Image processing device, image processing method and program

Abstract

To improve visibility of image data to be processed.SOLUTION: An image processing device includes an image generation unit that generates output image data by setting a calculated value as a pixel value corresponding to a pixel of interest, the pixel of interest being set to a pixel of each of pieces of image data to be processed, and the calculated value being obtained by collecting pixel values of pixels in the vicinity of the pixel of interest. The image generation unit obtains the calculated value by combining the maximum value and the minimum value of the pixel values of the pixels in the vicinity of the pixel of interest.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an image processing device, an image processing method, and a program. [Background technology]

[0002] Patent Document 1 discloses a technology in the medical field that visualizes changes in lesions and the like by presenting to a user differential image data between three-dimensional image data obtained by imaging using various modalities. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2018-33698 Summary of the Invention [Problem to be solved by the invention]

[0004] In the technology disclosed in Patent Document 1 for visualizing changes in a lesion or the like, there may be cases where changes contained in differential image data between three-dimensional image data are overlooked.

[0005] The present invention has been made in view of the above-mentioned problems, and has as its object to provide an image processing technique that can improve the visibility of image data to be processed. [Means for solving the problem]

[0006] An image processing device according to one aspect of the present invention has the following arrangement. difference process of subject an input image acquisition unit that acquires two pieces of input image data such that a differential image acquisition unit that acquires differential image data generated from the two input image data; The difference Image data Focus on The pixel is set as the target pixel. Whenan image generating means for generating output image data by setting a calculated value obtained by aggregating pixel values ​​of pixels in the vicinity of the pixel of interest as a pixel value corresponding to the pixel of interest; and, Equipped with The image generating means determines the calculated value by combining the maximum and minimum pixel values ​​of pixels in the vicinity of the pixel of interest. [Effects of the Invention]

[0007] According to the present invention, it is possible to improve the visibility of image data to be processed. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a diagram showing the configuration of an image processing system including an image processing apparatus according to a first embodiment. [Figure 2] FIG. 2 is a diagram showing the functional configuration of a control unit of the image processing apparatus. [Figure 3] 10 is a flowchart showing an example of a processing procedure of the image processing device. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the invention according to the claims. Although multiple features are described in the embodiments, not all of these multiple features are necessarily essential to the invention, and multiple features may be combined arbitrarily. Furthermore, in the accompanying drawings, the same reference numerals are used to designate the same or similar components, and redundant explanations will be omitted.

[0010] [First embodiment] The image processing device according to this embodiment improves the visibility of image data to be processed. For example, the image data to be processed is subtraction image data, and the image processing device generates enhanced image data that improves the visibility of the subtraction image data between two sets of medical image data. The configuration and processing of this embodiment will be described below with reference to FIG. 1.

[0011] 1 is a diagram showing the configuration of an image processing system 10 including an image processing device 100 according to the first embodiment. The image processing system 10 includes, as its functional configuration, the image processing device 100, a network 120, and a data server 130. The image processing device 100 is communicably connected to the data server 130 via the network 120. The network 120 includes, for example, a LAN (Local Area Network) or a WAN (Wide Area Network).

[0012] The data server 130 is a picture archiving and communication system (PACS) that stores and manages medical images and information associated with the medical images. The image processing device 100 can acquire medical images stored in the data server 130 via the network 120. The data server 130 receives and stores image data captured by a medical imaging device (modality), and transmits the image data to each device in response to a request from the device connected to the network 120. The data server 130 also includes a database that can store received image data as well as various data associated with the image data.

[0013] In the following description, it is assumed that the data server 130 stores a plurality of medical image data as image data to be processed, the medical image data having been acquired by previously imaging a subject under different conditions (different modalities, imaging modes, dates and times, body positions, etc.). In this embodiment, the medical image data to be processed is described as 3D image data acquired by an X-ray CT device, but the 3D image data may be acquired by other modalities. In addition to an X-ray CT device, modalities include, for example, an MRI device, an ultrasound diagnostic imaging device (ultrasound imaging device), a SPECT device, a PET device, etc., and the image processing device 100 according to this embodiment is applicable to medical image data acquired by various modalities.

[0014] Furthermore, the image data to be processed may be two-dimensional image data instead of three-dimensional image data. Furthermore, the image data to be processed may be projection image data obtained by simple X-ray photography instead of tomographic image data. Furthermore, the two medical image data to be processed may be any combination of image data. For example, they may be images captured at the same time using different modalities or different imaging modes. Furthermore, they may be image data captured on the same subject using the same modality and in the same position on different dates and times for follow-up observation.

[0015] The image processing device 100 may acquire subtraction image data generated by an external device or the like, or may acquire subtraction image data by applying known subtraction processing to two sets of medical image data to generate subtraction image data. The image processing device 100 also functions as a device that displays the generated enhanced image data on a display unit 150 and functions as a terminal device for interpretation operated by a user such as a doctor. The image processing device 100 includes a communication IF (Interface) 111 (communication unit), a ROM (Read Only Memory) 112, a RAM (Random Access Memory) 113, a storage unit 114, and a control unit 115. The image processing device 100 is connected to an instruction unit 140 and the display unit 150.

[0016] The communication IF 111 (communication unit) is configured with a LAN card or the like, and realizes communication between an external device (for example, the data server 130) and the image processing device 100. The ROM 112 is configured with a non-volatile memory or the like, and stores various programs. The RAM 113 is configured with a volatile memory or the like, and temporarily stores various pieces of information as data. The storage unit 114 is configured with a HDD (Hard Disk Drive) or the like, and stores various pieces of information as data.

[0017] The instruction unit 140 is configured with a GUI (Graphical User Interface) such as a keyboard, mouse, and touch panel, and inputs instructions from a user (e.g., a doctor) to the image processing device 100. Image data to be processed is input to the image processing device 100 in accordance with instructions from the user who operates the instruction unit 140. Note that the selection of image data does not have to be based on instructions from the user, and for example, the control unit 115 of the image processing device 100 may be configured to automatically select image data to be processed based on predetermined rules.

[0018] 2 is a diagram showing the functional configuration of the control unit 115. The control unit 115 is configured with a CPU (Central Processing Unit) and the like, and controls the overall processing in the image processing device 100. The control unit 115 has, as its functional configuration, an input image acquisition unit 101, a difference image acquisition unit 103, and an enhanced image generation unit 105.

[0019] The input image acquisition unit 101 acquires reference image data and floating image data as image data to be processed from the data server 130 via the communication IF 111 (communication unit) and the network 120. In the following description, medical image data that serves as a reference for alignment is referred to as reference image data (hereinafter, reference image data), and medical image data that is aligned with the reference image data is referred to as comparison image data (hereinafter, floating image data). Then, the difference image acquisition unit 103 generates difference image data between the reference image data and the floating image data as medical image data to be processed.

[0020] The enhanced image generation unit 105 processes the image data (reference image data, floating image data) acquired by the input image acquisition unit 101 and the differential image data generated by the differential image acquisition unit 103. In this embodiment, an example will be described in which the differential image data is used as the image data to be processed. The enhanced image generation unit 105 generates enhanced image data by enhancing the signals in the differential image data generated by the differential image acquisition unit 103.

[0021] The display control unit 107 performs display control to display image data or various information on the display unit 150. The display unit 150 is configured with any device such as an LCD or a CRT, and displays image data and various information to the user. Specifically, the display unit 150 displays reference image data and floating image data acquired from the image processing device 100. The display unit 150 also displays differential image data and enhanced image data generated by the image processing device 100.

[0022] Each of the components of the image processing device 100 described above functions according to a computer program. For example, the control unit 115 (CPU) uses the RAM 113 as a work area to read and execute a computer program stored in the ROM 112 or the storage unit 114, thereby realizing the function of each component. Note that some or all of the functions of the components of the image processing device 100 may be realized using dedicated circuits. Also, some of the functions of the components of the control unit 115 may be realized using a cloud computer.

[0023] For example, a computing device located at a different location from the image processing device 100 may be communicatively connected to the image processing device 100 via the network 120, and the image processing device 100 and the computing device may send and receive data to realize the functions of the components of the image processing device 100 or the control unit 115.

[0024] Next, an example of processing by the image processing device 100 in Fig. 1 will be described with reference to Fig. 3. Fig. 3 is a flowchart showing an example of a processing procedure of the image processing device 100. In this embodiment, the processing for obtaining enhanced image data will be described using CT image data of a subject as an example, but this embodiment can also be applied to image data obtained by other modalities.

[0025] (S1010: Acquire input image data) In step S1010, when the user issues an instruction to acquire two pieces of image data (first image data and second image data) via the instruction unit 140, the input image acquisition unit 101 acquires reference image data and floating image data as the multiple pieces of image data designated by the user from the data server 130. Then, the acquired reference image data and floating image data are output to the difference image acquisition unit 103 and the enhanced image generation unit 105.

[0026] (S1020: Obtaining differential image data) In step S1020, the difference image acquisition unit 103 generates difference image data between the reference image data and floating image data acquired in step S1010. First, the difference image acquisition unit 103 performs deformation registration of one of the two image data (reference image data, floating image data) acquired from the input image acquisition unit 101 (reference image data) toward the other (floating image data). For deformation registration, known deformation registration processes such as the FFD (Free-Form Deformation) method or the LDDMM (Large Deformation Diffeomorphic Metric Mapping) method can be applied. In both cases, deformation registration maintains the structure of the target area in the medical image data.

[0027] The differential image acquisition unit 103 can calculate the pixel position on the floating image data corresponding to each pixel on the reference image data through the deformation registration process (acquire deformation information (deformation information) indicating the corresponding pixel position between image data). The pixel position of the pixel in the floating image data corresponding to each pixel constituting the reference image data is set as the corresponding pixel position information.

[0028] The differential image acquisition unit 103 can acquire differential image data by subtracting the pixel value of a position on the floating image data corresponding to each position from the pixel value of the reference image data based on the deformation information between the reference image data and the floating image data.

[0029] Note that if differential image data is stored in advance in the data server 130, the process of generating differential image data based on deformation information obtained by deformation alignment may be skipped, and the differential image data stored in the data server 130 may be read and acquired. Furthermore, the image processing device 100 does not necessarily have to have a function of generating differential image data, and the differential image acquisition unit 103 may be configured to acquire differential image data stored in the data server 130. In this case, the process of the input image acquisition unit 101 performed in step 1010 is not necessarily required.

[0030] (S1030: Generate enhanced image data) In step S1030, the enhanced image generation unit 105 acquires differential image data from the input image acquisition unit 101 or the differential image acquisition unit 103, and processes the acquired differential image data to generate enhanced image data (hereinafter also referred to as "output image data").

[0031] The enhanced image generation unit 105 generates enhanced image data (output image data) by setting each pixel of the input image data to be processed as a pixel of interest and setting a calculated value obtained by aggregating pixel values ​​of pixels near the pixel of interest as the pixel value corresponding to the pixel of interest. The enhanced image generation unit 105 obtains a calculated value obtained by aggregating pixel values ​​of pixels near the pixel of interest by combining the maximum and minimum pixel values ​​of the pixels near the pixel of interest through the calculation process of equation (1). In the calculation process of equation (1), the enhanced image generation unit 105 combines the maximum value obtained by the maximum function and the minimum value obtained by the minimum function by adding them together.

[0032] The enhanced image generating unit 105 generates enhanced image data by calculating the pixel value of each pixel in the differential image data, which is a pixel of interest, based on the pixel values ​​of each pixel (pixels in the vicinity of the pixel of interest) within a predetermined range centered on the pixel of interest. The enhanced image generating unit 105 generates enhanced image data I'sub(x) by performing the calculation process of equation (1).

[0033]

number

[0034] In the calculation process of equation (1), the enhanced image generating unit 105 calculates the pixel value of each pixel x on the enhanced image data I'(x), where I represents the differential image data, and I(x) represents the pixel value at coordinate x on the differential image data.

[0035] Here, the coordinate x is a coordinate vector and represents a coordinate according to the dimension of the differential image data. That is, if the differential image data is two-dimensional, it represents a two-dimensional coordinate, and if the differential image data is three-dimensional, it represents a three-dimensional coordinate.

[0036] Furthermore, Φ indicates a predetermined region (region surrounding the pixel of interest) centered on the pixel of interest, and Φ(x) represents each pixel within the predetermined region centered on the pixel of interest position when the pixel at coordinate x is the pixel of interest. Φ can be set arbitrarily based on the filter size of the spatial filter. For example, if the differential image data is three-dimensional image data, Φ can be a 3×3×3 region centered on coordinate x. Region Φ can be set in any direction or shape centered on the pixel of interest. This will be described in detail in Modification Example 1.

[0037] In the calculation process of equation (1), max represents a maximum value function, and min represents a minimum value function, which indicate that the maximum and minimum pixel values ​​of each pixel within a predetermined range are obtained.

[0038] However, the maximum value function max has a constraint that the maximum value must be greater than or equal to 0. In other words, if the maximum value is less than or equal to 0, the maximum value is set to 0. Similarly, the minimum value function min has a constraint that the minimum value must be less than or equal to 0. In other words, if the minimum value is greater than or equal to 0, the minimum value is set to 0. This process is equivalent to the process of finding the maximum positive value and the minimum negative value.

[0039] The enhanced image generating unit 105 calculates the pixel value of the enhanced image data at the target pixel position based on the maximum and minimum values ​​calculated using the maximum and minimum functions for each pixel within a predetermined range centered on the target pixel position. That is, the enhanced image generating unit 105 determines the pixel value of the enhanced image data at the target pixel position as the sum of the maximum and minimum values, as shown in equation (1).

[0040] The highlighted image generating unit 105 may modify the calculation process of equation (1) to set the average value of the maximum and minimum values ​​of the acquired pixel values ​​as the pixel value of the highlighted image data at the pixel of interest position.

[0041] Alternatively, the enhanced image generating unit 105 may generate enhanced image data I'sub(x) by combining the maximum and minimum values ​​weighted based on the distance from the position of the pixel of interest using the calculation process of the following equation (2):

[0042]

number

[0043] The calculation process of equation (2) corresponds to the weighted sum of the maximum and minimum values ​​described in equation (1). The enhanced image generating unit 105 calculates the pixel value of each pixel x on the enhanced image data by calculating the weighted sum using the weights for the maximum and minimum values ​​through the calculation process of equation (2).

[0044] In the calculation process of equation (2), the weight used in the weighted sum can be calculated as follows. That is, the weight is determined based on the relationship between a first distance (hereinafter referred to as d_max) from the pixel of interest position of a pixel that gives the maximum value in the maximum value function and a second distance (hereinafter referred to as d_min) from the pixel of interest position of a pixel that gives the minimum value in the minimum value function. The enhanced image generating unit 105 combines the maximum value obtained by the maximum value function and the minimum value obtained by the minimum value function based on the weight.

[0045] The enhanced image generation unit 105 may set the weights of the weighted sum so that, for example, the weight of a pixel closer to the pixel of interest is greater and the weight of a pixel farther from the pixel of interest is smaller. For example, the enhanced image generation unit 105 can set the weights so that the weights become greater as the first distance (d_max) or the second distance (d_min) becomes closer to the pixel of interest (as they become closer to 0). Furthermore, the enhanced image generation unit 105 can set the weights so that the weights become smaller as the first distance (d_max) or the second distance (d_min) becomes farther from the pixel of interest.

[0046] Equation (3) is a formula for calculating the weight of the maximum value (w_max), and equation (4) is a formula for calculating the weight of the minimum value (w_min).

[0047] w_max= 2*d_min / (d_max+d_min)···(3) w_min= 2*d_max / (d_max+d_min)···(4) The weights may be set in any manner that satisfies the above constraints. For example, a weight table corresponding to combinations of distances (d_max, d_min) may be prepared in advance.

[0048] The enhanced image generation unit 105 acquires a first distance (d_max) from the pixel of interest position of a pixel that gives the maximum value in the maximum value function and a second distance (d_min) from the pixel of interest position of a pixel that gives the minimum value in the minimum value function, and can acquire a weight according to the combination of the acquired distances (d_max, d_min) by referencing a table. The enhanced image generation unit 105 sets a weight according to the combination of the first distance and the second distance by referencing the table. The enhanced image generation unit 105 combines the maximum value acquired by the maximum value function and the minimum value acquired by the minimum value function by calculating a weighted sum using the weights.

[0049] Note that the method of calculating the weighted sum of the maximum and minimum values ​​by the calculation process of Equation (2) is merely one example of a method of combining the maximum and minimum values ​​based on the distance from the target pixel position. For example, a first distance (d_max) from the target pixel position of a pixel that gives the maximum value in the maximum value function and a second distance (d_min) from the target pixel position of a pixel that gives the minimum value in the minimum value function may be compared, and the value closer to the target pixel position (maximum or minimum value) may be selected as the pixel value of the enhanced image data at that pixel position.

[0050] When combining the maximum and minimum pixel values ​​weighted based on the distance from the target pixel position, if either the maximum or minimum value is 0, that value is interpreted as not existing, and the other value is used.

[0051] Since both the positive and negative values ​​of differential image data have important meanings, the process described above can be used to determine the maximum and minimum pixel values ​​near the target pixel position and combine them to generate enhanced image data suitable for the differential image data.

[0052] (S1040: Save and display image data) In step S1040, the control unit 115 of the image processing device 100 stores the difference image data generated in step S1020 and the enhanced image data generated in step S1030 in the storage unit 114 or the data server 130. At this time, the control unit 115 stores at least the enhanced image data in the storage unit 114, and if the difference image data has been stored in advance in the data server 130, it is not necessary to store the difference image data.

[0053] Furthermore, the display control unit 107 displays the highlighted image data on the display unit 150. In this case, the display control unit 107 can switch between displaying the differential image data and the highlighted image data on the display unit 150 in response to a user input using a UI (User Interface) of the instruction unit 140. Note that when the display control unit 107 displays the highlighted image data, the control unit 115 does not necessarily have to store the highlighted image data.

[0054] According to this embodiment, the visibility of the difference image data can be improved by performing enhancement processing suited to the image data to be processed.

[0055] (Variation 1) The shape of the region Φ can be set arbitrarily depending on the type of image data (two-dimensional image data, three-dimensional image data) to be processed. When the medical image data to be processed is two-dimensional image data, the shape of Φ is not limited to a rectangle including a square or a rectangle, but may be a circle, for example. When the medical image data to be processed is three-dimensional image data, the shape of Φ is not limited to a cube or a rectangular parallelepiped, but may be a sphere, for example. Furthermore, the shape of Φ may be set to a fixed shape, or may be selectable by the user via the UI of the instruction unit 140. For example, the user may specify the filter size n of the spatial filter and specify an n×n×n range as Φ.

[0056] Alternatively, multiple Φ may be set via the UI of the instruction unit 140, and the enhanced image generating unit 105 may generate enhanced image data for each Φ. Furthermore, when generating enhanced image data, the enhanced image generating unit 105 may determine the noise level of the differential image data and automatically select Φ to be used depending on the noise level of the differential image data.

[0057] For example, when the reference image data is CT image data, the enhanced image generating unit 105 can change the filter size according to the reconstruction function of the reference image data. For example, the enhanced image generating unit 105 can determine the filter size according to the noise level of the image data. Furthermore, the enhanced image generating unit 105 can change the filter size based on a comparison between the noise level of the image data and a threshold value. For example, when the reconstruction function is a lung field condition, the enhanced image generating unit 105 can determine that the noise level is higher than the threshold value and set the filter size to a small value. Furthermore, when the reconstruction function is a vertical contour condition, the enhanced image generating unit 105 can determine that the noise level is lower than the threshold value and set the filter size to a large value. That is, the enhanced image generating unit 105 sets the filter size when the noise level is higher than the threshold value to a smaller value than the filter size when the noise level is lower than the threshold value.

[0058] Furthermore, the enhanced image generating unit 105 can change the filter size depending on whether or not noise removal processing has been performed on the differential image data. For example, when noise removal processing has been performed on the differential image data, the enhanced image generating unit 105 may set the filter size to be larger than when noise removal processing has not been performed. Furthermore, the enhanced image generating unit 105 may perform the above-mentioned enhancement processing as post-processing when noise removal processing has been performed on the differential image data.

[0059] According to the first modification, by setting an area Φ suitable for the image data to be processed and performing emphasis processing, it is possible to improve the visibility of the image data to be processed.

[0060] (Variation 2) In the above embodiment, the process of generating enhanced image data is performed on differential image data. However, the enhanced image generation unit 105 can also perform the process of generating enhanced image data described above on any input image data (reference image data, comparison image data, or differential image data) specified by the user. That is, regardless of whether the image data for which enhanced image data is to be generated is differential image data, the enhanced image generation unit 105 may perform the processes of steps S1030 and S1040 on the image data acquired by the input image acquisition unit 101 in step S1010. For example, the processes of steps S1030 and S1040 may be performed on at least one of the reference image data (reference image data) that serves as a reference for alignment acquired in step S1010 and the comparison image data (floating image data) that is aligned toward the reference image data. That is, the image data that is the target of the process of generating enhanced image data may include at least one of the reference image data, comparison image data, and differential image data.

[0061] Furthermore, when differential image data is set as the processing target, the enhanced image generation unit 105 may determine whether the image data input to the enhanced image generation unit 105 is differential image data or not based on the presence or absence of type information indicating that it is a differential image set by the differential image acquisition unit 103 when acquiring the differential image data, and if the type of the input image data is differential image data, automatically execute the generation process of the enhanced image data (output image data) described in step S1030.

[0062] (Other embodiments) The present invention can also be realized by supplying a program that realizes one or more functions of the above-described embodiments to a system or device via a network or a storage medium, and having one or more processors in the computer of the system or device read and execute the program. It can also be realized by a circuit (e.g., ASIC) that realizes one or more functions.

[0063] The invention is not limited to the above-described embodiments, and various changes and modifications can be made without departing from the spirit and scope of the invention. Accordingly, the following claims are appended to apprise the public of the scope of the invention. [Explanation of symbols]

[0064] 101: Input image acquisition unit, 103: Difference image acquisition unit, 105: Enhanced image generation unit, 107: Display control unit

Claims

1. An input image acquisition unit that acquires two pieces of input image data to be subjected to differential processing; a differential image acquisition unit that acquires differential image data generated from the two input image data; an image generating means for generating output image data by setting a calculated value obtained by aggregating pixel values ​​of pixels in the vicinity of the pixel of interest when the pixel of interest in the differential image data is set as a pixel value corresponding to the pixel of interest, The image processing device is characterized in that the image generating means obtains the calculated value by combining the maximum and minimum pixel values ​​of pixels in the vicinity of the pixel of interest.

2. 2. The image processing apparatus according to claim 1, wherein said image generating means combines said maximum value and said minimum value by adding said maximum value and said minimum value together.

3. the image generating means sets weights using a first distance from the pixel of interest to the pixel giving the maximum value and a second distance from the pixel of interest to the pixel giving the minimum value, 3. The image processing apparatus according to claim 1, wherein the maximum value and the minimum value are combined based on the weight.

4. 4. The image processing device according to claim 3, wherein the image generating means sets the weight so that it increases as the first distance or the second distance approaches the pixel of interest, and sets the weight so that it decreases as the first distance or the second distance moves away from the pixel of interest.

5. 5. The image processing device according to claim 3, wherein the image generating means sets the weight by referring to a table that stores in advance weights corresponding to combinations of the first distance and the second distance.

6. 6. The image processing apparatus according to claim 3, wherein the image generating means obtains a weighted sum using the weights to obtain a combination of the maximum value and the minimum value.

7. The image generating means compares a first distance from the pixel of interest to the pixel giving the maximum value with a second distance from the pixel of interest to the pixel giving the minimum value, 2. The image processing device according to claim 1, wherein the pixel value of the pixel that gives the maximum value and the pixel that gives the minimum value, whichever is closer to the pixel of interest, is selected as an arithmetic process for calculating a combination of the maximum value and the minimum value.

8. 8. The image processing device according to claim 1, wherein the image data to be subjected to the difference processing includes difference image data obtained by subtracting pixel values ​​between the two input image data.

9. 9. The image processing apparatus according to claim 8, wherein the image generating means generates the output image data when the type of image data to be subjected to the difference processing is the difference image data.

10. 10. The image processing apparatus according to claim 1, wherein the image generating means sets the region including pixels in the vicinity of the pixel of interest based on a filter size.

11. 11. The image processing apparatus according to claim 10, wherein the image generating means determines the filter size in accordance with a noise level of the differential image data.

12. 12. The image processing apparatus according to claim 11, wherein the image generating means changes the filter size based on a comparison between a noise level of the differential image data and a threshold value.

13. 13. The image processing device according to claim 12, wherein the image generating means sets a filter size when the noise level is higher than the threshold to be smaller than a filter size when the noise level is lower than the threshold.

14. further comprising a display control means for displaying the output image data on a display means; 10. The image processing apparatus according to claim 8, wherein the display control means switches the display between the differential image data and the output image data in response to an input from an instruction means and displays the images on the display means.

15. An image processing method for performing differential image processing between two images, comprising: an input image acquisition step of acquiring two pieces of input image data to be subjected to difference processing; a differential image acquisition step of acquiring differential image data generated from the two input image data; an image generating step of generating output image data by setting a calculated value obtained by aggregating pixel values ​​of pixels in the vicinity of the pixel of interest when the pixel of interest in the differential image data is set as a pixel value corresponding to the pixel of interest, The image processing method is characterized in that, in the image generating step, the calculated value is obtained by combining the maximum and minimum pixel values ​​of pixels in the vicinity of the pixel of interest.

16. A program that, when executed on a computer, performs each step of the image processing method according to claim 15.

Images