Medical image processor, medical image processing method and program, and image diagnosis system

Abstract

To provide a medical image processor capable of intuitively determining, respective values of three or more kinds of image quality parameters in medical images, in a short time, a medical image processing method and program, and an image diagnosis system.SOLUTION: A medical image processor performs processing of two-dimensionally arranging multiple candidate images obtained by subjecting medical imaging data to image processing by combining multiple candidate values of different kinds of one image quality parameter and multiple candidate values of different kinds of the other image quality parameter in a selectable state, and determining at least one of the candidate values of the kind of one image quality parameter corresponding to the selected candidate image and candidate values of the kind of the other image quality parameter, as a set value of the kind of the image quality parameter, in higher priority order among three or more kinds of the image quality parameter.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a medical image processing apparatus, a medical image processing method and program, and an image diagnostic system, and more particularly to a technique for determining the values ​​of image quality parameters of a medical image. [Background technology]

[0002] In MRI (Magnetic Resonance Imaging) image processing devices, users adjust image quality by performing image processing after capturing an image. The parameters for such image quality adjustment need to be changed for each patient and each disease.

[0003] An example of a parameter for adjusting image quality is the strength of denoising. In addition to the strength of denoising, there is also a desire for users to select their preferred image quality, but since there are so many types of parameters for creating the desired image quality, it is difficult to adjust the values ​​of the parameter types in a short period of time.

[0004] As a conventional technique, a technique is known in which images are displayed in which the values ​​of two parameter types are changed, and the user can select while viewing the images (see Patent Documents 1, 2, and 3). Also, a technique is known in which, for three or more parameter types, a preferred parameter value is extracted in advance by using past images (see Patent Document 4). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2003-284705 A [Patent Document 2] Japanese Patent Application Publication No. 2-260073 [Patent Document 3] JP 2019-188031 A [Patent Document 4] JP 2002-183725 A Summary of the Invention [Problem to be solved by the invention]

[0006] However, there is no description of a method for selecting values ​​of three or more types of parameters in Patent Documents 1 to 3. As described above, since there are a wide variety of types of parameters, particularly in MRI images, there is a problem that the techniques described in Patent Documents 1 to 3 are difficult to deal with.

[0007] Furthermore, Patent Document 4 does not describe a method for adjusting parameter values ​​while viewing a newly captured image. Therefore, there is a problem in that it is difficult to handle images of rare cases that are not available in past images.

[0008] The present invention has been made in consideration of the above circumstances, and aims to provide a medical image processing device, a medical image processing method and program, and an image diagnostic system that can intuitively determine the values ​​of each of three or more types of image quality parameters of a medical image in a short period of time. [Means for solving the problem]

[0009] In order to achieve the above object, a medical image processing apparatus according to a first aspect of the present disclosure includes at least one processor and at least one memory that stores instructions to be executed by the processor, the processor acquires medical imaging data, and for a parameter type set of two image quality parameter types among three or more image quality parameter types related to image quality of a medical image generated from the medical imaging data, causes a display device to display preview images in which a plurality of candidate images are obtained by image processing the medical imaging data by combining a plurality of different candidate values ​​of one image quality parameter type with a plurality of different candidate values ​​of the other image quality parameter type, the preview images being arranged two-dimensionally with one image quality parameter type on one axis and the other image quality parameter type on the other axis, a first image quality parameter type set including a first image quality parameter type having the first priority and a second image quality parameter type having the second priority, and a second parameter type set including a second image quality parameter type having the second priority, the first parameter type set being a first parameter type set including a first image quality parameter type having the first priority and a second image quality parameter type having the second priority, the medical image processing device applying the setting values ​​of the three or more image quality parameter types to image process the medical imaging data and generate a medical image.

[0010] A medical image processing device according to a second aspect of the present disclosure is a medical image processing device according to the first aspect, wherein the processor determines a setting value of a first image quality parameter type and a setting value of a second image quality parameter type for a first parameter type set, and the second parameter type set preferably includes a third image quality parameter type having third priority and a fourth image quality parameter type having fourth priority.

[0011] A medical image processing device according to a third aspect of the present disclosure is preferably a medical image processing device according to the first aspect, wherein the processor determines a setting value of a first image quality parameter type for a first parameter type set, and the second parameter type set includes a second image quality parameter type and a third image quality parameter type having third priority.

[0012] A medical image processing device according to a fourth aspect of the present disclosure is preferably a medical image processing device according to the third aspect, wherein the range of candidate values ​​of the second image quality parameter type of the second parameter type set is relatively narrower than the range of candidate values ​​of the second image quality parameter type of the first parameter type set, and includes a setting value of the second image quality parameter type of the first parameter type set.

[0013] A medical image processing device according to a fifth aspect of the present disclosure is a medical image processing device according to any of the first to fourth aspects, and is provided with a memory unit that retains previously determined setting values ​​of three or more image quality parameter types, and it is preferable that the processor, in the preview image, relatively emphasizes a first candidate image corresponding to a combination of the previously determined setting value of one image quality parameter type and the previously determined setting value of the other image quality parameter type, compared to a second candidate image different from the first candidate image.

[0014] In a medical image processing device according to a sixth aspect of the present disclosure, in a medical image processing device according to any of the first to fifth aspects, it is preferable that the processor acquires an imaging portion of the medical imaging data and acquires three or more types of image quality parameters according to the imaging portion.

[0015] In a medical image processing device according to a seventh aspect of the present disclosure, in a medical image processing device according to any of the first to sixth aspects, it is preferable that a higher priority is given to types of image quality parameters having a relatively larger variation in previously determined setting values.

[0016] A medical image processing device according to an eighth aspect of the present disclosure is a medical image processing device according to the first aspect or any of the fifth to seventh aspects, wherein the first parameter type set further includes a third image quality parameter type having third priority, and the processor displays on the display device a first preview image in which a plurality of candidate images of the first candidate value of the third image quality parameter type are arranged in two dimensions among a plurality of candidate images obtained by image processing of medical imaging data by combining a plurality of different candidate values ​​of the first image quality parameter type, a plurality of different candidate values ​​of the second image quality parameter type, and a plurality of different candidate values ​​of the third image quality parameter type, accepts a switching operation for switching the candidate value of the third image quality parameter type, displays a second preview image in which a plurality of candidate images of a second candidate value different from the first candidate value of the third image quality parameter type are arranged in two dimensions in response to the switching operation, accepts a selection operation of one candidate image from the first preview image or the second preview image, and determines at least the candidate value of the first image quality parameter type corresponding to the selected candidate image as the setting value of the first image quality parameter type.

[0017] A medical image processing device according to a 9th aspect of the present disclosure is preferably a medical image processing device according to the 8th aspect, wherein the processor determines a candidate value of the second image quality parameter type corresponding to the selected candidate image as a setting value of the second image quality parameter type, and determines a candidate value of the third image quality parameter type corresponding to the selected candidate image as a setting value of the third image quality parameter type.

[0018] A medical image processing device according to a tenth aspect of the present disclosure is preferably a medical image processing device according to any one of the first to ninth aspects, in which the candidate images are three-dimensional images, and the processor displays a third preview image in which slice images at a first slice position of each of the multiple candidate images are arranged in two dimensions, accepts a switching operation for switching the slice positions of the multiple candidate images, displays a fourth preview image in which slice images at a second slice position different from the first slice position are arranged in two dimensions in response to the switching operation, and accepts a selection operation of one candidate image from the third preview image or the fourth preview image.

[0019] In a medical image processing device according to an eleventh aspect of the present disclosure, in a medical image processing device according to any of the first to tenth aspects, it is preferable that the processor applies the setting values ​​determined for the first parameter type set to image process the medical imaging data to generate a plurality of candidate images for the second parameter type set.

[0020] In order to achieve the above-mentioned object, an image diagnostic system according to a 12th aspect of the present disclosure is an image diagnostic system including a medical image processing device according to any one of the first to 11th aspects, an image diagnostic device that captures medical imaging data, a display device, and an input device for a user to select one candidate image from preview images.

[0021] In an imaging diagnostic system according to a thirteenth aspect of the present disclosure, in the imaging diagnostic system according to the twelfth aspect, it is preferable that the imaging diagnostic device is an MRI (Magnetic Resonance Imaging) device.

[0022] In order to achieve the above object, a medical image processing method according to a fourteenth aspect of the present disclosure includes at least one processor acquiring medical imaging data, and for a parameter type set of two image quality parameter types among three or more image quality parameter types related to the image quality of a medical image generated from the medical imaging data, displaying on a display device a preview image in which a plurality of candidate images are obtained by image processing the medical imaging data by combining a plurality of different candidate values ​​of one image quality parameter type with a plurality of different candidate values ​​of the other image quality parameter type, the preview image being two-dimensionally arranged with one image quality parameter type on one axis and the other image quality parameter type on the other axis, and accepting an operation to select one candidate image from the preview image. a medical image processing method for determining at least one of a candidate value of one image quality parameter type and a candidate value of the other image quality parameter type corresponding to a selected candidate image as a setting value for the image quality parameter type, wherein three or more image quality parameter types are each assigned a priority order, and after determining a setting value for a first parameter type set including a first image quality parameter type having the first priority and a second image quality parameter type having the second priority, a setting value is determined for a second parameter type set different from the first parameter type set, and the setting values ​​of the three or more image quality parameter types are applied to image process the medical imaging data to generate a medical image.

[0023] In order to achieve the above object, a program according to a fifteenth aspect of the present disclosure is a program for causing a computer to execute the medical image processing method according to the fourteenth aspect. A non-transitory computer-readable recording medium such as a CD-ROM (Compact Disk-Read Only Memory) storing the program according to the fifteenth aspect is also included in the present disclosure. Effect of the Invention

[0024] According to the present invention, the values ​​of three or more types of image quality parameters of a medical image can be intuitively determined in a short time. [Brief description of the drawings]

[0025] [Figure 1] FIG. 1 is a diagram showing the overall configuration of an image diagnostic system. [Diagram 2] FIG. 2 is a block diagram showing the functional configuration of the medical image processing apparatus. [Diagram 3] FIG. 3 is a flow chart showing steps of a medical image processing method. [Figure 4] FIG. 4 is a diagram showing an example of a preview image. [Diagram 5] FIG. 5 is a diagram showing another example of the preview image. [Figure 6] FIG. 6 is a diagram showing an example of a preview image. [Figure 7] FIG. 7 is a diagram showing an example of a preview image. [Figure 8] FIG. 8 is a flow chart showing steps of a medical image processing method. [Figure 9] FIG. 9 is a diagram showing an example of a preview image. [Figure 10] FIG. 10 is a diagram showing an example of a preview image. [Figure 11] FIG. 11 is a diagram showing an example of a preview image. [Figure 12] FIG. 12 is a diagram showing an example of a preview image. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026] Hereinafter, preferred embodiments of a medical image processing apparatus, a medical image processing method and program, and an image diagnostic system according to the present disclosure will be described with reference to the accompanying drawings.

[0027] <Imaging diagnostic system> 1 is an overall configuration diagram of an image diagnostic system 10. As shown in FIG. 1, the image diagnostic system 10 includes an image diagnostic apparatus 20 and an information processing apparatus 30.

[0028] The image diagnostic apparatus 20 and the information processing apparatus 30 are connected to each other so as to be able to transmit and receive data via a network 22. The network 22 includes a wired or wireless LAN (Local Area Network) that communicatively connects various devices in a medical institution. The network 22 may also include a WAN (Wide Area Network) that connects the LANs of multiple medical institutions.

[0029] The image diagnostic apparatus 20 includes an imaging device that captures an image of an imaging region, which is a region to be examined of a patient, and outputs medical imaging data. The image diagnostic apparatus 20 includes, for example, a computed tomography (CT) device, a magnetic resonance imaging (MRI) device, and a positron emission tomography (PET) device.

[0030] The information processing device 30 includes a medical image processing device 40, an input device 50, and a display device 60. The medical image processing device 40, the input device 50, and the display device 60 are connected to each other so as to be able to transmit and receive data.

[0031] The medical image processing device 40 is a device that generates a medical image by performing image processing with desired image quality parameters on the medical imaging data acquired from the image diagnostic device 20. The medical image is, for example, a three-dimensional reconstructed image obtained by reconstructing the medical imaging data. Note that the term "image" in this specification includes not only the image itself such as a photograph, but also image data, which is a signal representing an image.

[0032] A personal computer or a workstation (an example of a "computer") is applied as the medical image processing device 40. The medical image processing device 40 includes a processor 42, a memory 44, an input / output interface 46, and a communication interface 48.

[0033] The processor 42 executes instructions stored in the memory 44. The hardware structure of the processor 42 is various processors as shown below. The various processors include a CPU (Central Processing Unit), which is a general-purpose processor that executes software (programs) and acts as various functional units, a GPU (Graphics Processing Unit), which is a processor specialized for image processing, a PLD (Programmable Logic Device), which is a processor whose circuit configuration can be changed after manufacture such as an FPGA (Field Programmable Gate Array), and a dedicated electric circuit, which is a processor having a circuit configuration designed specifically for executing specific processing such as an ASIC (Application Specific Integrated Circuit).

[0034] A processing unit may be configured with one of these various processors, or may be configured with two or more processors of the same or different types (for example, multiple FPGAs, or a combination of a CPU and an FPGA, or a combination of a CPU and a GPU). Also, multiple functional units may be configured with one processor. As an example of configuring multiple functional units with one processor, first, as represented by a computer such as a client or a server, there is a form in which one processor is configured with a combination of one or more CPUs and software, and this processor acts as multiple functional units. Second, as represented by a SoC (System On Chip), there is a form in which a processor is used that realizes the functions of the entire system including multiple functional units with one IC (Integrated Circuit) chip. In this way, the various functional units are configured using one or more of the above various processors as a hardware structure.

[0035] Furthermore, the hardware structure of these various processors is, more specifically, an electric circuit that combines circuit elements such as semiconductor elements.

[0036] The memory 44 stores instructions to be executed by the processor 42. The memory 44 includes a RAM (Random Access Memory) and a ROM (Read Only Memory), not shown. The processor 42 uses the RAM as a working area, executes software using various programs including a medical image processing program stored in the ROM, and executes various processes of the medical image processing device 40 by using parameters stored in the ROM, etc.

[0037] The input / output interface 46 controls input from an input device 50 and output to a display device 60 .

[0038] The communication interface 48 controls communication with the image diagnostic apparatus 20 via the network 22 in accordance with a predetermined protocol.

[0039] The medical image processing device 40 may be included in the image diagnostic device 20. The medical image processing device 40 may be a cloud server accessible from a plurality of medical institutions via the Internet. The processing performed by the medical image processing device 40 may be a cloud service with a fee-based or fixed-fee system.

[0040] The input device 50 includes a mouse (not shown) and a keyboard (not shown). A user inputs instructions to the medical image processing apparatus 40 using the input device 50.

[0041] The display device 60 includes a liquid crystal display, an organic EL (Electro Luminescence) display, a plasma display, or a projector. The display device 60 displays medical images and the like in accordance with instructions from the medical image processing device 40.

[0042] The information processing device 30 may include a touch panel display in which the input device 50 and the display device 60 are integrated.

[0043] [Functional configuration of medical image processing device] Fig. 2 is a block diagram showing the functional configuration of the medical image processing device 40. Each function of the medical image processing device 40 is realized by the processor 42 executing a medical image processing program stored in the memory 44. As shown in Fig. 2, the medical image processing device 40 includes a medical imaging data acquisition unit 70, a preview image generation unit 72, a preview image display unit 74, a selection operation acceptance unit 76, an image quality parameter value determination unit 78, and a final image generation unit 80.

[0044] The medical imaging data acquisition unit 70 acquires medical imaging data from the image diagnostic apparatus 20 via the network 22. The medical imaging data includes, for example, magnetic resonance data captured by an MRI apparatus and projection data captured by a CT apparatus.

[0045] The preview image generator 72 generates a preview image for determining setting values ​​of types of image quality parameters that relate to the image quality of a medical image generated from medical imaging data and are post-processing parameters to be applied to the medical imaging data.

[0046] The types of image quality parameters include "S / N ratio (denoising strength)", "edge enhancement strength", "contrast", and "spatial resolution". The types of image quality parameters may include "Truncation", "Shading", "Mode", "Correction", "Strength", "T2 correct.", "Adaptive Filter", "Edge Enhance", "DLR Level", "MIP Image", "DCLevel", "Region Cut", "W-Width1", and "W-Level1". The types of image quality parameters are stored in memory 44.

[0047] The preview image generating unit 72 prepares a plurality of different candidate values ​​for one image quality parameter type and a plurality of different candidate values ​​for the other image quality parameter type for a parameter type set including two image quality parameter types among the three or more image quality parameter types, and performs image processing on the medical imaging data by combining the plurality of candidate values ​​for both image quality parameter types to generate a plurality of candidate images. Furthermore, the preview image generating unit 72 generates a preview image arranged two-dimensionally with one image quality parameter on one axis and the other image quality parameter on the other axis.

[0048] Preview image display unit 74 displays the preview images generated by preview image generation unit 72 on display device 60 so that the user can select one candidate image. The user can select one candidate image from the preview images using input device 50. Selection operation receiving unit 76 receives a selection operation of one candidate image from input device 50.

[0049] Image quality parameter value determination section 78 determines at least one of the candidate value for one image quality parameter type corresponding to the selected candidate image and the candidate value for the other image quality parameter type as the setting value for that image quality parameter type. Image quality parameter value determination section 78 may store the determined setting value for the image quality parameter type in memory 44.

[0050] The final image generating unit 80 applies the set values ​​of the three or more types of image quality parameters to the medical imaging data to generate a medical image, which is a final image. The final image generating unit 80 may display the generated final image on the display device 60, or may store the generated final image in a medical image database (not shown).

[0051] [Medical image processing method: First embodiment] 3 is a flowchart showing steps of a medical image processing method according to the first embodiment performed by the medical image processing device 40. The medical image processing method is a method for allowing a user such as a doctor to determine the setting values ​​of three or more types of image quality parameters in a short period of time. The medical image processing method is realized by the processor 42 executing a medical image processing program stored in the memory 44. The medical image processing program may be provided by a computer-readable non-transitory storage medium, or may be provided via the Internet.

[0052] In step S1, the user specifies an imaging region using the input device 50. The imaging region includes, for example, at least one of a "head", a "abdomen", and a "joint".

[0053] In step S2, the user uses input device 50 to select three or more important types of image quality parameters from the types of image quality parameters stored in memory 44, and assigns unique priorities to each of the selected types of image quality parameters.

[0054] For example, if the imaging area is the "head" and the user wishes to diagnose the fine tissue structures within the brain, the user may prioritize "spatial resolution" as the first priority, "S / N ratio (denoise intensity)" as the second priority, "edge enhancement intensity" as the third priority, and "contrast" as the fourth priority.

[0055] In addition, if the imaging area is the "abdomen" and the user wishes to clearly see the difference between the diseased area and normal tissue during a liver contrast examination, the user may prioritize "contrast" as the first priority, "edge enhancement intensity" as the second priority, "S / N ratio (denoise intensity)" as the third priority, and "spatial resolution" as the fourth priority.

[0056] Furthermore, if the imaging area is a "joint" and the user wishes to accurately measure dimensions such as the thickness of the cartilage of the knee joint, the user may prioritize "spatial resolution" as the first priority, "edge enhancement intensity" as the second priority, "S / N ratio (denoise intensity)" as the third priority, and "contrast" as the fourth priority.

[0057] Here, four types of image quality parameters are selected for each imaging region, but the user may select at least three types of image quality parameters and assign priorities to them. Also, the user may select five or more types of image quality parameters and assign priorities to them.

[0058] The medical image processing apparatus 40 may store in the memory 44 the types of image quality parameters corresponding to the imaging region selected in step S2 and their respective priorities.

[0059] The medical image processing device 40 may store in advance the priority order according to the imaging part in the memory 44, etc. In this case, in step S2, the medical image processing device 40 may read out the priority order according to the imaging part designated in step S1.

[0060] Next, the medical imaging data acquisition unit 70 acquires medical imaging data of the imaging region designated in step S1. The preview image generation unit 72 generates a preview image of the first parameter type set.

[0061] Furthermore, in step S3, the preview image display unit 74 causes the display device 60 to display a preview image of the first parameter type set. Fig. 4 is a diagram showing an example of the preview image displayed on the display device 60. F4A in Fig. 4 shows the preview image IPA1 displayed in step S3.

[0062] The first parameter type set includes a first image quality parameter type having the first priority among three or more image quality parameter types acquired according to the imaging region, and a second image quality parameter type having the second priority. If the imaging region is the "head", the first image quality parameter type is "spatial resolution" and the second image quality parameter type is "S / N ratio (denoise intensity)".

[0063] The first image quality parameter type has candidate values ​​which are different values ​​of a plurality of first image quality parameters, and the second image quality parameter type has candidate values ​​which are different values ​​of a plurality of second image quality parameters. Here, the first image quality parameter type has three candidate values ​​P1A, P1B, and P1C, and the second image quality parameter type has three candidate values ​​P2A, P2B, and P2C. Note that the candidate values ​​are not limited to numerical values, and may include the presence or absence of a selection as to whether or not to use the image quality parameter in image processing.

[0064] The preview image generating unit 72 performs image processing on the medical imaging data for each combination of each candidate value of the first image quality parameter type and each candidate value of the second image quality parameter type, i.e., nine combinations of P1A×P2A, P1A×P2B, P1A×P2C, P1B×P2A, P1B×P2B, P1B×P2C, P1C×P2A, P1C×P2B, and P1C×P2C, to generate nine candidate images ICA1 11 , ICA1 12 , ICA1 13 , ICA1 21 , ICA1 22 , ICA1 23 , ICA1 31 , ICA1 32 , ICA1 33 Generate.

[0065] It should be noted that preview image generating section 72 may perform image processing using predetermined fixed values ​​for image quality parameter types other than the first image quality parameter type and the second image quality parameter type.

[0066] Furthermore, the preview image generating unit 72 generates nine candidate images ICA1 11 , ICA1 12 , ICA1 13 , ICA1 21 , ICA1 22 , ICA1 23 , ICA1 31 , ICA1 32 , ICA1 33A preview image IPA1 is generated by arranging the first image quality parameter type on the vertical axis and the second image quality parameter type on the horizontal axis in two dimensions. Candidate image ICA1 11 , ICA1 12 , ICA1 13 , ICA1 21 , ICA1 22 , ICA1 23 , ICA1 31 , ICA1 32 , ICA1 33 When the images are three-dimensional, the preview image generating section 72 may arrange slice images having the same orientation and the same slice position two-dimensionally.

[0067] In the example shown in F4A, the candidate images ICA1 are arranged in the top row of the preview image IPA1 in order from the left. 31 , ICA1 32 , ICA1 33 The candidate images ICA1, ICA2, ICA3, ICA4, ICA5, ICA6, ICA7, ICA8, ICA9, ICA10, ICA111, ICA121, ICA131, ICA141, ICA142, ICA151, ICA152, ICA161, ICA162, ICA171, ICA172, ICA183, ICA191, ICA192, ICA193, ICA194, ICA195, ICA196, ICA197, ICA198, ICA199, ICA201, ICA202, ICA203, ICA204, ICA205, ICA206, ICA207, ICA208, ICA2109, ICA2111, ICA212, ICA213, ICA214, ICA215 31 , ICA1 21 , ICA1 11 are images whose first image quality parameter type values ​​are candidate values ​​P1C, P1B, and P1A, and whose second image quality parameter type values ​​are candidate value P2A.

[0068] The preview image may display the values ​​of the image quality parameters of each candidate image. Fig. 5 is a diagram showing another example of the preview image IPA1. The preview image IPA1 shown in Fig. 5 displays nine candidate images ICA1 11 , ICA1 12 , ICA1 13 , ICA1 21 , ICA1 22 , ICA1 23 , ICA1 31 , ICA1 32 , ICA1 33In each corner of the candidate image ICA1, the value of the first image quality parameter and the value of the second image quality parameter type are displayed. 31 In the corner of the image, the candidate image ICA1 31 The text "P1C / P2A" is displayed, indicating that the value of the first image quality parameter type is candidate value P1C, and the value of the second image quality parameter type is candidate value P2A.

[0069] Returning to the description of FIG. 3, in step S4, the user uses the input device 50 to input nine candidate images ICA1 of the preview image IPA1. 11 , ICA1 12 , ICA1 13 , ICA1 21 , ICA1 22 , ICA1 23 , ICA1 31 , ICA1 32 , ICA1 33 The selection operation receiving unit 76 receives a selection operation for the candidate image.

[0070] Image quality parameter value determination section 78 determines the candidate value of the first image quality parameter type corresponding to the candidate image selected in step S4 as the setting value for the first image quality parameter type. Also, image quality parameter value determination section 78 determines the candidate value of the second image quality parameter type corresponding to the candidate image selected in step S4 as the setting value for the second image quality parameter type. For example, if the selected candidate image is candidate image ICA1 11 If so, the setting value of the type of the first image quality parameter is determined to be P1A, and the setting value of the type of the second image quality parameter is determined to be P2A. 23 If so, the setting value of the first image quality parameter type is determined to be P1B, and the setting value of the second image quality parameter type is determined to be P2C.

[0071] Next, the preview image generating unit 72 generates a preview image of the second parameter type set. In step S5, the preview image display unit 74 displays the preview image of the second parameter type set on the display device 60. F4B in Fig. 4 shows the preview image IPA2 displayed in step S5.

[0072] The second parameter type set includes a third image quality parameter type that has the third priority and a fourth image quality parameter type that has the fourth priority. If the imaging part is the "head", the third image quality parameter type is "edge emphasis intensity" and the fourth image quality parameter type is "contrast". Here, the third image quality parameter type has three candidate values ​​P3A, P3B, and P3C, and the fourth image quality parameter type has three candidate values ​​P4A, P4B, and P4C.

[0073] The preview image generating unit 72 performs image processing on the medical imaging data for each of the nine combinations of the candidate values ​​of the third image quality parameter type and the candidate values ​​of the fourth image quality parameter type, i.e., P3A×P4A, P3A×P4B, P3A×P4C, P3B×P4A, P3B×P4B, P3B×P4C, P3C×P4A, P3C×P4B, and P3C×P4C, to generate nine candidate images ICA2 11 , ICA2 12 , ICA2 13 , ICA2 21 , ICA2 22 , ICA2 23 , ICA2 31 , ICA2 32 , ICA2 33 , is generated. Note that preview image generating unit 72 may use the setting values ​​determined in step S4 for the first parameter type and the second parameter type in the image processing in step S5.

[0074] Furthermore, the preview image generating unit 72 generates nine candidate images ICA2 11 , ICA2 12 , ICA2 13 , ICA2 21, ICA2 22 , ICA2 23 , ICA2 31 , ICA2 32 , ICA2 33 A preview image IPA2 is generated in which the above-mentioned three image quality parameters are arranged two-dimensionally with the type of the third image quality parameter on the vertical axis and the type of the fourth image quality parameter on the horizontal axis.

[0075] In step S6, the user uses the input device 50 to input nine candidate images ICA2 of the preview image IPA2. 11 , ICA2 12 , ICA2 13 , ICA2 21 , ICA2 22 , ICA2 23 , ICA2 31 , ICA2 32 , ICA2 33 The selection operation receiving unit 76 receives a selection operation for the candidate image.

[0076] Image quality parameter value determination section 78 determines the candidate value of the third image quality parameter type corresponding to the candidate image selected in step S6 as the setting value for the third image quality parameter type. Image quality parameter value determination section 78 also determines the candidate value of the fourth image quality parameter type corresponding to the candidate image selected in step S6 as the setting value for the fourth image quality parameter type.

[0077] In this way, for three or more types of image quality parameters acquired according to the imaging area, setting values ​​are sequentially determined for each type of image quality parameter for a parameter type set consisting of two types of image quality parameters combined in order of priority.

[0078] Furthermore, the preview image generating unit 72 generates a preview image of the (N)th parameter type set. In step S7, the preview image display unit 74 displays the preview image of the (N)th parameter type set on the display device 60. F4C in Fig. 4 shows the preview image IPAN displayed in step S7.

[0079] The (N)th parameter type set includes a (2N-1)th image quality parameter type having a (2N-1)th priority order, and a (2N)th image quality parameter type having a (2N)th priority order. Here, it is assumed that the (2N-1)th image quality parameter type has three candidate values ​​P(2N-1)A, P(2N-1)B, and P(2N-1)C, and the (2N)th image quality parameter type has three candidate values ​​P(2N)A, P(2N)B, and P(2N)C.

[0080] The preview image generating unit 72 performs image processing on the medical imaging data for each of the nine combinations of the candidate values ​​of the (2N-1)th image quality parameter type and the candidate values ​​of the (2N)th image quality parameter type, i.e., P(2N-1)A×P(2N)A, P(2N-1)A×P(2N)B, P(2N-1)A×P(2N)C, P(2N-1)B×P(2N)A, P(2N-1)B×P(2N)B, P(2N-1)B×P(2N)C, P(2N-1)C×P(2N)A, P(2N-1)C×P(2N)B, and P(2N-1)C×P(2N)C, to generate nine candidate images ICAN 11 , I.C.A.N. 12 , I.C.A.N. 13 , I.C.A.N. 21 , I.C.A.N. 22 , I.C.A.N. 23 , I.C.A.N. 31 , I.C.A.N. 32 , I.C.A.N. 33 , is generated. Note that preview image generating unit 72 may use the setting values ​​determined so far for the first parameter type through the (2N-2)th parameter type in the image processing in step S7.

[0081] Furthermore, the preview image generating unit 72 generates nine candidate images ICAN 11 , I.C.A.N. 12 , I.C.A.N. 13 , I.C.A.N. 21 , I.C.A.N. 22 , I.C.A.N. 23 , I.C.A.N. 31 , I.C.A.N. 32 , I.C.A.N. 33A preview image IPAN is generated in which the (2N-1)th image quality parameter type is arranged two-dimensionally with the (2N)th image quality parameter type on the vertical axis and the (2N)th image quality parameter type on the horizontal axis.

[0082] In step S8, the user uses the input device 50 to select one of the nine candidate images ICAN of the preview image IPAN. 11 , I.C.A.N. 12 , I.C.A.N. 13 , I.C.A.N. 21 , I.C.A.N. 22 , I.C.A.N. 23 , I.C.A.N. 31 , I.C.A.N. 32 , I.C.A.N. 33 The selection operation receiving unit 76 receives a selection operation for the candidate image.

[0083] Image quality parameter value determination section 78 determines the candidate value for the (2N-1)th image quality parameter type corresponding to the candidate image selected in step S8 as the setting value for the (2N-1)th image quality parameter type. Furthermore, image quality parameter value determination section 78 determines the candidate value for the (2N)th image quality parameter type corresponding to the candidate image selected in step S8 as the setting value for the (2N)th image quality parameter type.

[0084] Finally, in step S9, the final image generating section 80 applies the setting values ​​of the first to (2N) types of image quality parameters to image process the acquired medical imaging data to generate a medical image, which is the final image.

[0085] When the number of types of image quality parameters obtained according to the imaging area is odd, for the type of image quality parameter with the lowest priority, multiple candidate values ​​for that type of image quality parameter are used to image process the medical imaging data to generate multiple candidate images, a preview image is generated in which the multiple candidate images are arranged in one dimension, and the user is allowed to select one of the candidate images.

[0086] According to this embodiment, by checking the preview image displayed on display device 60, the user can intuitively ascertain which combination of candidate values ​​in each image quality parameter type set will provide the most preferable image quality for the candidate image, and so can select appropriate values ​​for each image quality parameter type.

[0087] Here, an example has been described in which there are three candidate values ​​for each image quality parameter type, but the number of candidate values ​​is not limited to three. If L and M are each an integer of 2 or more, preview image generation section 72 can generate a preview image in which (L×M) types of candidate images are arranged, each of which combines L candidate values ​​of one image quality parameter type with M candidate values ​​of the other image quality parameter type. L and M may be different for each image quality parameter type set. Furthermore, when arranging the candidate images two-dimensionally, it may be arbitrarily determined which image quality parameter type is arranged on the vertical axis or on the vertical axis.

[0088] Alternatively, the candidate values ​​for each image quality parameter type may be fixed to three, and the three candidate values ​​may be changed by the user to desired values.

[0089] Here, three or more image quality parameter types are given non-overlapping priorities, but the priorities may overlap. For example, the first parameter type set may include a first image quality parameter type that has the highest priority and a second image quality parameter type that is also tied for first place.

[0090] Second Embodiment An image processing method according to the second embodiment will be described, focusing on the differences from the first embodiment, using the flowchart in Fig. 3. In the first embodiment, three or more image quality parameter types acquired according to the imaging region were assigned to each parameter type set without overlap, but in the second embodiment, one image quality parameter type may be selected in a duplicated manner for multiple parameter type sets.

[0091] The processes in steps S1 and S2 are the same as those in the first embodiment. In step S3, preview image display unit 74 displays a preview image of the first parameter type set on display device 60. The first parameter type set includes a first image quality parameter type having the first priority, and a second image quality parameter type having the second priority.

[0092] FIG. 6 is a diagram showing an example of a preview image displayed on the display device 60. F6A in FIG. 6 shows a preview image IPB1 displayed in step S3. The preview image IPB1 is an image similar to the preview image IPA1 in the first embodiment. That is, nine candidate images ICA1 included in the preview image IPB1 are 11 , ICA1 12 , ICA1 13 , ICA1 21 , ICA1 22 , ICA1 23 , ICA1 31 , ICA1 32 , ICA1 33 are images that have been processed using combinations of three candidate values ​​P1A, P1B, P1C of the first image quality parameter type and three candidate values ​​P2A, P2B, P2C of the second image quality parameter type.

[0093] In step S4, the user uses the input device 50 to input the nine candidate images ICA1 of the preview image IPB1. 11 , ICA1 12 , ICA1 13 , ICA1 21 , ICA1 22 , ICA1 23 , ICA1 31 , ICA1 32 , ICA1 33 The selection operation receiving unit 76 receives a selection operation for the candidate image.

[0094] Image quality parameter value determination section 78 determines the candidate value of the first image quality parameter type corresponding to the candidate image selected in step S4 as the setting value of the first image quality parameter type. For example, if the selected candidate image is candidate image ICA1 21 If so, the setting value of the type of the first image quality parameter is determined to be P1B. Also, if the selected candidate image is candidate image ICA1 33 If so, the setting value of the first image quality parameter type is determined to be P1C. Note that the setting value of the second image quality parameter type has not been determined at this point.

[0095] Next, in step S5, the preview image display unit 74 displays the preview image of the second parameter type set on the display device 60. F6B in Fig. 6 shows the preview image IPB2 displayed in step S5.

[0096] In the second embodiment, the second parameter type set includes a second image quality parameter type and a third image quality parameter type that has third priority. Here, the second image quality parameter type has three candidate values ​​P2D, P2E, and P2F, and the third image quality parameter type has three candidate values ​​P3A, P3B, and P3C.

[0097] Here, it is preferable that the range of candidate values ​​for the second image quality parameter type of the second parameter type set is relatively narrower than the range of candidate values ​​for the second image quality parameter type of the first parameter type set. <P2B<P2C、かつP2D<P2E<P2Fであるとすると、(P2C-P2A)> It is preferable that the relationship (P2F-P2D) is satisfied.

[0098] Furthermore, it is preferable that the range of candidate values ​​for the second image quality parameter type of the second parameter type set includes the candidate value of the second image quality parameter type corresponding to the candidate image of the first parameter type set selected in step S4. In other words, if the candidate value of the second image quality parameter type corresponding to the candidate image selected in step S4 is P2Z, it is preferable that the relationship P2D≦P2Z≦P2F is satisfied.

[0099] The number of candidate values ​​of the second image quality parameter type in the second parameter type set may be relatively smaller than the number of candidate values ​​of the second image quality parameter type in the first parameter type set.

[0100] The preview image generating unit 72 performs image processing on the medical imaging data for each combination of the candidate values ​​of the second image quality parameter type and the candidate values ​​of the third image quality parameter type, i.e., nine combinations of P2D×P3A, P2D×P3B, P2D×P3C, P2E×P3A, P2E×P3B, P2E×P3C, P2F×P3A, P2F×P3B, and P2F×P3C, to generate nine candidate images ICB2 11 , ICB2 12 , ICB2 13 , ICB2 21 , ICB2 22 , ICB2 23 , ICB2 31 , ICB2 32 , ICB2 33 Generate.

[0101] Furthermore, the preview image generating unit 72 generates nine candidate images ICB2 11 , ICB2 12 , ICB2 13 , ICB2 21 , ICB2 22 , ICB2 23 , ICB2 31 , ICB2 32 , ICB2 33Then, a preview image IPB2 is generated in which the second image quality parameter type is arranged two-dimensionally with the type of the second image quality parameter on the vertical axis and the type of the third image quality parameter on the horizontal axis. Preview image IPB2 may have the type of the second image quality parameter on the horizontal axis and the type of the third image quality parameter on the vertical axis.

[0102] In step S6, the user uses the input device 50 to input one of the nine candidate images ICB2 of the preview image IPB2. 11 , ICB2 12 , ICB2 13 , ICB2 21 , ICB2 22 , ICB2 23 , ICB2 31 , ICB2 32 , ICB2 33 The selection operation receiving unit 76 receives a selection operation for the candidate image.

[0103] Image quality parameter value determination section 78 determines the candidate value of the second image quality parameter type corresponding to the candidate image selected in step S6 as the setting value for the second image quality parameter type. Note that the setting value for the third image quality parameter type has not been determined at this point.

[0104] Next, the preview image display unit 74 displays the preview image of the third parameter type set on the display device 60. F6C in Fig. 6 shows the preview image IPB3.

[0105] The third parameter type set includes a third image quality parameter type and a fourth image quality parameter type that has the fourth highest priority. The third image quality parameter type has three candidate values ​​P3D, P3E, and P3F, and the fourth image quality parameter type has three candidate values ​​P4A, P4B, and P4C. As with the second parameter type set, P3A <P3B<P3C、かつP3D<P3E<P3Fであるとすると、(P3C-P3A)> It is preferable that the relationship (P3F-P3D) is satisfied. Furthermore, if the candidate value of the third image quality parameter type corresponding to the candidate image selected in step S6 is P3Z, it is preferable that the relationship P3D≦P3Z≦P3F is satisfied.

[0106] The preview image generating unit 72 performs image processing on the medical imaging data for each combination of the candidate values ​​of the third image quality parameter type and the candidate values ​​of the fourth image quality parameter type, i.e., nine combinations of P3D×P4A, P3D×P4B, P3D×P4C, P3E×P4A, P3E×P4B, P3E×P4C, P3F×P4A, P3F×P4B, and P3F×P4C, to generate nine candidate images ICB3 11 , ICB3 12 , ICB3 13 , ICB3 21 , ICB3 22 , ICB3 23 , ICB3 31 , ICB3 32 , ICB3 33 Generate.

[0107] Furthermore, the preview image generating unit 72 generates nine candidate images ICB3 11 , ICB3 12 , ICB3 13 , ICB3 21 , ICB3 22 , ICB3 23 , ICB3 31 , ICB3 32 , ICB3 33 A preview image IPB3 is generated in which the above-mentioned three image quality parameters are arranged two-dimensionally with the type of the third image quality parameter on the vertical axis and the type of the fourth image quality parameter on the horizontal axis.

[0108] Next, the user uses the input device 50 to select one of the nine candidate images ICB3 of the preview image IPB3. 11 , ICB3 12 , ICB3 13 , ICB3 21 , ICB3 22 , ICB3 23 , ICB3 31 , ICB3 32 , ICB3 33 The selection operation receiving unit 76 receives a selection operation for the candidate image.

[0109] Image quality parameter value determination section 78 determines the candidate value of the third image quality parameter type corresponding to the selected candidate image as the setting value for the third image quality parameter type. Note that the setting value for the fourth image quality parameter type has not been determined at this point.

[0110] In this way, for three or more image quality parameter types acquired according to the imaging area, where K is an integer, a preview image is displayed in which multiple candidate images are arranged for a parameter type set of the (K)th image quality parameter type and the (K+1)th image quality parameter type combined in order of priority, and the setting value of the (K)th image quality parameter type with the highest priority is determined.

[0111] Similarly, steps S7 and S8 are executed to determine the setting value for the (N)th parameter type set. For the type of image quality parameter with the lowest priority, multiple candidate values ​​for that image quality parameter type are used to perform image processing on the medical imaging data to generate multiple candidate images, a preview image is generated in which the multiple candidate images are arranged in one dimension, and the user is allowed to select one of the candidate images.

[0112] According to the first embodiment, by setting the second parameter type set to the third image quality parameter type and the fourth image quality parameter type, it is possible to quickly determine the setting values ​​of subsequent image quality parameter types without having to consider the first image quality parameter type and the second image quality parameter type for which setting values ​​have already been determined.

[0113] On the other hand, according to the second embodiment, the second parameter type set is set as the second image quality parameter type and the third image quality parameter type, and the second image quality parameter types for which candidate images were selected in the first parameter type set are overlapped and re-evaluated, thereby achieving the effect of enabling a more detailed consideration of the compatibility of the second image quality parameter type in combination with other image quality parameter types.

[0114] The first embodiment and the second embodiment may be used appropriately. For example, of three or more types of image quality parameters, the setting values ​​of the types of image quality parameters having a relatively high priority may be determined by detailed consideration as in the second embodiment, and the setting values ​​of the types of image quality parameters having a relatively low priority may be determined quickly as in the first embodiment.

[0115] Third embodiment In the first and second embodiments, image quality parameter value determination section 78 determines the candidate value of the type of image quality parameter corresponding to a candidate image selected from the preview image as a setting value, and stores the determined setting value for each type of image quality parameter in memory 44 (an example of a "storage section"). Note that the setting value may be stored for each determined doctor, or may be stored for each hospital including multiple doctors.

[0116] Furthermore, when setting values ​​for each type of image quality parameter for a certain number of patients are accumulated, the preview image generating unit 72 may emphasize a candidate image that has been image processed using the candidate value that has been selected the most times for each type of image quality parameter.

[0117] 7 is a diagram showing an example of a preview image according to the third embodiment. Nine candidate images ICC1 included in the preview image IPC 11 , ICC1 12 , ICC1 13 , ICC1 21 , ICC1 22 , ICC1 23 , ICC1 31 , ICC1 32 , ICC1 33 are images obtained by image processing medical imaging data for each of the nine combinations of three candidate values ​​P1A, P1B, P1C of a first image quality parameter type and three candidate values ​​P2A, P2B, P2C of a second image quality parameter type, namely, P1A×P2A, P1A×P2B, P1A×P2C, P1B×P2A, P1B×P2B, P1B×P2C, P1C×P2A, P1C×P2B, and P1C×P2C.

[0118] Here, it is assumed that the most frequently selected candidate value for the first image quality parameter type is P1B, and the most frequently selected candidate value for the second image quality parameter type is P2C. In this case, preview image generating section 72 generates candidate image ICC1, which is a combination of P1B×P2C. 23 (An example of the "first candidate image") is the candidate image ICC1 23 In the preview image IPC shown in FIG. 7, the candidate image ICC1 is emphasized relatively to the other candidate images (an example of a "second candidate image"). 23 is highlighted by being surrounded by a frame FR.

[0119] In this way, candidate values ​​for types of image quality parameters that have been frequently selected in the past serve as guide information, making it easier and more intuitive to select candidate images for determining setting values ​​for each type of image quality parameter.

[0120] The highlighting of the candidate image is not limited to the manner of surrounding it with the frame FR, as long as the user can recognize that the candidate image is highlighted.

[0121] [Fourth embodiment] The priority order given to types of image quality parameters may be such that the more varied the preferences for setting values ​​of an image quality parameter type, the higher the priority order given to that type of image quality parameter.

[0122] As in the third embodiment, image quality parameter value determination section 78 stores the determined setting values ​​for each image quality parameter type in memory 44. When the setting values ​​for each image quality parameter type for a certain number of patients have been accumulated, processor 42 reads out the previously determined setting values ​​for each image quality parameter type from memory 44 and calculates the variation in setting values ​​for each image quality parameter type. Then, image quality parameter types with relatively greater variation in setting values ​​are reassigned relatively higher priorities.

[0123] That is, image quality parameter types with large variation in set values ​​are considered to be image quality parameter types with user preferences that vary, and are therefore reassigned high priority. On the other hand, image quality parameter types with small variation in set values ​​are considered to be image quality parameter types for which the user has little need to select a set value, and are therefore reassigned low priority. Image quality parameter types with small variation in set values ​​may be deleted from the three or more image quality parameter types acquired according to the imaging region. In this case, the average value of image quality parameters with small variation in set values ​​may be used as a fixed value.

[0124] Thereafter, the processor 42 performs the same processes as those in the first and second embodiments based on the reassigned priorities.

[0125] In this way, processor 42 performs processing according to the priority assigned in step S2 from the time of shipment until the setting values ​​are accumulated. Then, when the setting values ​​of each image quality parameter type for a certain number of patients have been accumulated, image quality parameter types with variations in preference are automatically extracted, and priority is assigned according to the variation in setting values, and the types are rearranged.

[0126] For example, suppose the imaging area is the "head" and the priority order given by the user is first "spatial resolution," second "S / N ratio (denoise intensity)," third "edge enhancement intensity," and fourth "contrast."

[0127] Thereafter, if the result of calculating the variation in the setting value for each type of image quality parameter shows that the variation in the setting value of "edge enhancement intensity" is relatively small, processor 42 relatively lowers the priority of "edge enhancement intensity." That is, when the imaging part is the "head," the reassigned priorities are as follows: first, "spatial resolution," second, "S / N ratio (denoise intensity)," third, "contrast," and fourth, "edge enhancement intensity."

[0128] Furthermore, when the variation in the setting value of "edge enhancement intensity" is relatively small, processor 42 may delete "edge enhancement intensity" from the types of image quality parameters selected according to the imaging region "head". That is, when the imaging region is "head", the priority order to be reassigned may be first "spatial resolution", second "S / N ratio (denoise intensity)", and third "contrast". In this case, processor 42 may process "edge enhancement intensity" with the average value of the setting value with little variation as a fixed value.

[0129] According to the fourth embodiment, it is possible to select setting values ​​preferentially from among a plurality of image quality parameter types, image quality parameter types for which preferences are likely to vary, i.e., image quality parameter types that are important to the user. This makes it possible to assist the user in determining setting values ​​for image quality parameter types by using a parameter database of a certain number of medical images, such as several hundred examples.

[0130] Fifth embodiment 8 is a flowchart showing steps of a medical image processing method according to the fifth embodiment by the medical image processing apparatus 40. In the fifth embodiment, each parameter type set includes three image quality parameter types.

[0131] The processes in steps S11 and S12 are similar to the processes in steps S1 and S2 in the first embodiment.

[0132] In step S13, the preview image display unit 74 generates a preview image of the first parameter type set, and causes the display device 60 to display it.

[0133] The first parameter type set includes a first image quality parameter type having the first priority, a second image quality parameter type having the second priority, and a third image quality parameter type having the third priority. Here, it is assumed that the first image quality parameter type has three candidate values ​​P1A, P1B, P1C, the second image quality parameter type has three candidate values ​​P2A, P2B, P2C, and the third image quality parameter type has three candidate values ​​P3A, P3B, P3C.

[0134] Preview image generation unit 72 generates combinations of candidate values ​​for the first image quality parameter type, candidate values ​​for the second image quality parameter type, and candidate values ​​for the third image quality parameter type, namely P1A×P2A×P3A, P1A×P2A×P3B, P1A×P2A×P3C, P1A×P2B×P3A, P1A×P2B×P3B, P1A×P2B×P3C, P1A×P2C×P3A, P1A×P2C×P3B, P1A×P2C×P3C, P1B×P2A×P3A, P1B×P2A×P3B, P1B×P2A×P The medical imaging data was processed for each of the 27 combinations, i.e., P1B×P2B×P3A, P1B×P2B×P3B, P1B×P2B×P3C, P1B×P2C×P3A, P1B×P2C×P3B, P1B×P2C×P3C, P1C×P2A×P3A, P1C×P2A×P3B, P1C×P2A×P3C, P1C×P2B×P3A, P1C×P2B×P3B, P1C×P2B×P3C, P1C×P2C×P3A, P1C×P2C×P3B, P1C×P2C×P3C, and 27 candidate images ICD1 111 , ICD1 112 , ICD1 113 , ICD1 121 , ICD1 122 , ICD1 123, ICD1 131 , ICD1 132 , ICD1 133 , ICD1 211 , ICD1 212 , ICD1 213 , ICD1 221 , ICD1 222 , ICD1 223 , ICD1 231 , ICD1 232 , ICD1 233 , ICD1 311 , ICD1 312 , ICD1 313 , ICD1 321 , ICD1 322 , ICD1 323 , ICD1 331 , ICD1 332 , ICD1 333 , to generate

[0135] Furthermore, preview image generating section 72 generates a preview image for each value type of the third image quality parameter out of the 27 types of candidate images.

[0136] Here, preview image generating unit 72 selects nine types of candidate images ICD1, out of the 27 types of candidate images, for which the candidate value of the third image quality parameter type is P3A (an example of a "first candidate value"). 111 , ICD1 121 , ICD1 131 , ICD1 211 , ICD1 221 , ICD1 231 , ICD1 311 , ICD1 321 , ICD1 331 Then, a preview image IPD11 (an example of a "first preview image") is generated in which the first image quality parameter type is plotted two-dimensionally with the vertical axis representing the type of the second image quality parameter and the horizontal axis representing the type of the second image quality parameter.

[0137] Furthermore, preview image generating unit 72 generates nine candidate images ICD1 among the 27 candidate images for which the candidate value of the third image quality parameter type is P3B (an example of a "second candidate value"). 112 , ICD1 122 , ICD1132 , ICD1 212 , ICD1 222 , ICD1 232 , ICD1 312 , ICD1 322 , ICD1 332 Then, a preview image IPD12 (an example of a "second preview image") is generated in which the first image quality parameter type is plotted two-dimensionally with the vertical axis representing the type of the second image quality parameter and the horizontal axis representing the type of the second image quality parameter.

[0138] Similarly, the preview image generating unit 72 generates nine candidate images ICD1, out of the 27 candidate images, for which the candidate value of the third image quality parameter type is P3C. 113 , ICD1 123 , ICD1 133 , ICD1 213 , ICD1 223 , ICD1 233 , ICD1 313 , ICD1 323 , ICD1 333 A preview image IPD13 is generated in which the first image quality parameter type is arranged two-dimensionally with the vertical axis representing the type of the second image quality parameter and the horizontal axis representing the type of the second image quality parameter.

[0139] Fig. 9 is a diagram showing an example of a preview image displayed on the display device 60. F9A in Fig. 9 shows a preview image IPD11. A scroll bar SB is displayed on the right side of the preview image IPD11. The scroll bar SB includes a scroll area SA that extends linearly in the vertical direction, and a scroll knob SN that can be moved in the vertical direction within the scroll area SA.

[0140] In the state shown in F9A, the scroll bar SB is located at the top of the scroll area SA. Here, the position of the scroll bar SB in the scroll area SA corresponds to the candidate value of the third image quality parameter type. The user can move the scroll bar SB in the scroll area SA by using the input device 50.

[0141] When the user moves scroll bar SB to the center of scroll area SA (an example of a "switching operation"), preview image display unit 74 displays preview image IPD12, which is a preview image of the first parameter type set and in which the candidate value for the third image quality parameter type is P3B, on display device 60. F9B in Fig. 9 shows preview image IPD12.

[0142] Furthermore, when the user moves scroll bar SB to the bottom within scroll area SA, preview image display unit 74 causes preview image IPD13, which is a preview image of the first parameter type set and in which the candidate value for the third image quality parameter type is P3C, to be displayed on display device 60. F9C in Fig. 9 shows preview image IPD13.

[0143] In step S14, the user operates scroll bar SB to display and select one of preview images IPD11, IPD12, IPD13 on display device 16. Selection operation receiving unit 76 receives the preview image selection operation. This user action corresponds to selecting a candidate value for the third image quality parameter type.

[0144] In step S15, the user uses the input device 50 to select one candidate image from the preview images displayed on the display device 16. The selection operation receiving unit 76 receives the selection operation of the candidate image.

[0145] That is, when the preview image IPD11 is displayed, the user can select from nine types of candidate images ICD1 111 , ICD1 121 , ICD1 131 , ICD1 211 , ICD1 221 , ICD1 231 , ICD1 311 , ICD1 321 , ICD1 331 When the preview image IPD12 is displayed, the user selects one of the nine candidate images ICD1 112, ICD1 122 , ICD1 132 , ICD1 212 , ICD1 222 , ICD1 232 , ICD1 312 , ICD1 322 , ICD1 332 When the preview image IPD13 is displayed, the user selects one of the nine candidate images ICD1 113 , ICD1 123 , ICD1 133 , ICD1 213 , ICD1 223 , ICD1 233 , ICD1 313 , ICD1 323 , ICD1 333 , and selects one candidate image from among these. This user action corresponds to selecting a candidate value for the first image quality parameter type and a candidate value for the second image quality parameter type.

[0146] The image quality parameter value determination unit 78 determines the candidate value of the third image quality parameter type corresponding to the preview image selected in step S14, the candidate value of the first image quality parameter type corresponding to the candidate image selected in step S15, and the candidate value of the second image quality parameter type as the setting values ​​for each image quality parameter type.

[0147] Next, in step S16, preview image display unit 74 generates a number of preview images of the second parameter type set, and causes one of the preview images to be displayed on display device 60. The second parameter type set includes a fourth image quality parameter type having the fourth priority, a fifth image quality parameter type having the fifth priority, and a sixth image quality parameter type having the sixth priority.

[0148] In step S17, the user selects one preview image from the multiple preview images of the second parameter type set using the input device 50. The selection operation receiving unit 76 receives the selection operation of the preview image.

[0149] In step S18, the user selects one candidate image from the preview images selected in step S17 using the input device 50. The selection operation receiving unit 76 receives the selection operation of the candidate image. As a result, the setting value for the second parameter type set is determined.

[0150] Similarly, steps S19, S20, and S21 are executed to determine the setting values ​​for the (N)th parameter type set.

[0151] Finally, in step S22, the final image generator 80 applies the determined setting values ​​for each type of image quality parameter to image process the acquired medical imaging data to generate a medical image, which is the final image.

[0152] According to the fifth embodiment, when determining setting values ​​for a large number of types of image quality parameters, the parameters can be determined in a shorter time than when determining the parameters two at a time as in the first embodiment.

[0153] The method of determining the setting values ​​in image quality parameter value determination section 78 is not limited to the example of determining three at a time. For example, image quality parameter value determination section 78 may determine the candidate value of the first image quality parameter type corresponding to the candidate image selected in step S4 as the setting value for the first image quality parameter type, but not determine setting values ​​for the second image quality parameter type and the third image quality parameter type.

[0154] In this case, the second parameter type set in step S5 includes the second image quality parameter type, the third image quality parameter type, and a fourth image quality parameter type with the fourth highest priority. As in the second embodiment, the range of candidate values ​​for the second image quality parameter type in the second parameter type set is relatively narrower than the range of candidate values ​​for the second image quality parameter type in the first parameter type set. Also, the range of candidate values ​​for the second image quality parameter type in the second parameter type set includes the setting value of the second image quality parameter type in the first parameter type set. The same applies to the range of candidate values ​​for the third image quality parameter type.

[0155] In addition, the image quality parameter value determination unit 78 determines the candidate value of the first image quality parameter type and the candidate value of the second image quality parameter type corresponding to the candidate image selected in step S4 as the setting value of the first image quality parameter type and the setting value of the second image quality parameter type, respectively, and does not need to determine a setting value for the third image quality parameter type.

[0156] In this case, the second parameter type set in step S5 includes a third image quality parameter type, a fourth image quality parameter type with the fourth highest priority, and a fifth image quality parameter type with the fifth highest priority. As in the second embodiment, the range of candidate values ​​for the third image quality parameter type in the second parameter type set is relatively narrower than the range of candidate values ​​for the third image quality parameter type in the first parameter type set. Also, the range of candidate values ​​for the third image quality parameter type in the second parameter type set includes the setting value of the third image quality parameter type in the first parameter type set.

[0157] Moreover, the position of the scroll bar SB is not limited to a position adjacent to the preview image. Fig. 10 is a diagram showing an example of a preview image in which the scroll bar is arranged at a different position. As shown in Fig. 10, it is sufficient that the scroll bar is arranged within the screen of the display device 60. Moreover, the scroll bar SB may include a scroll area SA that extends linearly in the left-right direction, and a scroll knob SN that can be moved left-right within the scroll area SA.

[0158] Furthermore, a preview image other than the preview image corresponding to the position of the scroll bar SB may be displayed. A preview image other than the preview image corresponding to the position of the scroll bar SB may be displayed so as to be partially hidden behind the preview image corresponding to the position of the scroll bar SB. In the example shown in Fig. 10, the preview image corresponding to the position of the scroll bar SB is preview image IPD11, and the other preview images IPD12 and IPD13 are displayed so as to be partially hidden behind preview image IPD11. By displaying in this manner, the user can recognize the existence of preview images other than the preview image corresponding to the position of the scroll bar SB.

[0159] Moreover, switching of preview images is not limited to using a scroll bar. FIG. 11 is a diagram showing an example of preview images that can be switched by a method other than the scroll bar. As shown in FIG. 11, the preview images may be displayed as if they were arranged in a space with depth (so-called flip 3D display). The user can select a desired preview image by operating the input device 50. Also, the foremost preview image may be switchable by operating the input device 50.

[0160] Sixth embodiment When the candidate image is a three-dimensional image and the image included in the preview image is a slice image of the candidate image, the slice position may be changed using a scroll bar.

[0161] Fig. 12 is a diagram showing an example of a preview image displayed on the display device 60. Each candidate image included in the preview image IPE1 shown in F12A of Fig. 12 (an example of a "third preview image") is a slice image at the same slice position in the same direction (an example of a "first slice position"). As shown in F12A, a scroll bar SB is displayed on the right side of the preview image IPE1. Here, the position of the scroll bar SB in the scroll area SA corresponds to the slice position of the candidate image. The user can move the scroll bar SB in the scroll area SA by using the input device 50.

[0162] When the user moves the scroll bar SB (an example of a "switching operation"), the preview image display unit 74 displays a preview image IPE2 different from the preview image IPE1. F12B in FIG. 12 shows the preview image IPE2 (an example of a "fourth preview image"). The slice positions (an example of a "second slice position") of each candidate image of the preview image IPE2 are different from the slice positions of each candidate image of the preview image IPE1.

[0163] The selection operation receiving unit 76 receives a selection operation of one candidate image from the preview image IPE1 or the preview image IPE2.

[0164] According to the sixth embodiment, preview images of slice images at different slice positions can be displayed, so that the user can select appropriate values ​​for each image quality parameter type. A switching button for changing the slice direction may be displayed together with the preview images.

[0165] <Other> The medical image processing device, the medical image processing method and program, and the image diagnostic system according to the present disclosure can also be applied to an image processing device, an image processing method and program, and an image diagnostic system that use natural images other than medical images. For example, the present disclosure can be applied to a technology for performing an inspection to detect defects such as cracks from image data of social infrastructure facilities such as transportation, electricity, gas, and water.

[0166] The technical scope of the present invention is not limited to the scope described in the above embodiments. The configurations and the like in each embodiment can be appropriately combined with each other without departing from the spirit of the present invention. [Explanation of symbols]

[0167] 10. Diagnostic imaging system 20... Diagnostic imaging equipment 30...Information processing device 40...Medical image processing device 42…Processor 44…Memory 50...Input device 60…Display device

Claims

1. At least one processor; at least one memory storing instructions for said processor to execute; Equipped with The processor, Acquire medical imaging data; displaying on a display device a preview image in which a plurality of candidate images obtained by image processing the medical imaging data by combining a plurality of different candidate values ​​of one image quality parameter type with a plurality of different candidate values ​​of the other image quality parameter type for a parameter type set of two image quality parameter types out of three or more image quality parameter types related to the image quality of a medical image generated from the medical imaging data are arranged two-dimensionally with the type of one image quality parameter on one axis and the type of the other image quality parameter on the other axis; accepting a selection operation of one of the candidate images from the preview image; determining at least one of the candidate value of the one image quality parameter type and the candidate value of the other image quality parameter type corresponding to the selected candidate image as a setting value of the image quality parameter type; A medical image processing device, The three or more types of image quality parameters are assigned priorities, determining the setting values ​​for a first parameter type set including a first image quality parameter type having a first priority and a second image quality parameter type having a second priority, and then determining the setting values ​​for a second parameter type set different from the first parameter type set; applying the set values ​​of each of the three or more types of image quality parameters to image-process the medical imaging data to generate a medical image; Medical imaging equipment.

2. the processor determines the setting value of the first image quality parameter type and the setting value of the second image quality parameter type for the first parameter type set; the second parameter type set includes a third image quality parameter type having third priority and a fourth image quality parameter type having fourth priority; The medical image processing device according to claim 1 .

3. The processor determines the setting value of the first image quality parameter type for the first parameter type set; the second parameter type set includes the second image quality parameter type and a third image quality parameter type having the third priority order; The medical image processing device according to claim 1 .

4. a range of the plurality of candidate values ​​of the second image quality parameter type of the second parameter type set is relatively narrower than the range of the plurality of candidate values ​​of the second image quality parameter type of the first parameter type set, and includes the candidate value of the second image quality parameter type of the first parameter type set that corresponds to the selected candidate image. The medical image processing device according to claim 3 .

5. a storage unit for storing previously determined setting values ​​of each of the three or more image quality parameter types; The processor, in the preview image, a first candidate image corresponding to a combination of the setting value that has been determined most frequently in the past for the one image quality parameter type and the setting value that has been determined most frequently in the past for the other image quality parameter type is relatively emphasized compared to a second candidate image different from the first candidate image; The medical image processing device according to claim 1 .

6. The processor, acquiring an imaging region of the medical imaging data; acquiring the three or more types of image quality parameters according to the imaging region; The medical image processing device according to claim 1 .

7. the priority order is assigned relatively higher to types of image quality parameters for which the previously determined setting values ​​have a relatively large variation; The medical image processing device according to claim 1 .

8. the first parameter type set further includes a third image quality parameter type having a third priority; The processor, displaying on a display device a first preview image in which the plurality of candidate images for the first candidate value of the third image quality parameter type are arranged in two dimensions among a plurality of candidate images obtained by image processing the medical imaging data by combining a plurality of different candidate values ​​for the first image quality parameter type, a plurality of different candidate values ​​for the second image quality parameter type, and a plurality of different candidate values ​​for the third image quality parameter type; accepting a switching operation for switching the candidate value for the third image quality parameter type; displaying a second preview image in which the plurality of candidate images for a second candidate value different from the first candidate value for the third image quality parameter type are arranged in two dimensions in response to the switching operation; accepting a selection operation of one of the candidate images from the first preview image or the second preview image; determining the candidate value of at least the first image quality parameter type corresponding to the selected candidate image as a setting value of the first image quality parameter type; The medical image processing device according to claim 1 .

9. The processor, determining the candidate value of the second image quality parameter type corresponding to the selected candidate image as a setting value of the second image quality parameter type; determining the candidate value of the third image quality parameter type corresponding to the selected candidate image as a setting value of the third image quality parameter type; The medical image processing device according to claim 8 .

10. the candidate images are three-dimensional images; The processor, displaying a third preview image in which slice images at the first slice positions of each of the plurality of candidate images are arranged two-dimensionally; Accepting a switching operation for switching slice positions of the plurality of candidate images; displaying a fourth preview image in which slice images at a second slice position different from the first slice position are arranged two-dimensionally in response to the switching operation; accepting a selection operation of one of the candidate images from the third preview image or the fourth preview image; The medical image processing device according to claim 1 .

11. The processor, applying the determined settings for the first parameter type set to image process the medical imaging data to generate a plurality of candidate images for the second parameter type set; The medical image processing device according to claim 1 .

12. A medical image processing apparatus according to any one of claims 1 to 11, an image diagnostic device for capturing the medical imaging data; The display device; an input device for allowing a user to select one of the candidate images from the preview images; Equipped with Diagnostic imaging system.

13. The imaging diagnostic apparatus is an MRI (Magnetic Resonance Imaging) apparatus. The imaging diagnostic system according to claim 12.

14. At least one processor Acquire medical imaging data; displaying on a display device a preview image in which a plurality of candidate images obtained by image processing the medical imaging data by combining a plurality of different candidate values ​​of one image quality parameter type with a plurality of different candidate values ​​of the other image quality parameter type for a parameter type set of two image quality parameter types out of three or more image quality parameter types related to the image quality of a medical image generated from the medical imaging data are arranged two-dimensionally with the type of one image quality parameter on one axis and the type of the other image quality parameter on the other axis; accepting a selection operation of one of the candidate images from the preview image; determining at least one of the candidate value of the one image quality parameter type and the candidate value of the other image quality parameter type corresponding to the selected candidate image as a setting value of the image quality parameter type; 1. A medical image processing method, comprising: The three or more types of image quality parameters are assigned priorities, determining the setting values ​​for a first parameter type set including a first image quality parameter type having a first priority and a second image quality parameter type having a second priority, and then determining the setting values ​​for a second parameter type set different from the first parameter type set; applying the set values ​​of each of the three or more types of image quality parameters to image-process the medical imaging data to generate a medical image; Medical image processing method.

15. A program for causing a computer to execute the medical image processing method according to claim 14.

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