIG. 9 shows the thumbnail image display area 810 and the thumbnail image display area 910 after the names are displayed. In the thumbnail image display area 910, the names of the cross sections are displayed on eight highlighted thumbnail images. In this case, since the thumbnail image 911 selected by the user is the cross section "A4C," the other cross sections belonging to the analysis target are the cross sections "A2C" and "A3C." Next, the state of the thumbnail image display area after the analysis target is selected will be described with reference to FIG. 10.

[0075] Fig. 10 is a diagram illustrating the state of the thumbnail image display area in which the thumbnail image to be analyzed is highlighted in the first embodiment. Fig. 10 shows the thumbnail image display area 910 and a thumbnail image display area 1010 after the analysis target has been selected. Of the eight highlighted thumbnail images, the thumbnail image display area 1010 highlights two thumbnail images, thumbnail image 1011 selected by the user, as well as thumbnail image 1012 and thumbnail image 1013, as analysis targets.

[0076] 10, the fourth closest thumbnail image 1012 (cross section "A2C") is selected and highlighted compared to the first closest thumbnail image (cross section "A2C") with respect to the acquisition time of the thumbnail image 1011 (cross section "A4C") selected by the user. This indicates that the medical image data of the fourth closest thumbnail image 1012 is more related to the medical image data of the first closest thumbnail image.

[0077] It should be noted that, since the above-mentioned FIGS. 7 to 10 are all explanatory diagrams, the display form of the thumbnail image display area shown in each diagram may or may not be displayed on the display.

[0078] 4, step ST122 and step ST123 may be interchanged. That is, step ST123 is executed after step ST121, and if the processing result in step ST123 is YES, step ST122 is executed, and step ST122 is followed by step ST124. By using this processing order, the processing circuitry 180 can acquire multiple thumbnails generated in advance and identify cross sections of organs collectively using the acquired multiple thumbnails.

[0079] (Step ST130) The processing circuitry 180 executes a selected cross-section determination process. A specific example of the selected cross-section determination process will be described below with reference to the flowchart in Fig. 5. The selected cross-section determination process may also be called a second-stage discrimination process.

[0080] Fig. 5 is a flowchart illustrating the selected cross-section determination process of Fig. 2. The flowchart of Fig. 5 transitions from step ST120 of Fig. 2.

[0081] (Step ST131) When the selected cross section determination process is executed, the processing circuitry 180 executes the image generation function 183. When the image generation function 183 is executed, the processing circuitry 180 generates a plurality of high-resolution images using a plurality of analysis target medical image data related to the analysis target.

[0082] (Step ST132) After generating the multiple high-resolution images, the processing circuitry 180 identifies the cross-section of the organ included in each of the multiple high-resolution images using the identification function 185. The identification of the cross-section of the organ has been performed using the low-resolution images in step ST122. In this step, the cross-section of the organ is identified again using the high-resolution images.

[0083] (Step ST133) After identifying the cross section of the organ, the processing circuitry 180 determines whether the identified cross section of the organ belongs to the analysis target. Whether or not it belongs to the analysis target is determined based on the group of the analysis target in step ST125. If it is determined that the identified cross section of the organ belongs to the analysis target, the process proceeds to step ST134. On the other hand, if it is determined that the identified cross section of the organ does not belong to the analysis target, or if the analysis targets overlap, the process proceeds to step ST135.

[0084] (Step ST134) After determining in step ST133 that the cross section of the organ identified belongs to the analysis target, the processing circuitry 180 determines the plurality of medical image data as the analysis target. At this time, the processing circuitry 180 may associate each of the plurality of medical image data determined as the analysis target. After step ST134, the selected cross section determination process ends, and the analysis target extraction process of FIG. 2 ends.

[0085] (Step ST135) After determining in step ST133 that the cross section of the organ identified does not belong to the analysis target, the processing circuitry 180 notifies the user to manually select multiple medical image data. Specifically, the processing circuitry 180 displays a dialog to the user informing them that manual selection is required. Furthermore, the processing circuitry 180 may present multiple cross sections that may belong to the analysis target to prompt the user to make a selection. After step ST135, the selected cross section determination process ends, and the analysis target extraction process of FIG. 2 ends.

[0086] 11 is a diagram illustrating a display screen 1100 after analysis by the myocardial function analysis application in the first embodiment. The display screen 1100 in FIG. 11 includes a thumbnail image display area 1110 and a medical image display area 1120. The thumbnail image display area 1110 and the medical image display area 1120 have the same configuration as the thumbnail image display area 610 and the medical image display area 620 in FIG. 6.

[0087] In the thumbnail image display area 1110, in addition to the thumbnail image 1111 (cross section "A4C") selected by the user, two thumbnail images, 1112 (cross section "A2C") and 1113 (cross section "A3C"), are highlighted as targets for analysis.

[0088] In the medical image display area 1120, a divided area 1121 displays a medical image corresponding to a thumbnail image 1111 (cross section "A4C"), a divided area 1122 displays a medical image corresponding to a thumbnail image 1112 (cross section "A2C"), a divided area 1123 displays a medical image corresponding to a thumbnail image 1113 (cross section "A3C"), and a divided area 1124 displays the GLS analysis results (bullseye diagram).

[0089] In summary, when a user executes a myocardial function analysis application for calculating GLS and selects one thumbnail image (the cross section "A4C") to be analyzed, the processing circuitry 180 of the ultrasound diagnostic apparatus 1 selects the remaining two cross sections (the cross sections "A2C" and "A3C") as a group for calculating GLS. The processing circuitry 180 then highlights the thumbnail images, displays medical images of each cross section, and displays GLS analysis results (bullseye diagrams) based on each medical image. Note that when the user selects another thumbnail image on the display screen after analysis by the myocardial function analysis application, the processing circuitry 180 executes the above process again, updating the display screen to display the selected thumbnail image.

[0090] (First Modification of the First Embodiment) Fig. 12 is a diagram for explaining the state of the thumbnail image display area in which the analysis candidates have been rearranged in the first modified example of the first embodiment. Fig. 12 shows the thumbnail image display area 810 and a thumbnail image display area 1210 after the rearrangement.

[0091] The thumbnail image display area 1210 includes a thumbnail image 1211 highlighted by user selection, eight thumbnail images highlighted as analysis candidates, and other thumbnail images. The thumbnail image 1211 is located in the upper left of the thumbnail image display area 1210, and the eight thumbnail images are arranged in order of their acquisition times relative to the acquisition time of the medical image data corresponding to the thumbnail image 1211.

[0092] According to the first modification of the first embodiment, when a user manually selects medical image data, the thumbnail images are rearranged in descending order of acquisition time based on the acquisition time of the medical image data first selected by the user. This allows the user to visually recognize the rearranged thumbnail images, thereby improving visibility in the thumbnail image display area.

[0093] (Second Modification of the First Embodiment) Fig. 13 is a diagram illustrating the state of the thumbnail image display area in which thumbnail images other than analysis candidates are displayed in an unselected state in the second modified example of the first embodiment. Fig. 13 shows the thumbnail image display area 810 and a thumbnail image display area 1310 after the unselected display process.

[0094] The thumbnail image display area 1310 includes the thumbnail image 1211 that has been highlighted by the user's selection, and eight thumbnail images that have been highlighted as analysis candidates. Thumbnail images other than the thumbnail image 1211 and the eight thumbnail images are marked with an X and are displayed as unselected, i.e., unselected.

[0095] According to the second modification of the first embodiment, when a user manually selects medical image data, thumbnail images that do not need to be selected are displayed as unselected. This eliminates the need for the user to check unnecessary thumbnail images, thereby improving visibility in the thumbnail image display area.

[0096] (Third Modification of the First Embodiment) In the first embodiment, a series of processes from the execution of the myocardial function analysis application to the generation of the display screen exemplified in Fig. 11 has been described. On the other hand, in the third modified example of the first embodiment, a process after the generation of the display screen exemplified in Fig. 11 will be described.

[0097] Specifically, in the third modified example of the first embodiment, it is assumed that the user selects another thumbnail image after the display screen exemplified in Fig. 11 is displayed. When the user selects another thumbnail image on the display screen after analysis by the myocardial function analysis application, the processing circuitry 180 can be set in advance by the user to execute, for example, one of the following two processes (first process and second process).

[0098] In the first process, after the user selects another thumbnail image, another medical image is selected again based on the selected thumbnail image. That is, the first process is equivalent to executing the flowchart of Fig. 2 again. In this case, the processing circuitry 180 performs an analysis process based on medical images included in another analysis target, including the medical image corresponding to the other thumbnail image, and generates another analysis result.

[0099] The second process changes only another thumbnail image selected by the user. For example, on the display screen 1100 of FIG. 11, if the user wants to change the medical image of the cross section "A3C" displayed in the divided area 1123, the user selects the thumbnail image of the cross section "A3C" from the thumbnail image display area 1110. After the user selects the thumbnail image, the processing circuitry 180 changes the medical image included in the analysis target to a medical image corresponding to the selected thumbnail image, performs analysis processing based on the changed medical image, and generates another analysis result based on the other analysis target.

[0100] According to the first and second processes described above, the processing circuitry 180 may display a medical image of another analysis target including another medical image selected by the user, and another analysis result generated from the other analysis target, where the medical image of the other analysis target is different from at least one medical image of the medical images of the analysis target.

[0101] According to the third modification of the first embodiment, a user can flexibly change the medical images used in the analysis process even after the myocardial function analysis application is executed, thereby improving the user convenience in executing the myocardial function analysis process.

[0102] (Fourth Modification of the First Embodiment) In the first embodiment, the user selects an arbitrary thumbnail using a thumbnail image display area included in the display screen after the myocardial function analysis application is executed, as shown in Fig. 6. On the other hand, in a fourth modified example of the first embodiment, the user may select an arbitrary thumbnail on a display screen (e.g., an examination list screen) before the myocardial function analysis application is executed.

[0103] The examination list screen includes, for example, a thumbnail image display area for examination images of a patient taken on the day of the examination. The user may select any thumbnail using the thumbnail image display area included in the examination list screen. After the user selects any thumbnail, the user may execute the myocardial function analysis application by pressing a software button (e.g., a button for executing the myocardial function analysis application) that is displayed (or has been displayed) on the examination list screen. In this case, the thumbnail is selected when the myocardial function analysis application is executed.

[0104] According to the fourth modification of the first embodiment, the user can select a thumbnail and execute the myocardial function analysis process using any display screen, not just the display screen of the myocardial function analysis application, thereby improving the user convenience in executing the myocardial function analysis process.

[0105] (Another specific example of the first embodiment) The first embodiment has been described above with reference to a specific example of a myocardial function analysis application for determining GLS. Another specific example of the first embodiment will be described with reference to an application for performing stress echocardiography (analysis).

[0106] In stress echocardiography, the same cross sections are collected as the analysis target in both the first phase before stress is applied to the patient and the second phase after stress is applied to the patient. The analysis target is, for example, a group of cardiac cross sections. In stress echocardiography, the group of cardiac cross sections is, for example, the apical two-chamber view, the apical four-chamber view, the parasternal long-axis view, and the parasternal short-axis view.

[0107] For example, in stress echocardiography analysis, the processing circuitry 180 may perform processing substantially similar to that of the first embodiment. Information specific to stress echocardiography analysis includes phase information. The phase information is, for example, information indicating whether the collected medical image data belongs to the first phase or the second phase. Furthermore, the phase information is, for example, attached to the medical image data as incidental information. Therefore, when the processing circuitry 180 calculates the degree of association between medical image data using the calculation function 186, the degree of association may also be based on stress echocardiography phase information attached to the medical image data. The degree of association based on the phase information is, for example, larger if the medical image data are in the same phase. In other words, the processing circuitry 180 calculates a larger degree of association between medical image data in the same phase of stress echocardiography analysis.

[0108] Specifically, the processing circuitry 180 can select medical image data to be analyzed from among medical image data collected during stress echocardiography, or associate multiple medical image data determined as analysis targets for each phase. In addition, the processing circuitry 180 can replace medical image data to be analyzed if the recollected medical image data has a higher degree of association than the medical image data that has already been collected.

[0109] The processing circuitry 180 may have a stress echocardiographic analysis function (stress echocardiographic analysis unit) that executes stress echocardiographic analysis. The processing circuitry 180 may generate stress echocardiographic analysis results by analyzing a group of medical image data related to the analysis target using the stress echocardiographic analysis function. This group of medical image data includes, for example, medical image data selected by the user.

[0110] In summary, the ultrasound diagnostic apparatus according to the first embodiment searches for thumbnails surrounding a thumbnail selected by a user (selected thumbnail) to automatically select a thumbnail depicting a cross section of an organ other than that depicted in the selected thumbnail. Specifically, the ultrasound diagnostic apparatus according to the first embodiment automatically selects a medical image from among multiple medical image candidates corresponding to multiple automatically selected thumbnails based on at least one of similar heart rates, images in the same stress echocardiogram phase, and images acquired with the same probe. The ultrasound diagnostic apparatus according to the first embodiment generates analysis results based on the medical image selected by the user and the automatically selected medical image, and generates a display image including the multiple medical images and the analysis results. Furthermore, if a different thumbnail is selected by the user after generating the display image, the ultrasound diagnostic apparatus according to the first embodiment updates the analysis results and the display image based on the medical image corresponding to the different thumbnail.

[0111] As described above, the ultrasound diagnostic apparatus according to the first embodiment acquires low-resolution images (thumbnails) of each of a plurality of cross-sectional image data related to the first medical image data (first cross-sectional image data) selected by the user and showing a cross-section of an organ, identifies the cross-section of the organ included in each of the plurality of thumbnails using the acquired thumbnails, and selects a cross-section to be used as an analysis target from the identified plurality of cross-sections, other than the cross-section selected by the user, based on the degree of association between the first cross-sectional image data and each of the plurality of cross-sectional image data.

[0112] Therefore, the ultrasound diagnostic apparatus according to the first embodiment can identify a cross section from a low-resolution image (thumbnail) and select a cross section that belongs to the analysis target based on the degree of association, thereby efficiently selecting a cross section suitable for the desired analysis.

[0113] (Second embodiment) The first embodiment has been described with respect to an ultrasonic diagnostic apparatus that performs myocardial function analysis processing, whereas the second embodiment will be described with respect to an analysis apparatus that performs myocardial function analysis processing.

[0114] Fig. 14 is a block diagram showing an example of the configuration of an analysis device 1400 according to the second embodiment. The analysis device 1400 in Fig. 14 is connected to an input device 1401 and an output device 1402. The analysis device 1400 is also connected to a medical imaging device 1403 via a network NW. The medical imaging device 1403 corresponds to, for example, an ultrasound diagnostic device. The input device 1401 is substantially the same as the input device 102 in Fig. 1, and typically corresponds to a mouse and keyboard. The output device 1402 is substantially the same as the output device 103 in Fig. 1.

[0115] Analysis device 1400 is, for example, a computer capable of executing a myocardial function analysis application. Analysis device 1400 includes a memory circuit 1410, an input interface 1420, an output interface 1430, a communication interface 1440, and a processing circuit 1450.

[0116] The memory circuitry 1410 includes a processor-readable storage medium, such as a magnetic storage medium, an optical storage medium, or a semiconductor memory. The memory circuitry 1410 stores a program related to myocardial function analysis and various data. The various data include, for example, parameters and LUTs used during program execution. The program and various data may be pre-stored in the memory circuitry 1410. Alternatively, the program and various data may be stored in a non-transitory storage medium, distributed, read from the non-transitory storage medium, and installed in the memory circuitry 1410. The memory circuitry 1410 also stores medical image data generated by the medical imaging device 1403 or the like in accordance with operations input via the input interface 1420. The memory circuitry 1410 can also transfer the stored medical image data to an external device or the like via the communication interface 1440.

[0117] The storage circuit 1410 may be a drive device that reads and writes various information from and to a portable storage medium such as a CD drive, a DVD drive, or a flash memory. The storage circuit 1410 can write stored data to the portable storage medium and store the data in an external device via the portable storage medium.

[0118] The input interface 1420 receives various instructions from an operator via the input device 1401. The input interface 1420 is connected to the processing circuit 1450 via, for example, a bus, converts the operation instructions input by the operator into electrical signals, and outputs the electrical signals to the processing circuit 1450. Note that the input interface 1420 is not limited to those connected to physical operation components such as a mouse and a keyboard. For example, a circuit that receives electrical signals corresponding to operation instructions input from an external input device provided separately from the analysis device 1400 and outputs the electrical signals to the processing circuit 1450 is also included as an example of the input interface.

[0119] The output interface 1430 is an interface for outputting, for example, an electrical signal from the processing circuit 1450 to the output device 1402. The output interface 1430 is connected to the processing circuit 1450 via, for example, a bus, and outputs the electrical signal from the processing circuit 1450 to the output device 1402.

[0120] The communication interface 1440 is connected to the medical imaging device 1403 and an external device via, for example, a network NW, and performs data communication between the devices.

[0121] The processing circuitry 1450 is, for example, a processor that functions as the core of the analysis device 1400. The processing circuitry 1450 executes a program stored in the storage circuitry 1410 to realize a function corresponding to the program. The processing circuitry 1450 has an acquisition function 184 (acquisition unit), an identification function 185 (identification unit), a calculation function 186 (calculation unit), a selection function 187 (selection unit), a display control function 188 (display control unit), and a system control function 189 (control unit) in the first embodiment. These various functions are substantially the same as those in the first embodiment, and therefore description thereof will be omitted.

[0122] As described above, the analysis device according to the second embodiment acquires low-resolution images (thumbnails) of each of a plurality of cross-sectional image data related to the first medical image data (first cross-sectional image data) selected by the user, which is a cross-section of an organ, and uses the acquired thumbnails to identify the cross-section of the organ contained in each of the plurality of thumbnails, and selects, from the identified plurality of cross-sections, a cross-section to be used as an analysis target other than the cross-section selected by the user, based on the degree of association between the first cross-sectional image data and each of the plurality of cross-sectional image data.

[0123] Therefore, the analysis device according to the second embodiment is expected to have the same effects as the first embodiment.

[0124] According to at least one of the embodiments described above, a cross section suitable for a desired analysis can be efficiently selected.

[0125] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0126] 1. Ultrasound diagnostic equipment 100 Device body 101 Ultrasound probe 102,1401 Input devices 103,1402 Output Device 104 External device 110 Ultrasonic transmission circuit 120 Ultrasonic receiving circuit 130 Internal memory circuit 140 image memory 150,1420 input interface 160,1430 output interface 170,1440 Communication Interface 180,1450 Processing circuit 181 B-mode processing function 182 Doppler processing function 183 Image generation function 184 Acquisition Function 185 Specific Functions 186 Calculation Function 187 Selection Function 188 Display Control Function 189 System Control Functions 600,1100 display screen 610,710,810,910,1010,1110,1210,1310 Thumbnail image display area 611,711,811,911,1011,1012,1013,1111,1112,1113,1211 Thumbnail images 620,1120 Medical image display area 621,622,623,624,1121,1122,1123,1124 Divided area 1400 Analysis device 1403 Medical imaging equipment 1410 Memory circuit NW Network

Claims

1. an acquisition unit that acquires thumbnails of each of a plurality of cross-sectional image data related to first cross-sectional image data selected by a user, the first cross-sectional image data indicating a cross section of an organ; an identification unit that uses the acquired thumbnails to identify a cross section of an organ included in each of the acquired thumbnails; a selection unit that selects a cross section to be used as an analysis target from the specified plurality of cross sections based on the degree of association between the first cross section image data and each of the plurality of cross section image data, the cross section being other than the cross section selected by the user; An analysis device comprising:

2. The thumbnail is information about a cross section of the organ. The analysis device according to claim 1 .

3. the acquisition unit acquires the plurality of thumbnails of the plurality of cross-sectional image data acquired in the same mode as the mode of the ultrasound diagnostic apparatus in which the first cross-sectional image data was acquired. The analysis device according to claim 1 .

4. the acquisition unit searches the plurality of thumbnails in order of the acquisition time of each of the plurality of cross-sectional image data being closest to the acquisition time of the first cross-sectional image data; The analysis device according to claim 1 .

5. The degree of association is based on the acquisition time of the first cross-sectional image data. The analysis device according to claim 1 .

6. the degree of association is based on at least one of a heart rate, a probe type, and phase information of stress echocardiography, which are attached to the first cross-sectional image data; The analysis device according to claim 5 .

7. a calculation unit for calculating a degree of association between the first cross-sectional image data and each of the plurality of cross-sectional image data; Further comprising: The analysis device according to claim 1 .

8. The analysis object is a group of cross sections of the heart. The analysis device according to claim 1 .

9. the group including apical two-chamber view, apical three-chamber view, and apical four-chamber view, or apical two-chamber view, apical four-chamber view, parasternal long axis view, and parasternal short axis view; The analysis device according to claim 8.

10. a display control unit that sorts and displays the first cross-sectional image data and the plurality of thumbnails of the plurality of cross-sectional image data in order of the acquisition time of each of the plurality of cross-sectional image data being closest to the acquisition time of the first cross-sectional image data; The analysis device of claim 1 further comprising:

11. a display control unit that changes the display format of the first cross-sectional image data and the plurality of thumbnails of the plurality of cross-sectional image data depending on whether the cross-sectional image data is related to the analysis target and displays the thumbnails; The analysis device of claim 1 further comprising:

12. an analysis unit that generates an analysis result by analyzing cross-sectional image data of an analysis target including the first cross-sectional image data; a display control unit that displays the cross-sectional image data of the analysis target and the analysis results; The analysis device of claim 1 further comprising:

13. the display control unit displays the cross-sectional image data of another analysis target including the cross-sectional image data selected by the user and another analysis result generated from the other analysis target; The cross-sectional image data of the other analysis target is different in at least one cross-sectional image data of the cross-sectional image data of the analysis target. The analysis device according to claim 12.

14. an acquisition unit that acquires thumbnails of each of a plurality of cross-sectional image data related to first cross-sectional image data selected by a user, the first cross-sectional image data indicating a cross section of an organ; an identification unit that uses the acquired thumbnails to identify a cross section of an organ included in each of the acquired thumbnails; a selection unit that selects a cross section to be used as an analysis target from the specified plurality of cross sections based on the degree of association between the first cross section image data and each of the plurality of cross section image data, the cross section being other than the cross section selected by the user; An ultrasound diagnostic device comprising:

15. Computer a means for acquiring thumbnails of each of a plurality of cross-sectional image data related to a first cross-sectional image data selected by a user, the first cross-sectional image data indicating a cross section of an organ; a means for identifying a cross section of an organ included in each of the acquired thumbnails using the acquired thumbnails; a means for selecting a cross section to be used as an analysis target from the plurality of cross sections identified based on the degree of association between the first cross section image data and each of the plurality of cross section image data, the cross section being other than the cross section selected by the user; A program that functions as a

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