Ultrasonic diagnostic apparatus, image processing apparatus, and image processing program

Abstract

To present the status of processing performed in the background to an operator.SOLUTION: An ultrasonic diagnostic device according to an embodiment includes an image acquisition unit, a contour candidate acquisition unit, and a contour determination unit. The image acquisition unit acquires ultrasonic image data by ultrasonic scanning. The contour candidate acquisition unit acquires a plurality of candidates of contour information on the basis of the quantitative value indicating the function of the tissue, superimposes the candidates of the contour information on the ultrasonic image data, and causes the display unit to display the candidates. The contour determination unit determines the contour information from the plurality of candidates of the contour information.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The embodiments disclosed in this specification and the drawings relate to an ultrasonic diagnostic apparatus, an image processing apparatus, and an image processing program.

Background Art

[0002] In the medical field, an ultrasonic diagnostic apparatus is used to image the inside of a subject by using ultrasonic waves generated by a plurality of vibrators (piezoelectric vibrators) of an ultrasonic probe. The ultrasonic diagnostic apparatus transmits ultrasonic waves into the subject from an ultrasonic probe connected to the ultrasonic diagnostic apparatus, generates an echo signal based on the reflected waves, and obtains a desired ultrasonic image by image processing.

[0003] In an echocardiogram examination using an ultrasonic diagnostic apparatus, after a freeze operation of the display image, the operator manually selects a heartbeat considered to be optimal from a plurality of recent heartbeats, and various measurements and analyses are performed on the ultrasonic image corresponding to the selected heartbeat. Examples of methods for measuring and analyzing ultrasonic images include two-dimensional WMT (Wall Motion Tracking) and three-dimensional WMT for analyzing myocardial wall motion, and Auto_EF (Automated Ejection Fraction) for automatically calculating the left ventricular ejection fraction, etc.

[0004] Auto_EF performs pattern recognition by comparing the actual shape of the heart with features (appearance of the heart, left ventricular endocardium, etc.) registered in a pre-constructed database, searches for a heart having a similar pattern, detects the left ventricular endocardium, and calculates, as quantitative values indicating the function of the heart at each heartbeat, the end-diastolic left ventricular volume (EDV), the end-systolic left ventricular volume (ESV), the left ventricular ejection fraction (EF), etc.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to present a plurality of contour information corresponding to the quantitative values indicating the functions of tissues to the operator.

[0007] However, the problems solved by the embodiments disclosed in this specification and the like are not limited to the above problems. The problems corresponding to the respective effects of each configuration shown in the embodiments described later can also be regarded as other problems solved by the embodiments disclosed in this specification and the like.

Means for Solving the Problems

[0008] The ultrasonic diagnostic apparatus according to the embodiment includes an image acquisition unit, a contour candidate acquisition unit, and a contour determination unit. The image acquisition unit acquires ultrasonic image data by ultrasonic scanning. The contour candidate acquisition unit acquires candidates for a plurality of contour information based on the quantitative values indicating the functions of tissues, and superimposes the candidates for the plurality of contour information on the ultrasonic image data and displays them on the display unit. The contour determination unit determines the contour information from the candidates for the plurality of contour information.

Brief Description of the Drawings

[0009]

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MODE FOR CARRYING OUT THE INVENTION

[0010] Hereinafter, embodiments of an ultrasonic diagnostic apparatus, an image processing apparatus, and an image processing program will be described in detail with reference to the drawings.

[0011] The image processing apparatus according to the embodiment is provided as part of a medical image diagnostic apparatus that generates medical images. Hereinafter, in the first embodiment, a case where the image processing apparatus is provided as part of an ultrasonic diagnostic apparatus as a medical image diagnostic apparatus will be described. However, it is not limited to that case. For example, the image processing apparatus may be provided as part of a simple X-ray apparatus, an X-ray fluoroscopy apparatus, an X-ray CT (Computed Tomography) apparatus, an MRI (Magnetic Resonance Imaging) apparatus, a nuclear medicine diagnostic apparatus, etc. as a medical image diagnostic apparatus. Further, the image processing apparatus according to the embodiment may be installed separately from the medical image diagnostic apparatus and process the medical image data acquired by the medical image diagnostic apparatus. Hereinafter, in the second embodiment, a case where the image processing apparatus is installed separately from the medical image diagnostic apparatus will be described.

[0012] (First Embodiment) The image processing apparatus according to the first embodiment is provided as part of an ultrasonic diagnostic apparatus as a medical image diagnostic apparatus.

[0013] FIG. 1 is a schematic diagram showing an example of the configuration of an ultrasonic diagnostic apparatus provided with the image processing apparatus according to the embodiment.

[0014] FIG. 1 shows an ultrasonic diagnostic apparatus 1 provided with an image processing apparatus 10 according to the embodiment. The ultrasonic diagnostic apparatus 1 shows the image processing apparatus 10, an ultrasonic probe 20, an input interface 30, a display 40, and a biological signal sensor 50. Note that in some cases, an apparatus obtained by adding at least one of the ultrasonic probe 20, the input interface 30, the display 40, and the biological signal sensor 50 to the image processing apparatus 10 may be referred to as an image processing apparatus. In the following description, a case where all of the ultrasonic probe 20, the input interface 30, the display 40, and the biological signal sensor 50 are provided outside the image processing apparatus 10 will be described.

[0015] The image processing apparatus 10 includes a transmission / reception circuit 11, a B-mode processing circuit 12, a Doppler processing circuit 13, an image generation circuit 14, an image memory 15, a network interface 16, a processing circuit 17, and a main memory 18. The circuits 11 to 14 are configured by an application specific integrated circuit (ASIC) or the like. However, it is not limited to that case, and all or part of the functions of the circuits 11 to 14 may be realized by the processing circuit 17 executing a program.

[0016] The transmission / reception circuit 11 has a transmission circuit and a reception circuit (not shown). The transmission / reception circuit 11 controls the transmission directivity and the reception directivity in the transmission and reception of ultrasonic waves under the control of the processing circuit 17. Although the case where the transmission / reception circuit 11 is provided in the image processing apparatus 10 will be described, the transmission / reception circuit 11 may be provided in the ultrasonic probe 20, or may be provided in both the image processing apparatus 10 and the ultrasonic probe 20. Note that the transmission / reception circuit 11 is an example of a transmission / reception unit.

[0017] The transmission circuit has a pulse generation circuit, a transmission delay circuit, a pulsar circuit, etc., and supplies a drive signal to the ultrasonic transducer. The pulse generation circuit repeatedly generates rate pulses for forming transmitted ultrasonic waves at a predetermined rate frequency. The transmission delay circuit focuses the ultrasonic waves generated from the ultrasonic transducers of the ultrasonic probe 20 into a beam shape, and gives the delay time for each piezoelectric vibrator necessary for determining the transmission directivity to each rate pulse generated by the pulse generation circuit. Further, the pulsar circuit applies a drive pulse to the ultrasonic transducer at a timing based on the rate pulse. The transmission delay circuit arbitrarily adjusts the transmission direction of the ultrasonic beam transmitted from the piezoelectric vibrator surface by changing the delay time given to each rate pulse.

[0018] The receiving circuit has an amplifier circuit, an A / D (Analog to Digital) converter, an adder, etc., receives the echo signal received by the ultrasonic transducer, and performs various processes on this echo signal to generate echo data. The amplifier circuit amplifies the echo signal for each channel and performs gain correction processing. The A / D converter performs A / D conversion on the gain-corrected echo signal and gives a delay time necessary for determining the reception directivity to the digital data. The adder performs an addition process on the echo signal processed by the A / D converter to generate echo data. By the addition process of the adder, the reflection component from the direction corresponding to the reception directivity of the echo signal is emphasized.

[0019] The B-mode processing circuit 12 receives echo data from the receiving circuit under the control of the processing circuit 17, performs logarithmic amplification, envelope detection processing, etc., and generates data (two-dimensional or three-dimensional data) in which the signal intensity is represented by the brightness of the luminance. This data is generally called B-mode data. Note that the B-mode processing circuit 12 is an example of a B-mode processing unit.

[0020] Incidentally, the B-mode processing circuit 12 can change the frequency band to be visualized by changing the detection frequency through filter processing. By using the filter processing function of the B-mode processing circuit 12, harmonic imaging such as contrast harmonic imaging (CHI) and tissue harmonic imaging (THI) can be executed. That is, the B-mode processing circuit 12 can separate the reflected wave data of the harmonic component (harmonic wave data or sub-harmonic wave data) with the contrast agent (microbubbles, bubbles) as the reflection source and the reflected wave data of the fundamental wave component (fundamental wave data) with the tissue in the subject as the reflection source from the reflected wave data of the subject injected with the contrast agent. The B-mode processing circuit 12 can also generate B-mode data for generating contrast image data from the reflected wave data of the harmonic component (received signal), and can also generate B-mode data for generating fundamental wave (fundamental) image data from the reflected wave data of the fundamental wave component (received signal).

[0021] Also, in THI by using the filter processing function of the B-mode processing circuit 12, harmonic wave data or sub-harmonic wave data, which are the reflected wave data of the harmonic component (received signal), can be separated from the reflected wave data of the subject. Then, the B-mode processing circuit 12 can generate B-mode data for generating tissue image data with noise components removed from the reflected wave data of the harmonic component (received signal).

[0022] Furthermore, when performing harmonic imaging of CHI or THI, the B-mode processing circuit 12 can extract harmonic components by a method different from the method using the filter processing described above. In harmonic imaging, imaging methods called amplitude modulation (AM) method, phase modulation (PM) method, and AMPM method which combines the AM method and the PM method are performed. In the AM method, the PM method, and the AMPM method, ultrasonic transmissions with different amplitudes or phases are performed multiple times for the same scanning line. As a result, the transmission / reception circuit 11 generates and outputs a plurality of reflected wave data (received signals) for each scanning line. Then, the B-mode processing circuit 12 extracts harmonic components by performing addition and subtraction processing on the plurality of reflected wave data (received signals) of each scanning line according to the modulation method. Then, the B-mode processing circuit 12 performs envelope detection processing or the like on the reflected wave data (received signals) of the harmonic components to generate B-mode data.

[0023] For example, when the PM method is performed, the transmission / reception circuit 11 transmits ultrasonic waves with the same amplitude but with the phase polarity reversed, such as (-1, 1), twice for each scanning line according to the scan sequence set by the processing circuit 17. Then, the transmission / reception circuit 11 generates a received signal due to the transmission of "-1" and a received signal due to the transmission of "1", and the B-mode processing circuit 12 adds these two received signals. As a result, a signal is generated in which the fundamental wave component is removed and mainly the second harmonic component remains. Then, the B-mode processing circuit 12 performs envelope detection processing or the like on this signal to generate B-mode data of THI or B-mode data of CHI.

[0024] Alternatively, for example, in THI, a method of visualizing using the second harmonic component and the difference tone component included in the received signal has been put into practical use. In the visualization method using the difference tone component, for example, transmit ultrasonic waves of a composite waveform obtained by synthesizing a first fundamental wave with a center frequency of "f1" and a second fundamental wave with a center frequency of "f2" greater than "f1" are transmitted from the ultrasonic probe 20. This composite waveform is a waveform obtained by synthesizing the waveforms of the first fundamental wave and the second fundamental wave whose phases are adjusted so that a difference tone component having the same polarity as the second harmonic component is generated. The transmission / reception circuit 11 transmits the transmit ultrasonic waves of the composite waveform, for example, twice while inverting the phase. In such a case, for example, the B-mode processing circuit 12 adds the two received signals to remove the fundamental wave component, extracts the harmonic component mainly remaining the difference tone component and the second harmonic component, and then performs envelope detection processing or the like.

[0025] The Doppler processing circuit 13 frequency-analyzes the velocity information from the echo data from the reception circuit under the control of the processing circuit 17, and generates data (two-dimensional or three-dimensional data) in which movement information of a moving object such as average velocity, variance, power, etc. is extracted for multiple points. This data is generally called Doppler data. Here, the moving object is, for example, blood flow, tissue such as the heart wall, or a contrast agent. Note that the Doppler processing circuit 13 is an example of a Doppler processing unit.

[0026] The image generation circuit 14 generates an ultrasonic image represented by a predetermined luminance range as image data based on the echo signal received by the ultrasonic probe 20 under the control of the processing circuit 17. For example, the image generation circuit 14 generates a B-mode image representing the intensity of the reflected wave in luminance from the two-dimensional B-mode data generated by the B-mode processing circuit 12 as an ultrasonic image. Further, the image generation circuit 14 generates an average velocity image, a variance image, a power image, or a color Doppler image as a combined image of these, representing the movement state information from the two-dimensional Doppler data generated by the Doppler processing circuit 13 as an ultrasonic image. Note that the image generation circuit 14 is an example of an image generation unit.

[0027] Here, the image generation circuit 14 generally converts (scans and converts) the scanning line signal sequence of ultrasonic scanning into a scanning line signal sequence in a video format typified by a television or the like, and generates ultrasonic image data for display. Specifically, the image generation circuit 14 generates ultrasonic image data for display by performing coordinate conversion according to the ultrasonic scanning form by the ultrasonic probe 20. In addition to scan conversion, the image generation circuit 14 performs various image processes, for example, an image process (smoothing process) of regenerating an average value image of luminance using a plurality of image frames after scan conversion, and an image process (edge enhancement process) using a differential filter within the image. Further, the image generation circuit 14 synthesizes character information, scales, body marks, and the like of various parameters on the ultrasonic image data.

[0028] That is, the B-mode data and Doppler data are ultrasonic image data before the scan conversion process, and the data generated by the image generation circuit 14 is ultrasonic image data for display after the scan conversion process. Note that the B-mode data and Doppler data are also called raw data. The image generation circuit 14 generates two-dimensional ultrasonic image data for display from the two-dimensional ultrasonic image data before the scan conversion process.

[0029] Furthermore, the image generation circuit 14 generates three-dimensional B-mode image data by performing coordinate conversion on the three-dimensional B-mode data generated by the B-mode processing circuit 12. Also, the image generation circuit 14 generates three-dimensional Doppler image data by performing coordinate conversion on the three-dimensional Doppler data generated by the Doppler processing circuit 13. The image generation circuit 14 generates "three-dimensional B-mode image data and three-dimensional Doppler image data" as "three-dimensional ultrasonic image data (volume data)".

[0030] Then, the image generation circuit 14 performs a rendering process on the volume data in order to generate various two-dimensional image data for displaying the volume data stored in the three-dimensional memory on the display 40. As the rendering process, the image generation circuit 14 performs, for example, a process of generating MPR image data from the volume data by performing a multi-planar reconstruction (MPR) method. Further, as the rendering process, the image generation circuit 14 performs, for example, a volume rendering (VR) process of generating two-dimensional image data reflecting three-dimensional information.

[0031] The image memory 15 has, for example, a magnetic or optical recording medium, or a recording medium readable by a processor such as a semiconductor memory. The image memory 15 stores ultrasonic image data for a plurality of heartbeats associated with the heartbeat data, generated by the image generation circuit 14, under the control of the processing circuit 17. The plurality of ultrasonic image data stored in the image memory 15 are associated with the heartbeat data of the subject on a per heartbeat (one cardiac cycle) basis. Specifically, for example, each ultrasonic image data stored in the image memory 15 is associated with the heartbeat data corresponding to one heartbeat.

[0032] Note that the image memory 15 may store ultrasonic image data for one heartbeat as one image data, or may store ultrasonic image data for a plurality of heartbeats together as one image data. Further, the image memory 15 may store the ultrasonic image data generated by the image generation circuit 14 not only as two-dimensional data but also as volume data under the control of the processing circuit 17. Note that the image memory 15 is an example of the storage unit.

[0033] The network interface 16 implements various information communication protocols according to the form of the network. The network interface 16 connects the ultrasonic diagnostic apparatus 1 and other devices such as an external image management apparatus 60 and an image processing apparatus 70 in accordance with these various protocols. For this connection, an electrical connection via an electronic network or the like can be applied. Here, the electronic network means the entire information communication network using telecommunication technology, and includes, in addition to a wireless / wired hospital backbone LAN (Local Area Network) and the Internet, a telephone communication line network, an optical fiber communication network, a cable communication network, a satellite communication network, and the like.

[0034] Further, the network interface 16 may implement various protocols for non-contact wireless communication. In this case, the image processing apparatus 10 can directly transmit and receive data without going through a network, for example, with the ultrasonic probe 20. Note that the network interface 16 is an example of a network connection section.

[0035] The processing circuit 17 means a dedicated or general-purpose CPU (central processing unit), MPU (micro processor unit), or GPU (Graphics Processing Unit), as well as an ASIC and a programmable logic device or the like. Examples of the programmable logic device include a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA).

[0036] Further, the processing circuit 17 may be constituted by a single circuit or may be constituted by a combination of a plurality of independent circuit elements. In the latter case, the main memory 18 may be provided individually for each circuit element, or a single main memory 18 may store programs corresponding to the functions of a plurality of circuit elements. Note that the processing circuit 17 is an example of a processing unit.

[0037] The main memory 18 is constituted by a semiconductor memory element such as a RAM (random access memory) or a flash memory, a hard disk, an optical disk, etc. The main memory 18 may be constituted by a portable medium such as a USB (universal serial bus) memory and a DVD (digital video disk). The main memory 18 stores various processing programs (including an OS (operating system) in addition to application programs) used in the processing circuit 17 and data necessary for the execution of the programs. Further, the OS may include a GUI (graphical user interface) that makes extensive use of graphics for displaying information on the display 40 to the operator and enables basic operations to be performed by the input interface 30. Note that the main memory 18 is an example of a storage unit.

[0038] The ultrasonic probe 20 includes a plurality of minute vibrators (piezoelectric elements) on the front surface portion, and transmits and receives ultrasonic waves to and from a region including a scan target, for example, a region including a tubular cavity. Each vibrator is an electroacoustic conversion element, and has a function of converting an electric pulse into an ultrasonic pulse during transmission and converting a reflected wave into an electric signal (received signal) during reception. The ultrasonic probe 20 is configured to be small and lightweight, and is connected to the image processing apparatus 10 via a cable (or wireless communication).

[0039] The ultrasonic probe 20 is classified into types such as linear type, convex type, and sector type according to the difference in the scanning method. Further, the ultrasonic probe 20 is classified into a 1D array probe in which a plurality of vibrators are arranged one-dimensionally (1D) in the azimuth direction and a 2D array probe in which a plurality of vibrators are arranged two-dimensionally (2D) in the azimuth direction and the elevation direction according to the difference in the array dimension of the array. Note that the 1D array probe includes a probe in which a small number of vibrators are arranged in the elevation direction.

[0040] Here, when 3D scanning, that is, volume scanning, is performed, a 2D array probe having a scanning method such as a linear type, a convex type, and a sector type is used as the ultrasonic probe 20. Alternatively, when volume scanning is performed, a 1D probe having a scanning method such as a linear type, a convex type, and a sector type and having a mechanism that mechanically swings in the elevation direction is used as the ultrasonic probe 20. The latter probe is also called a mechanical 4D probe.

[0041] The input interface 30 includes an input device operable by an operator and an input circuit that inputs a signal from the input device. The input device is realized by a trackball, a switch, a mouse, a keyboard, a touch pad that performs an input operation by touching an operation surface, a touch screen in which a display screen and a touch pad are integrated, a non-contact input device using an optical sensor, a voice input device, and the like. When the input device is operated by the operator, the input circuit generates a signal corresponding to the operation and outputs it to the processing circuit 17. Note that the input interface 30 is an example of an input unit.

[0042] The display 40 is configured by a general display output device such as a liquid crystal display or an OLED (Organic Light Emitting Diode) display. The display 40 displays various information according to the control of the processing circuit 17. Note that the display 40 is an example of a display unit.

[0043] The biological signal sensor 50 detects biological signals from a subject to be ultrasonically scanned. The biological signal sensor 50 detects, as a biological signal, for example, an ECG (electrocardiogram waveform: Electrocardiogram) signal of the subject as an electrical signal. The biological signal sensor 50 performs various processes including digitization processing on the detected ECG signal, and then transmits it to the image processing apparatus 10 as heartbeat data. Note that the biological signal sensor 50 may detect, as a biological signal, in addition to / replace of the ECG, other signals having periodicity emitted from the subject such as electroencephalogram, pulse, and respiration.

[0044] Also, FIG. 1 shows an image management apparatus 60, which is an external device of the image processing apparatus 10, and an image processing apparatus 70. The image management apparatus 60 is, for example, a DICOM (Digital Imaging and Communications in Medicine) server, and is connected to devices such as an ultrasonic diagnostic apparatus 1 via a network N so as to enable data transmission and reception. The image management apparatus 60 manages medical images such as ultrasonic images generated by the ultrasonic diagnostic apparatus 1 as DICOM files.

[0045] The image processing apparatus 70 is connected to devices such as the ultrasonic diagnostic apparatus 1 and the image management apparatus 60 via the network N so as to enable data transmission and reception. Examples of the image processing apparatus 70 include a workstation that performs various image processes on ultrasonic images generated by the ultrasonic diagnostic apparatus 1, and a portable information processing terminal such as a tablet terminal. Note that the image processing apparatus 70 may be an offline device and may be a device capable of reading ultrasonic images generated by the ultrasonic diagnostic apparatus 1 via a portable storage medium.

[0046] Subsequently, the functions of the image processing apparatus 10 will be described.

[0047] FIG. 2 is a block diagram showing an example of the functions of the image processing apparatus 10.

[0048] The processing circuit 17 reads and executes a computer program (for example, an image processing program) stored in the main memory 18 or the memory within the processing circuit 17, thereby realizing an image acquisition function 171, a storage control function 172, a thumbnail generation function 173, a quantitative value acquisition function 174, a contour candidate acquisition function 175, and a contour determination function 176. Hereinafter, the case where the functions 171 to 176 are realized by a computer program will be described as an example, but all or part of the functions 171 to 176 may be provided as functions of a circuit such as an ASIC in the image processing apparatus 10.

[0049] Here, in the echocardiogram examination using an ultrasonic diagnostic apparatus, after the freeze operation of the displayed ultrasonic image, the operator manually selects the heartbeat considered to be optimal from a plurality of recent heartbeats, and various measurements and analyses are performed on the ultrasonic image corresponding to the selected heartbeat to obtain a quantitative value indicating the function of the heart. As a first method for obtaining a quantitative value indicating the function of the heart, there are 2D WMT (Wall Motion Tracking) and 3D WMT for performing myocardial wall motion analysis, Auto_EF (Automated Ejection Fraction) for automatically calculating the left ventricular ejection fraction, etc. Auto_EF performs pattern recognition by comparing the actual heart shape with features (heart appearance, left ventricular endocardium, etc.) registered in a pre-constructed database, searches for a heart having a similar pattern, detects (traces) the left ventricular endocardium, and calculates, as quantitative values for each heartbeat, the end-diastolic left ventricular volume (EDV), the end-systolic left ventricular volume (ESV), the left ventricular ejection fraction (EF), etc. According to the first method of measuring and analyzing ultrasonic images, since the contour is traced without the setting information of an operator such as a doctor, the trace result, and thus the quantitative value such as EF may be different from what the operator desires.

[0050] As a second method for obtaining a quantitative value indicating the function of the heart, there is a technique of generating a database by associating ultrasonic image data with a quantitative value in advance and obtaining a quantitative value corresponding to desired ultrasonic image data by referring to the database. For example, machine learning is used in the process of obtaining a quantitative value indicating the function of the heart. Further, as the machine learning, deep learning using a multi-layer neural network such as a convolutional neural network (CNN) or a convolutional deep belief network (CDBN) is used. According to the second method for measuring and analyzing an ultrasonic image, the obtained quantitative value may be different from the quantitative value based on the contour obtained from the same ultrasonic image. Further, according to the second method, since the ultrasonic image in which an ejection fraction such as EF is obtained does not remain as a basis, the operator cannot correct the tracing result of the contour to be performed on the ultrasonic image later (for example, before and after surgery).

[0051] Therefore, the processing circuit 17 realizes functions 171 to 176 described below.

[0052] The image acquisition function 171 includes a function of acquiring ultrasonic image data by ultrasonic scanning using the ultrasonic probe 20 by controlling the transmission / reception circuit 11, the B-mode processing circuit 12, the Doppler processing circuit 13, the image generation circuit 14, and the like. Specifically, the image acquisition function 171 acquires M-mode image data, B-mode image data, Doppler image data, etc. as ultrasonic image data. Further, the image acquisition function 171 includes a function of causing the image generation circuit 14 to live-display each piece of ultrasonic image data generated as an ultrasonic image on the display 40. Note that the image acquisition function 171 is an example of an image acquisition unit.

[0053] FIG. 3 is a diagram showing a display example of a B-mode image.

[0054] FIG. 3 shows a display screen including a B-mode image as an ultrasonic image. This display screen includes the B-mode image Bn (moving image data) of the n-th frame that is live-displayed. n is an integer of 1 or more. The B-mode image of the (n + 1)-th frame Bn+1 is superimposed on the B-mode image Bn of the n-th frame, and the display of the B-mode image is updated, whereby the B-mode image is live-displayed. Although not shown in the display screen, the display screen may include heartbeat data (for example, an electrocardiogram waveform).

[0055] Returning to the description of FIG. 2, the memory control function 172 includes a function of acquiring the heartbeat data output from the biological signal sensor 50 and sequentially storing (temporarily storing) a plurality of ultrasonic image data generated by the image generation circuit 14 in the image memory 15 in association with the heartbeat data. The memory control function 172 may sequentially store a plurality of ultrasonic image data in the image memory 15 and sequentially store the heartbeat data in another memory (not shown) in association with the plurality of ultrasonic image data. Further, the memory control function 172 may acquire heartbeat data regarding a plurality of heartbeats of the subject during the period in which a plurality of ultrasonic image data are acquired.

[0056] Further, the memory control function 172 includes a function of storing (secondarily storing) as moving image data in the image memory 15 a plurality of frames of ultrasonic image data corresponding to the ultrasonic image data of a specific frame related to the save instruction received by the input interface 30. Note that the memory control function 172 is an example of a memory control unit.

[0057] The thumbnail generation function 173 includes a function of generating thumbnail image data indicating a thumbnail of the ultrasonic image data of a specific frame related to the save instruction received by the input interface 30. Further, the thumbnail generation function 173 includes a function of displaying the thumbnail image data as a thumbnail image on the display 40. Note that the thumbnail generation function 173 is an example of a generation unit.

[0058] FIG. 4 is a diagram showing an example of display of a thumbnail image.

[0059] FIG. 4 shows a display screen including a thumbnail image. This display screen includes a B-mode image Bn of the nth frame that is live-displayed and a thumbnail image S showing a thumbnail of the saved B-mode image data.

[0060] In the display screen shown in FIG. 3, when the marker on the screen is aligned with the save button P and determined (clicked) by the input interface 30, the thumbnail generation function 173 causes a transition from the display screen shown in FIG. 3 to the display screen shown in FIG. 4.

[0061] Returning to the description of FIG. 2, the quantitative value acquisition function 174 includes a function of acquiring a quantitative value (e.g., XX%) indicating the function of an organ, such as the heart, and a function of acquiring a plurality of contour information candidates based on the quantitative value and superimposing the plurality of contour information candidates on the ultrasonic image data for display on the display 40. For example, the quantitative value acquisition function 174 acquires a quantitative value by a technique such as Auto_EF described above, or acquires a quantitative value by deep learning using the database or multi-layer neural network described above. Further, the quantitative value acquisition function 174 can also acquire a numerical value manually input from the input interface 30 as a quantitative value. In that case, the operator can input the quantitative value while referring to the moving image data related to the save instruction received by the input interface 30. Note that the quantitative value acquisition function 174 is an example of a quantitative value acquisition unit.

[0062] Also, the quantitative value acquisition function 174 can change the acquired quantitative value by changing the selected heartbeat or changing the frame of the selected end-diastole or end-systole. Thereby, the quantitative value can be changed without correcting the contour information described later.

[0063] The contour candidate acquisition function 175 includes a function of acquiring candidates for a plurality of contour information of the left ventricular endocardium of an organ (for example, the heart) based on the quantitative value acquired by the quantitative value acquisition function 174. The contour information includes the position, shape, etc. of the contour of the left ventricular endocardium. Further, when the acquisition process of the contour information candidates is completed, the contour candidate acquisition function 175 includes a function of causing the display 40 to display the processing result. Note that the contour candidate acquisition function 175 is an example of a contour candidate acquisition unit.

[0064] The contour determination function 176 includes a function of determining, from among the plurality of contour information candidates displayed by the contour candidate acquisition function 175, the one selected by the input interface 30 as the contour information corresponding to the moving image data according to the save instruction of the input interface 30. Note that the contour determination function 176 is an example of a contour determination unit.

[0065] Details of the functions 171 to 176 will be described with reference to FIGS. 5 to 9.

[0066] Next, the operation of the image processing apparatus 10 will be described.

[0067] FIG. 5 is a diagram showing an example of the operation of the image processing apparatus 10 as a flowchart. In FIG. 5, the symbols with numbers attached to “ST” indicate each step of the flowchart.

[0068] The image acquisition function 171 of the image processing apparatus 10, for example, after receiving examination order information from an examination request apparatus (not shown) such as HIS (Hospital Information Systems), receives an instruction to start an ultrasonic scan of an echocardiogram examination via the input interface 30. The image acquisition function 171 controls the transmission / reception circuit 11, the B-mode processing circuit 12, the Doppler processing circuit 13, the image generation circuit 14, etc., to start an ultrasonic scan using the ultrasonic probe 20 (step ST1). The image acquisition function 171 causes the B-mode image data of each frame including the heart, acquired in step ST1, to be live-displayed on the display 40 as a B-mode image (step ST2). An example of the display of the B-mode image is shown in FIG. 3.

[0069] The memory control function 172 receives, from the input interface 30, an instruction to save the B-mode image data of the frame displayed on the display 40 in step ST2 (step ST3). Generally, an instruction to save is received after the updated image of the B-mode image by live display is frozen from the input interface 30.

[0070] The memory control function 172 acquires, based on the save instruction received in step ST3, B-mode image data of a plurality of frames over a plurality of heartbeats immediately before the save instruction, and stores it as moving image data in the image memory 15 (step ST4). For example, in step ST4, the memory control function 172 acquires B-mode image data of a plurality of frames corresponding to four heartbeats immediately before the save instruction from the B-mode image data of a plurality of frames temporarily stored in the image memory 15 (or the main memory 18), and stores it secondarily in the image memory 15. The B-mode image data of a plurality of frames temporarily stored in the image memory 15 is associated with heartbeat data.

[0071] The thumbnail generation function 173 generates thumbnail image data indicating a thumbnail of the B-mode image data for which a save instruction was received in step ST3 (step ST5). The thumbnail generation function 173 causes the thumbnail image data generated in step ST5 to be displayed on the display 40 as a thumbnail image together with the live display of the B-mode image data (step ST6). An example of the display of the thumbnail image is shown in FIG. 4.

[0072] The quantitative value acquisition function 174 acquires a quantitative value (e.g., XX%) indicating the function of an organ, such as the heart (step ST7). For example, the quantitative value acquisition function 174 acquires the quantitative value by a technique such as Auto_EF described above, or acquires the quantitative value by deep learning using the database or multi-layer neural network described above. Further, the quantitative value acquisition function 174 can also acquire, as a quantitative value, a numerical value manually input from the input interface 30. In that case, the operator can input the quantitative value while referring to the moving image data related to the save instruction received by the input interface 30. Further, the quantitative value acquisition function 174 can also change the acquired quantitative value due to a change in the selected heartbeat or a change in the frame of the selected end-diastolic or end-systolic phase.

[0073] Based on the quantitative value acquired in step ST7, the contour candidate acquisition function 175 acquires a candidate for the contour information (step ST8).

[0074] In step ST8, for the acquisition process of the candidate for the left ventricular endocardial contour information based on the quantitative value acquired by the quantitative value acquisition function 174, the contour candidate acquisition function 175 may use, for example, a database associating the quantitative value and the contour information. Further, the contour candidate acquisition function 175 may use machine learning for the acquisition process of the candidate for the contour information based on the quantitative value by the quantitative value acquisition function 174. Further, as the machine learning, deep learning using a multi-layer neural network may be used.

[0075] Hereinafter, an example in which the contour candidate acquisition function 175 includes a neural network Na and uses deep learning to acquire a candidate for the left ventricular endocardial contour information from a quantitative value indicating the function of the heart will be shown.

[0076] FIG. 6 is an explanatory diagram showing an example of the data flow during learning.

[0077] The contour candidate acquisition function 175 sequentially updates the parameter data Pa by performing learning with a large number of training data inputs. The training data consists of a set of quantitative values (e.g., quantitative values indicating EF) S1, S2, S3,... indicating the function of the heart as training input data, and contour information T1, T2, T3,... of the endocardium of the heart (e.g., the left ventricular endocardium). The quantitative values S1, S2, S3,... constitute the training input data group Ba. The contour information T1, T2, T3,... constitutes the training output data group Ca.

[0078] Each time training data is input, the contour candidate acquisition function 175 performs so-called learning to update the parameter data Pa such that the result of processing the quantitative values S1, S2, S3,... by the neural network Na approaches the contour information T1, T2, T3,.... Generally, when the rate of change of the parameter data Pa converges within a threshold, the learning is determined to be complete. Hereinafter, the parameter data Pa after learning is particularly referred to as the learned parameter data Pa'.

[0079] Note that it should be noted that the types of training input data should be made to match the types of input data during operation shown in FIG. 7. For example, when the input data during operation is a quantitative value, the training input data group Ba during learning should also be a quantitative value.

[0080] FIG. 7 is an explanatory diagram showing an example of the data flow during operation.

[0081] During operation, the contour candidate acquisition function 175 inputs the quantitative value Sa indicating the function of the heart acquired in step ST7, and outputs the contour information Ta of the left ventricular endocardium using the learned parameter data Pa'.

[0082] Note that the neural network Na and the learned parameter data Pa' constitute the learned model 19a. The neural network Na is stored in the main memory 18 in the form of a program. The learned parameter data Pa' may be stored in the main memory 18 or may be stored in a storage medium connected to the ultrasonic diagnostic apparatus 1 via the network N. In this case, the contour candidate acquisition function 175 realized by the processor of the processing circuit 17 reads and executes the learned model 19a from the main memory 18 to generate contour information. Note that the learned model 19a may be constructed by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0083] Note that in order to improve the judgment accuracy of the contour candidate acquisition function 175, as supplementary information for the input data, in addition to the quantitative value, at least one of the height and weight of the imaging subject, image data including other modalities that have already been imaged, and representative model data of a gadget may be used.

[0084] In this case, during learning, the supplementary information of each subject of the quantitative values S1, S2, S3,... as training input data is also input to the neural network Na as training input data. During operation, the contour candidate acquisition function 175 inputs the supplementary information of the imaging subject together with the acquired quantitative value Ba to the learned model 19a read from the main memory 18 to output the contour information Ta. By using the quantitative value and the supplementary information of the imaging subject as the input data, it is possible to generate the learned parameter data Pa' that has been learned according to the type of the subject, so that the acquisition accuracy can be improved compared to the case where only the quantitative value is used as the input data.

[0085] The contour candidate acquisition function 175 uses deep learning using the above-described database or multi-layer neural network to acquire one or more pieces of contour information with high accuracy, and displays the contour information on the display 40 as candidates for the contour information. For example, the contour candidate acquisition function 175 acquires, as a candidate for the contour information, one piece of contour information with the highest accuracy based on the ultrasonic image. Alternatively, the contour candidate acquisition function 175 acquires a plurality of pieces of contour information with high accuracy as candidates for the contour information (illustrated in FIG. 8(A)). Alternatively, the contour candidate acquisition function 175 acquires one piece of contour information with the highest accuracy, acquires a plurality of pieces of contour information based on the contour information, and acquires them as candidates for the contour information (illustrated in FIG. 8(B)).

[0086] FIGS. 8 and 9 are diagrams showing examples of display screens showing candidates for the contour information. FIG. 8(A) shows a first display screen showing candidates for the contour information, and FIG. 8(B) shows a second display screen showing candidates for the contour information. FIG. 9 shows a third display screen showing candidates for the contour information. Note that the case where the number of candidates for the contour information is three will be described, but the present invention is not limited to this case. The number of candidates for the contour information may be two or more.

[0087] FIG. 8(A) shows a display screen in which three candidates for the contour information are superimposed on one piece of end-diastolic image data (or moving image data, or end-systolic image data) E when three pieces of contour information with high accuracy are acquired as candidates for the contour information (candidates 1 to 3) based on the ultrasonic image. As shown in FIG. 8(A), the three candidates for the contour information can be represented by different line types (solid line, broken line, thick line, etc.). Alternatively, the three candidates for the contour information can also be represented by different colors (hue, saturation, lightness). In addition, the displayed end-diastolic or end-systolic image data can be arbitrarily changed in frame.

[0088] FIG. 8(B) shows a display screen in which three contour information candidates (candidates 1 to 3), i.e., one contour information with the highest accuracy and two other contour information whose feature points match the contour information, are superimposed on one end-diastolic image data (or, moving image data, or end-systolic image data) E based on an ultrasonic image. For example, for at least one of the image data corresponding to the end-diastolic frame and the image data corresponding to the end-systolic frame among the moving image data saved by a save instruction, by fixing the valve annulus part and the apex as feature points and enlarging or reducing the contour as a whole, the other two contour information candidates are obtained and displayed. Or, for the said image data, by fixing the valve annulus part and the apex and enlarging or reducing a part of the contour, the other contour information candidates are obtained and displayed. Or, for the said image data, by moving the feature amounts such as the valve annulus part and the apex, the other two contour information candidates are obtained and displayed. Also, the end-diastolic or end-systolic image data to be displayed can be arbitrarily changed in frame.

[0089] FIG. 9 shows a display screen in which images in which one contour information candidate is superimposed on one end-diastolic image data (or, moving image data, or end-systolic image data) E are arranged in parallel when one contour information with the highest accuracy and two other contour information whose feature points match the contour information are obtained as contour information candidates (candidates 1 to 3) based on an ultrasonic image. Also, the end-diastolic or end-systolic image data to be displayed can be arbitrarily changed in frame.

[0090] Note that the contour candidate acquisition function 175 re-acquires and displays candidates for a plurality of contour information on the left ventricular endocardium in response to adjustment of quantitative values. Further, the contour candidate acquisition function 175 can preset the number of candidates for the contour information. Also, the contour candidate acquisition function 175 presets feature points such as the valve ring part and the apex part, and acquires candidates for the contour information so as to pass through the feature points, thereby narrowing down the options for the operator, and the operator can select the desired contour in a shorter time. Also, due to the limitation of the quantitative value and the feature points, there may be cases where the preset number of candidates for the contour information cannot be acquired. In that case, the contour candidate acquisition function 175 can display "Warning" on the display screen, recommend changing the quantitative value on the display screen, recommend changing (relaxing) the number of candidates for the set contour information on the display screen, or recommend changing (relaxing) the feature points on the display screen. In that case, the contour candidate acquisition function 175 can accept changes in the quantitative value, changes (relaxations) in the number of candidates for the set contour information, or changes (relaxations) in the feature points via the input interface 30.

[0091] The contour determination function 176 determines, as the contour information to be associated with the moving image data saved by the save instruction in step ST3, the contour information selected via the input interface 30 from among the candidates for the contour information displayed by the contour candidate acquisition function 175 (step ST9). Note that the contour determination function 176 can also adjust the contour information selected from the candidates for the contour information displayed by the contour candidate acquisition function 175 based on the input information from the input interface 73. For example, the contour candidate acquisition function 175 can adjust the contour information by adjusting the valve ring part or the apex part of the contour information shown in FIG. 8(B). Alternatively, the contour candidate acquisition function 175 can perform an adjustment to enlarge or reduce the contour information shown in FIG. 8(B) as a whole.

[0092] In the above description, an example in which the EF of the heart is adopted as a quantitative value indicating the function of the heart in each heartbeat has been described. However, the present invention can also be applied to quantitative values other than EF. For example, when the tissue is the heart, as a quantitative value indicating the function of the heart in each heartbeat, end-diastolic left ventricular volume (EDV), end-systolic left ventricular volume (ESV), left ventricular ejection fraction (EF), global longitudinal strain (GLS), right ventricular area change rate (FAC), etc. may be adopted. Further, when the tissue is a blood vessel, the quantitative value indicating the function of the blood vessel is, for example, the stenosis rate.

[0093] According to the image processing apparatus 10 according to the first embodiment, when a quantitative value such as EF is acquired using the Auto_EF function, by presenting candidates for contour information corresponding to the quantitative value to the operator, the operator can select the desired contour information from among them. As a result, it is possible to acquire the contour information corresponding to the quantitative value such as EF and desired by the operator. Further, according to the image processing apparatus 10 according to the first embodiment, when a quantitative value such as EF is acquired by manual input of the operator, by presenting candidates for contour information corresponding to the quantitative value to the operator, the operator can select the desired contour information from among them. As a result, it is possible to acquire the contour information corresponding to the quantitative value such as EF and desired by the operator.

[0094] (Second Embodiment) The image processing apparatus according to the second embodiment is provided separately from an ultrasonic diagnostic apparatus as a medical image diagnostic apparatus.

[0095] FIG. 10 is a schematic diagram showing an example of the configuration of a medical image system including the image processing apparatus according to the second embodiment.

[0096] FIG. 10 shows a medical image system S including an ultrasonic diagnostic apparatus 1 as a medical image diagnostic apparatus. The medical image system S includes the above-described ultrasonic diagnostic apparatus 1 and an image display apparatus as an image processing apparatus 70. The image processing apparatus 70 is a workstation that performs various image processes on image data, a portable information processing terminal such as a tablet terminal, etc., and is connected to the ultrasonic diagnostic apparatus 1 so as to be communicable via a network N.

[0097] The image processing apparatus 70 includes a processing circuit 71, a memory 72, an input interface 73, a display 74, and a network interface 75. The processing circuit 71, the memory 72, the input interface 73, the display 74, and the network interface 75 are each described as having the same configuration as the processing circuit 17, the main memory 18, the input interface 19, the display 40, and the network interface 16 shown in FIG. 1, and the description thereof is omitted.

[0098] FIG. 11 is a block diagram showing an example of the functions of the image processing apparatus 70.

[0099] The processing circuit 71 realizes an image acquisition function 171A, a contour candidate acquisition function 175, and a contour determination function 176 by reading and executing a computer program stored in the memory 72 or directly incorporated in the processing circuit 71. Hereinafter, the case where the functions 171A, 175, and 176 are realized by a computer program will be described as an example, but all or part of the functions 171A, 175, and 176 may be provided as functions of a circuit such as an ASIC in the image processing apparatus 70.

[0100] In FIG. 11, the same members as those shown in FIG. 2 are denoted by the same reference numerals and the description thereof is omitted.

[0101] The image acquisition function 171A includes a function of acquiring ultrasonic image data stored by the storage control function 172 of the ultrasonic diagnostic apparatus 1. Specifically, the image acquisition function 171A controls the network interface 75 to acquire moving image data stored by the storage control function 172 of the ultrasonic diagnostic apparatus 1 from the ultrasonic diagnostic apparatus 1 or the image management apparatus 60 via the network N. Note that the image acquisition function 171A is an example of an image acquisition unit.

[0102] Subsequently, the operation of the image processing apparatus 70 will be described.

[0103] FIG. 12 is a diagram showing an example of the operation of the image processing apparatus 70 as a flowchart. In FIG. 12, the symbols with numbers attached to "ST" indicate each step of the flowchart. In FIG. 12, the same steps as those in FIG. 5 are denoted by the same reference numerals and the description thereof is omitted.

[0104] The image acquisition function 171A of the image processing apparatus 70 controls the network interface 75 to acquire moving image data stored by the storage control function 172 of the ultrasonic diagnostic apparatus 1 from the ultrasonic diagnostic apparatus 1 or the image management apparatus 60 via the network N (step ST11).

[0105] According to the image processing apparatus 70 according to the second embodiment, when a quantitative value such as EF is acquired using the Auto_EF function, by presenting candidates for contour information corresponding to the quantitative value to the operator, the operator can select desired contour information therefrom. As a result, it is possible to acquire contour information corresponding to a quantitative value such as EF and desired by the operator. Further, according to the image processing apparatus 70 according to the second embodiment, when a quantitative value such as EF is acquired by manual input of the operator, by presenting candidates for contour information corresponding to the quantitative value to the operator, the operator can select desired contour information therefrom. As a result, it is possible to acquire contour information corresponding to a quantitative value such as EF and desired by the operator.

[0106] According to at least one embodiment described above, a plurality of contour information corresponding to a quantitative value indicating the function of the tissue can be presented to the operator.

[0107] Note that the image acquisition functions 171 and 171A are examples of an image acquisition unit. The memory control function 172 is an example of a memory control unit. The thumbnail generation function 173 is an example of a thumbnail generation unit. The quantitative value acquisition function 174 is an example of a quantitative value acquisition unit. The contour candidate acquisition function 175 is an example of a contour candidate unit. The contour determination function 176 is an example of a contour determination unit.

[0108] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, changes, combinations of embodiments, and combinations of an embodiment and one or more modifications can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention and are included in the invention described in the claims and the equivalent scope thereof.

Description of Reference Numerals

[0109] 1 Ultrasonic diagnostic apparatus 10, 70 Image processing apparatus 17, 71 Processing circuit 40, 74 Display 171, 171A Image acquisition function 172 Memory control function 173 Thumbnail generation function 174 Quantitative value acquisition function 175 Contour candidate acquisition function 176 Contour determination function S Image processing system

Claims

1. An image acquisition unit that acquires ultrasonic image data representing the heart of a subject by ultrasonic scanning, A contour candidate acquisition unit that acquires a plurality of contour information candidates corresponding to quantitative values indicating the function of the heart manually input via an input interface, and superimposes the plurality of contour information candidates on the heart of the subject represented by the ultrasonic image data and displays them on a display unit; A contour determination unit that determines the contour information of the heart of the subject corresponding to the quantitative value indicating the function of the heart manually input, which is associated with the ultrasonic image data, in response to an operation of selecting one contour information from the plurality of contour information candidates displayed on the display unit; An ultrasonic diagnostic apparatus having the above.

2. The contour candidate acquisition unit acquires the plurality of contour information candidates for the left ventricular endocardium of the heart based on the quantitative value manually input via the input interface. The ultrasonic diagnostic apparatus according to Claim 1.

3. The contour candidate acquisition unit acquires the plurality of contour information candidates in the left ventricular endocardium in response to adjustment of the quantitative value. The ultrasonic diagnostic apparatus according to Claim 2.

4. The contour candidate acquisition unit presets the number of the plurality of contour information candidates. The ultrasonic diagnostic apparatus according to any one of Claims 1 to 3.

5. The contour candidate acquisition unit presets feature points, and acquires the plurality of contour information candidates so as to pass through the feature points. The ultrasonic diagnostic apparatus according to Claim 4.

6. The feature point is at least one of an apex and an annulus. The ultrasonic diagnostic apparatus according to Claim 5.

7. When a preset number of contour information candidates cannot be acquired due to the limitation of the quantitative value and the feature point, the contour candidate acquisition unit displays "Warning" on the display screen, recommends changing the quantitative value on the display screen, recommends changing the number of the contour information candidates on the display screen, or recommends changing the feature point on the display screen. The ultrasonic diagnostic apparatus according to Claim 6.

8. The contour candidate acquisition unit inputs, via the input interface, a quantitative value indicating the function of the heart manually input to a learned model that outputs a plurality of contour information candidates corresponding to the quantitative value by inputting the quantitative value indicating the function of the heart, and acquires the plurality of contour information candidates corresponding to the quantitative value from the learned model. The ultrasonic diagnostic apparatus according to Claim 1.

9. An image acquisition unit that acquires ultrasonic image data representing the heart of a subject by ultrasonic scanning; A contour candidate acquisition unit that acquires a plurality of contour information candidates corresponding to quantitative values indicating the functions of the heart manually input via an input interface, and superimposes and displays the plurality of contour information candidates on the heart of the subject represented by the ultrasonic image data on a display unit; A contour determination unit that determines the contour information of the heart of the subject, which is associated with the ultrasonic image data and corresponds to the quantitative value indicating the function of the heart manually input, in response to an operation of selecting one piece of contour information from the plurality of contour information candidates displayed on the display unit; An image processing apparatus having the above.

10. A computer, A function of acquiring ultrasonic image data representing the heart of a subject by ultrasonic scanning; A function of acquiring a plurality of contour information candidates corresponding to quantitative values indicating the functions of the heart manually input via an input interface, and superimposing and displaying the plurality of contour information candidates on the heart of the subject represented by the ultrasonic image data on a display unit; A function of determining the contour information of the heart of the subject, which is associated with the ultrasonic image data and corresponds to the quantitative value indicating the function of the heart manually input, in response to an operation of selecting one piece of contour information from the plurality of contour information candidates displayed on the display unit; An image processing program for realizing the above.

Images