Medical image processing equipment

Abstract

To assist in selection of image data being a comparison object.SOLUTION: A medical image processing apparatus comprises: a designation unit; a selection unit; a first generation unit; a display control unit; and a second generation unit. The designation unit designates first image data. The selection unit selects one or a plurality of pieces of second image data from the plurality of image data sets having the plurality of pieces of image data. The first generation unit generates a difference image between the first image data and each of the one or the plurality of pieces of second image data. The display control unit displays a list image indicating the list of the difference images generated by the first generation unit. The second generation unit generates the difference image between the first image data and each of the plurality of pieces of image data of the image data set having the second image data that becomes the base of the difference image selected from the list image.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The embodiments disclosed in the present specification and drawings relate to a medical image processing apparatus.

[0002] Conventionally, medical image processing devices may display the difference between specified image data to allow medical professionals such as doctors to easily check changes over time in tumors or bones. For example, to examine changes over time, medical professionals specify image data captured in a current examination and image data captured in a previous examination. The medical image processing device then displays the difference between both sets of image data.

[0003] In some cases, medical professionals may want to compare image data with other image data, not just image data from a previous examination. In this case, medical professionals select image data to compare from an image list. However, medical professionals may have difficulty identifying the image data to select. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-277558 Summary of the Invention [Problem to be solved by the invention]

[0005] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to support the selection of image data to be compared. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be positioned as other problems. [Means for solving the problem]

[0006] A medical image processing apparatus according to an embodiment includes a designation unit, a selection unit, a first generation unit, a display control unit, and a second generation unit. The designation unit designates first image data. The selection unit selects one or more second image data from a plurality of image datasets each having a plurality of image data. The first generation unit generates a difference image between the first image data and one or more of the second image data. The display control unit displays a list image showing a list of the difference images generated by the first generation unit. The second generation unit generates a difference image between the first image data and a plurality of image data in the image dataset each having the second image data on which the difference image selected from the list image was based. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of a medical image processing apparatus according to this embodiment. [Figure 2] FIG. 2 is a diagram showing an example of the sample list image. [Figure 3] FIG. 3 is a flowchart showing an example of the difference image generation process executed by the medical image processing apparatus according to this embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, a medical image processing apparatus according to an embodiment will be described with reference to the drawings. In the following embodiments, parts with the same reference numerals perform similar operations, and redundant description will be omitted as appropriate.

[0009] (Present embodiment) 1 is a block diagram showing an example of the configuration of a medical image processing device 10 according to this embodiment. The medical image processing device 10 is a device that supports the selection of image data to be compared when displaying the differences between two or more image data. For example, the medical image processing device 10 is realized by a computer device such as a personal computer or a tablet terminal.

[0010] For example, the medical image processing apparatus 10 includes a network interface 110, an input interface 120, a display 130, a storage circuitry 140, and a processing circuitry 150.

[0011] The NW interface 110 is connected to the processing circuit 150 and controls the transmission and communication of various data between the processing circuit 150 and each device connected via a network. For example, the NW interface 110 is realized by a network card, a network adapter, a NIC (Network Interface Controller), or the like.

[0012] The input interface 120 is connected to the processing circuit 150 and converts an input operation received from an operator (medical professional) into an electrical signal and outputs the electrical signal to the processing circuit 150. Specifically, the input interface 120 converts the input operation received from the operator into an electrical signal and outputs the electrical signal to the processing circuit 150. For example, the input interface 120 may be realized by a trackball, a switch button, a mouse, a keyboard, a touchpad that performs input operations by touching the operation surface, a touchscreen that integrates a display screen and a touchpad, a non-contact input circuit using an optical sensor, a voice input circuit, or the like. Note that in this specification, the input interface 120 is not limited to those that include physical operation components such as a mouse and a keyboard. For example, an electrical signal processing circuit that receives an electrical signal corresponding to an input operation from an external input device provided separately from the device and outputs the electrical signal to a control circuit is also included as an example of the input interface 120.

[0013] The display 130 is connected to the processing circuit 150 and displays various information and image data output from the processing circuit 150. For example, the display 130 is realized by a liquid crystal display, a CRT (Cathode Ray Tube) display, an organic EL display, a plasma display, a touch panel, or the like.

[0014] The memory circuitry 140 is connected to the processing circuitry 150 and stores various data. The memory circuitry 140 also stores various programs that are read and executed by the processing circuitry 150 to realize various functions. For example, the memory circuitry 140 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, a hard disk, an optical disk, or the like.

[0015] The processing circuitry 150 controls the overall operation of the medical image processing apparatus 10. The processing circuitry 150 has, for example, an image designation function 151, a comparison target acquisition function 152, an image data acquisition function 153, a similarity calculation function 154, a comparison target identification function 155, a region detection function 156, a sample image generation function 157, a priority calculation function 158, a difference extraction function 159, a display control function 160, an operation control function 161, and a difference image generation function 162. In the embodiment, each processing function performed by the components of the image designation function 151, the comparison target acquisition function 152, the image data acquisition function 153, the similarity calculation function 154, the comparison target identification function 155, the region detection function 156, the sample image generation function 157, the priority calculation function 158, the difference extraction function 159, the display control function 160, the operation control function 161, and the difference image generation function 162 is stored in the storage circuitry 140 in the form of a computer-executable program. The processing circuitry 150 is a processor that realizes the functions corresponding to each program by reading and executing the programs from the storage circuitry 140. In other words, after reading each program, the processing circuitry 150 has the functions shown in the processing circuitry 150 of FIG.

[0016] 1 is described as realizing the image designation function 151, comparison target acquisition function 152, image data acquisition function 153, similarity calculation function 154, comparison target identification function 155, part detection function 156, sample image generation function 157, priority calculation function 158, difference extraction function 159, display control function 160, operation control function 161, and difference image generation function 162 by a single processor, but it is also possible to combine multiple independent processors to configure the processing circuit 150 and have each processor execute a program to realize the function. Also, in FIG. 1, it is described as realizing the program corresponding to each processing function by a single storage circuit such as storage circuit 140, but it is also possible to configure multiple storage circuits to be distributed and have the processing circuit 150 read out the corresponding program from each storage circuit.

[0017] The term "processor" used in the above description refers to a circuit such as a CPU (Central Processing Unit), a GPU (Graphical Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (e.g., a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). The processor realizes its functions by reading and executing a program stored in the memory circuit 140. Note that instead of storing a program in the memory circuit 140, the processor may be configured so that the program is directly embedded in its circuitry. In this case, the processor realizes its functions by reading and executing the program embedded in its circuitry.

[0018] When medical professionals capture image data using a medical image diagnostic device, they may compare the image data captured this time with image data captured previously. However, when there are multiple sets of image data captured in the past, medical professionals may have difficulty identifying the image data to select for comparison. For example, if a patient suffers from multiple diseases, the patient may undergo tests specific to each disease. In such cases, the contents of the current test may not match the contents of the previous test. If the test contents differ, medical professionals cannot make a meaningful diagnosis even if the differences between the image data are displayed. Therefore, the medical image processing device 10 supports the selection of image data to be compared using the following functions.

[0019] The image designation function 151 designates first image data. The image designation function 151 is an example of a designation unit. Here, the first image data is medical image data captured by a medical image diagnostic device such as an X-ray CT (Computed Tomography) device, an MRI (Magnetic Resonance Imaging) device, an X-ray diagnostic device, an ultrasound diagnostic device, or a mammography device. The first image data includes a patient.

[0020] More specifically, the image designation function 151 designates image data selected by a medical professional or the like from image data captured by a medical image diagnostic device and stored in a PACS (Picture Archiving and Communication Systems) or the like as the first image data. The first image data may also be image data selected from three-dimensional volume data.

[0021] The comparison target acquisition function 152 acquires one or more image datasets having multiple image data as comparison targets for the first image data specified by the image designation function 151. For example, the image datasets are multiple image data such as three-dimensional volume data captured by a medical image diagnostic device. More specifically, the comparison target acquisition function 152 acquires one or more image datasets from a PACS. That is, the comparison target acquisition function 152 acquires image datasets in which a patient was previously captured.

[0022] The image data acquisition function 153 acquires information about image data included in the image data set acquired by the comparison target acquisition function 152. More specifically, the image data acquisition function 153 acquires information about image data from DICOM (Digital Imaging and Communications in Medicine) tags, radiology reports, electronic medical record information, and the like.

[0023] The information related to the image data includes, for example, the degree of match of the image data, the imaging conditions, and the series description. The degree of match is the degree of match between the first image data specified by the image specification function 151 and the second image data selected from the image data set acquired by the comparison object acquisition function 152. The imaging conditions are the imaging conditions for the image data acquired by the medical image diagnostic device. For example, the imaging conditions include the imaging range, the tube voltage, and the presence or absence of a contrast agent. The series description is information describing the contents of the image data set written by a medical professional such as a technician operating the medical image diagnostic device.

[0024] The similarity calculation function 154 calculates the similarity between the first image data specified by the image specification function 151 and the image data included in the image dataset acquired by the comparison object acquisition function 152. Here, it is meaningless for a medical professional to compare completely different image data, such as that of a head and an abdomen. In other words, the medical image processing apparatus 10 should compare similar image data. Therefore, the similarity calculation function 154 calculates the similarity between the image dataset including the first image data and the image dataset acquired by the comparison object acquisition function 152. For example, the similarity calculation function 154 calculates the similarity based on the number of items that match between information about the image data of the first image data and information about the image data of the image dataset acquired by the comparison object acquisition function 152.

[0025] The comparison target identification function 155 selects one or more second image data from a plurality of image datasets each having a plurality of image data, which serve as the basis for a sample image showing the difference from the first image data specified by the image specification function 151. The comparison target identification function 155 is an example of a selection unit. The sample image is a difference image generated as a sample to make it easier for medical professionals to understand which image dataset to select when generating a formal difference image. Specifically, the sample image is a difference image showing the difference between a portion of the image data contained in the image dataset and the first image data. In this way, the medical image processing apparatus 10 reduces the processing time required to generate a difference image by selecting only a portion of the image data contained in the image dataset, rather than all of the image data.

[0026] For example, the comparison target identification function 155 identifies an image data set from which second image data serving as a basis for generating a sample image is to be selected from among the multiple image data sets acquired by the comparison target acquisition function 152. For example, the comparison target identification function 155 identifies an image data set based on the similarity between the first image data specified by the image designation function 151 and image data contained in the multiple image data sets acquired by the comparison target acquisition function 152. The comparison target identification function 155 is an example of an identification unit. For example, the comparison target identification function 155 identifies an image data set whose similarity is equal to or greater than a threshold. Alternatively, the comparison target identification function 155 identifies, from among the multiple image data sets acquired by the comparison target acquisition function 152, an image data set from an examination performed on the same patient for the same purpose, i.e., a previous examination, as the image data set from which second image data is to be selected.

[0027] Furthermore, the comparison target identification function 155 selects second image data that will be the basis for the sample image from the multiple image data included in the identified image dataset. That is, the comparison target identification function 155 selects second image data that will be the basis for the difference image. For example, the comparison target identification function 155 selects image data that is located at a set position among the image data included in the image dataset as the second image data. Specifically, the comparison target identification function 155 selects image data that is located at a set position, such as the beginning, center, or end of the image dataset, as the second image data.

[0028] Alternatively, the comparison target identification function 155 selects important estimated image data that is estimated to be important from among the image data sets included in the image data set as the second image data. For example, the important estimated image data may be image data included in an interpretation report containing test results, image data containing medical professional findings, image data to which information such as markings or annotations has been added, or image data referenced in electronic medical record information. Note that the important estimated image data is not limited to the image data described above, and may be other image data. Furthermore, the comparison target identification function 155 may detect important estimated image data from an image data set whose similarity is equal to or greater than a threshold, or may detect important estimated image data from an image data set acquired by the comparison target acquisition function 152.

[0029] The part detection function 156 identifies the part of the patient included in the second image data selected by the comparison object identification function 155. For example, the part detection function 156 detects anatomical features included in the second image data. The part detection function 156 then identifies the part of the patient based on the detected anatomical features and the coordinates of the anatomical features in the second image data. The part of the patient is used to describe the second image data.

[0030] The difference extraction function 159 extracts the difference details by comparing the first image data specified by the image specification function 151 with the second image data selected by the comparison target identification function 155. For example, the difference extraction function 159 extracts the difference in the number of tumors included in at least one of the first image data and the second image data, the difference in tumor size, the patient's weight, or the patient's age as the difference details. Note that the difference extraction function 159 may extract difference details regarding other content as the difference between the first image data and the second image data, without being limited to the number of tumors, the tumor size, the patient's weight, or the patient's age.

[0031] The sample image generation function 157 generates a difference image between the first image data specified by the image specification function 151 and one or more second image data selected by the comparison target specification function 155. The sample image generation function 157 is an example of a first generation unit. In this way, the sample image generation function 157 generates a difference image between the second image data selected from the image dataset and the first image data as a sample image.

[0032] The priority calculation function 158 calculates a priority for each sample image, indicating the degree to which the sample image should be used as a basis for generating an official difference image. The priority calculation function 158 calculates the priority based on information about the image data acquired by the image data acquisition function 153, the parts detected by the part detection function 156, and the difference content extracted by the difference extraction function 159. For example, the priority calculation function 158 calculates the priority by calculating the degree of agreement between the information about the first image data and the second image data, the degree of agreement between the parts, and the degree of agreement between the difference content.

[0033] The display control function 160 causes the display 130 to display a sample list image G1 having a list of sample images showing the differences between the two image data generated by the sample image generation function 157. The display control function 160 is an example of a display control unit.

[0034] 2 is a diagram showing an example of the sample list image G1. The sample list image G1 is a list of sample images generated by the sample image generation function 157. More specifically, the sample list image G1 shows information about the sample images and the second image data on which the sample images are based, for each selection condition under which the comparison object identification function 155 selected the second image data and each date on which the second image data was captured.

[0035] The selection condition is a condition for selecting the second image data that served as the basis for the sample image in generating the sample image. For example, the selection condition may be image data at a specified position in an image dataset captured in a previous examination, image data to which information such as annotations or remarks has been added, or image data from which findings have been generated. The selection condition may also be image data that is estimated to be important even though a sample image, i.e., a difference image, has not been generated.

[0036] In the sample list image G1, the display control function 160 displays the sample images in association with information about the second image data on which the sample images are based. For example, the display control function 160 displays a summary description, parts, differences, priority, etc. as information about the second image data on which the sample images are based. The summary description is information about the image data of the second image data on which the sample images are based, such as the degree of similarity between the first image data and the second image data, the shooting conditions, and a series description. In other words, the display control function 160 displays a summary description of the second image data on which the difference images are based in association with the difference images.

[0037] The region is a region of the patient included in the second image data on which the sample image is based that is detected by region detection function 156. That is, display control function 160 displays the region of the patient included in the second image data on which the sample image is based in association with the sample image.

[0038] The difference is information indicating the difference content between the first image data and the second image data extracted by the difference extraction function 159. That is, the display control function 160 displays the difference content of the second image data on which the sample image is based in association with the sample image.

[0039] The priority order is the order of priority calculated by the priority calculation function 158. That is, the display control function 160 displays the priority order for selecting an image dataset having the second image data on which the sample image is based, in association with the sample image.

[0040] In the sample list image G1 shown in Figure 2, selection condition A shows a state in which sample images are presented on dates "2021,03,17," "2021,03,10," "2021,03,03," and "2021,02,24," along with a summary description, parts, differences, and priority. Selection condition B shows a state in which sample images are presented on dates "2021,03,17" and "2021,03,10," along with a summary description, parts, differences, and priority. Selection condition C shows a state in which sample images are presented on date "2021,02,17," along with a summary description, parts, differences, and priority. In the sample list image G1 shown in Figure 2, "N / A" indicates that no corresponding data is available.

[0041] Furthermore, when the second image data on which the sample image is based is estimated important image data, the display control function 160 adds a first estimated important mark G11 to the corresponding sample image. That is, the display control function 160 displays the first estimated important mark G11, which indicates that the second image data on which the sample image is based is estimated to be important, in association with the sample image. The first estimated important mark G11 is an example of a first mark.

[0042] Furthermore, when the selection condition is that the image data is estimated to be important even though no sample image has been generated, the display control function 160 displays a sample list image G1 including image data that is estimated to be important but for which no sample image has been generated. The display control function 160 also adds a second importance estimation mark G12 to the corresponding image data. That is, the display control function 160 displays the second importance estimation mark G12, which indicates that the image data is estimated to be important but for which no sample image has been generated, in association with the image data. The second importance estimation mark G12 is an example of a second mark.

[0043] In the sample list image G1 shown in FIG. 2, the first important estimation mark G11 corresponds to the sample images of the dates "2021,03,17" and "2021,03,03" of selection condition A and "2021,03,10" of selection condition B. The second important estimation mark G12 corresponds to the sample image of the date "2021,02,17" of selection condition C.

[0044] The operation control function 161 accepts an operation to select an image dataset for generating a difference image. For example, the operation control function 161 accepts an operation to select a sample image included in the sample list image G1. The operation control function 161 accepts an image dataset having second image data on which the selected sample image is based as the image dataset for generating a difference image.

[0045] The difference image generation function 162 generates difference images between each of a plurality of image data of an image data set having second image data on which a sample image selected from the sample list image G1 is based and the first image data specified by the image specification function 151. The difference image generation function 162 is an example of a second generation unit. That is, the difference image generation function 162 generates a difference image when the operation control function 161 accepts an operation to select a sample image from the sample list image G1.

[0046] Next, a description will be given of the difference image generation processing executed by the medical image processing apparatus 10. Fig. 3 is a flowchart showing an example of the difference image generation processing executed by the medical image processing apparatus 10 according to this embodiment.

[0047] The image designation function 151 designates the first image data, which is image data to be compared (step S1).

[0048] The comparison target acquisition function 152 acquires an image data set having one or more image data (step S2).

[0049] The comparison target specifying function 155 selects one or more second image data from the image data set acquired by the comparison target acquiring function 152 (step S3).

[0050] The region detection function 156 detects the region of the patient included in the second image data (step S4).

[0051] The sample image generating function 157 generates sample images showing the differences between the first image data and one or more second image data (step S5).

[0052] The priority calculation function 158 calculates a priority indicating the degree to which the generation of the official difference image should be based (step S6).

[0053] The difference extraction function 159 extracts the differences between the first image data and one or more second image data (step S7).

[0054] The display control function 160 displays a sample list image G1 showing the selection conditions for selecting the second image data and sample images for each date on which the second image data was generated (step S8).

[0055] The operation control function 161 determines whether or not an operation to select a sample image included in the sample list image G1 has been accepted (step S9). If an operation to select a sample image has not been accepted (step S9; No), the operation control function 161 waits.

[0056] When an operation to select a sample image is accepted (step S9; Yes), the difference image generation function 162 generates a formal difference image between each of the multiple image data contained in the image data set corresponding to the sample image and the first image data (step S10).

[0057] With the above, the medical image processing apparatus 10 ends the difference image generation process.

[0058] As described above, the image designation function 151 of the medical image processing apparatus 10 according to this embodiment designates first image data. The comparison target identification function 155 selects one or more second image data from one or more image datasets containing multiple image data. The sample image generation function 157 generates sample images showing the differences between the first image data and one or more second image data. The display control function 160 displays a sample list image G1 containing a list of sample images. When a sample image from the sample list image G1 is selected, the difference image generation function 162 generates difference images between the first image data and multiple image data from an image dataset containing the second image data on which the selected sample image was based. Because the list of sample images is displayed in this way, medical professionals can easily understand what difference images will be generated. Therefore, the medical image processing apparatus 10 can assist in the selection of image data to be compared.

[0059] According to at least one of the embodiments described above, it is possible to assist in the selection of images to be compared.

[0060] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0061] 10 Medical image processing device 110 NW (Network) Interface 120 input interface 130 Display 140 Memory circuit 150 Processing Circuit 151 Image specification function 152 Comparison object acquisition function 153 Image data acquisition function 154 Similarity calculation function 155 Comparison Target Specific Function 156 Body Part Detection Function 157 Sample image generation function 158 Priority calculation function 159 Differential Extraction Function 160 Display Control Function 161 Operational Control Functions 162 Differential image generation function G1 sample list image G11 First Important Estimated Mark G12 Second Important Estimated Mark

Claims

1. a designation unit for designating the first image data; a selection unit that selects one or more second image data from a plurality of image data sets having a plurality of image data; a first generation unit that generates a difference image between the first image data and one or more pieces of second image data; a display control unit that displays a list image having a list of the difference images generated by the first generation unit; a second generation unit that generates difference images between the first image data and the plurality of image data in the image data set having the second image data that is the basis of the difference image selected from the list of images; A medical image processing device comprising:

2. the display control unit causes the difference image and information about the second image data on which the difference image is based to be displayed in association with each other. The medical image processing device according to claim 1 .

3. a specifying unit for specifying the image data set from which the second image data is selected from the plurality of image data sets; The selection unit selects the second image data from the plurality of image data included in the image data set identified by the identification unit.

3. The medical image processing device according to claim 1.

4. the display control unit displays a first mark, which indicates that the second image data on which the difference image is based is estimated to be important, in association with the difference image. The medical image processing device according to any one of claims 1 to 3.

5. the display control unit displays a part of the patient included in the second image data on which the difference image is based in association with the difference image. The medical image processing device according to any one of claims 1 to 4.

6. the display control unit displays a difference between the first image data and the second image data on which the difference image is based, in association with the difference image. The medical image processing device according to any one of claims 1 to 5.

7. The display control unit displays, in association with the difference image, a priority order for selecting the image data set having the second image data on which the difference image is based. The medical image processing device according to any one of claims 1 to 6.

8. the display control unit displays the list image including the image data for which the difference image has not been generated and which is estimated to be important. The medical image processing device according to any one of claims 1 to 7.

9. the display control unit displays a second mark corresponding to the image data for which the differential image has not been generated and which indicates that the image data is estimated to be important. The medical image processing device according to claim 8 .

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