Image processing apparatus, image processing method, and program

Abstract

To provide an image processing apparatus, an image processing method, and a program for determining the size of an appropriate comparison area when comparing images taken at different points in time.SOLUTION: An image processing apparatus 1620 is provided with: a pixel size acquisition unit 16020 for acquiring the size of first and second pixels, which is the size of the pixels in predetermined axial directions of a first image and a second image taken at different points in time, respectively; a pixel size determination unit 16030' for determining whether or not the size of the first pixel and the size of the second pixel are different from each other; and a comparison area size determination unit 16040 for, if the size of the first pixel is different from the size of the second pixel, determining the size in a predetermined axial direction of a comparison area, which is an area containing a plurality of density values in one of the first and second images different from the other image, in comparison with the density value of a target position in one of the first and second images based on the larger size of the first and second pixels.SELECTED DRAWING: Figure 16

Description

[Technical field]

[0001] The disclosure of this specification relates to an image processing device, an image processing method, and a program. [Background technology]

[0002] In the medical field, an image difference technique is known that aligns two images taken at different times and displays a difference image that visualizes the difference between the images to assist in comparing the images. However, there is a problem that noise occurs in the difference image due to alignment errors and differences in density values ​​of the same part between the images. As a solution to this problem, Non-Patent Document 1 discloses a technique (voxel matching method) that calculates the differences between a pixel of interest in a first image and a corresponding pixel in a second image and its neighboring pixels, and sets the minimum value of these differences as the density value of the difference image. According to this technique, a pixel closest in value to the pixel of interest is selected from the neighborhood of the corresponding pixel, and the difference value between the pixel and the corresponding pixel is adopted, thereby reducing noise in the difference image. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Yoshinori Itai, Hyoungseop Kim, Seiji Ishikawa, Shigehiko Katsuragawa, Kunio Doi, “Development of a voxel-matching technique for substantial reduction of subtraction artifacts in temporal subtraction images obtained from thoracic MDCT.” Journal of digital imaging, vol. 23, No. 1, pp. 31-38, 2010. Summary of the Invention [Problem to be solved by the invention]

[0004] However, in Non-Patent Document 1, the user arbitrarily determines the range of the comparison area in which the density value of the pixel of interest on the first image is compared with the density values ​​of the corresponding pixel on the second image and its neighboring pixels in the voxel matching method. Therefore, there are cases where noise cannot be sufficiently reduced, and conversely, cases where even necessary signals are deleted. In other words, there is a problem that the size of the comparison area cannot be appropriately determined.

[0005] In addition to the above-mentioned problem, the effect of each configuration shown in the description of the embodiment of the invention described below, which cannot be obtained by conventional techniques, can also be positioned as another problem of the present disclosure. [Means for solving the problem]

[0006] The image processing device disclosed in this specification has a pixel size acquisition means for acquiring a first pixel size, which is the pixel size in a predetermined axial direction of a first image and a second image captured at different times, and a second pixel size different from the first pixel size; a determination means for determining whether the first pixel size and the second pixel size acquired by the pixel size acquisition means are different; and a determination means for determining, when the first pixel size is different from the second pixel size, the size in the predetermined axial direction of a comparison region, which is an area including a plurality of density values ​​in the second image to be compared with the density value of a position of interest in the first image, based on the larger of the first pixel size and the second pixel size. Effect of the Invention

[0007] According to the disclosure of this specification, it is possible to determine an appropriate size of the comparison region. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an example of the device configuration of an image processing apparatus according to a first embodiment. [Diagram 2] FIG. 4 is a flowchart showing an example of an overall processing procedure in the first embodiment. [Diagram 3] 1A is a diagram showing an example of a discretization position shift in the first embodiment, (b) is a diagram showing an example of a discretization position shift in the first embodiment, and (c) is a diagram showing an example of a discretization position shift in the first embodiment. [Figure 4] 5A to 5C are views for explaining an example of a method for setting a comparison region in the first embodiment. [Diagram 5] FIG. 11 is a flowchart showing an example of an overall processing procedure in the second embodiment. [Figure 6] FIG. 11 is a diagram showing an example of the device configuration of an image processing apparatus according to a third embodiment. [Figure 7] FIG. 13 is a flowchart showing an example of an overall processing procedure in the third embodiment. [Figure 8] FIG. 13 is a flowchart showing an example of an overall processing procedure in the fourth embodiment. [Figure 9] FIG. 13 is a diagram showing an example of the device configuration of an image processing apparatus according to a fifth embodiment. [Figure 10] FIG. 13 is a flowchart showing an example of an overall processing procedure in the fifth embodiment. [Figure 11] FIG. 13 is a diagram showing an example of the device configuration of an image processing apparatus according to a sixth embodiment. [Figure 12] FIG. 23 is a flowchart showing an example of an overall processing procedure in the sixth embodiment. [Figure 13] FIG. 23 is a diagram showing an example of the device configuration of an image processing apparatus according to the seventh embodiment. [Figure 14] FIG. 23 is a flowchart showing an example of an overall processing procedure in the seventh embodiment. [Figure 15] 23A and 23B are diagrams showing examples of deviations in discretization positions in the seventh embodiment. [Figure 16] FIG. 23 is a flowchart showing an example of a processing procedure of an image processing device according to the eighth embodiment. [Figure 17] 23A to 23C are views for explaining an example of a method for setting a comparison region in the eighth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, preferred embodiments of the image processing device according to the disclosure of this specification will be described in detail with reference to the accompanying drawings. However, the scope of the invention is not limited to the illustrated examples. EXAMPLES

[0010] First Embodiment The image processing device according to this embodiment is a device that generates a three-dimensional difference image between a plurality of three-dimensional images (a first image and a second image). In order to calculate the difference in the details between the images, the image processing device according to this embodiment obtains a first converted image and a second converted image by converting the resolution of each of the first image and the second image so that the pixel size (voxel size) is different from that of the original image. Then, a corresponding position on the second converted image corresponding to the position of interest on the first converted image is obtained, and a comparison region is set on the second converted image centered on the corresponding position. At this time, the size of the comparison region is determined based on the pixel size of each of the first image and the second image before the resolution is converted, utilizing the fact that the position of the pixel that most reflects the original imaging signal is shifted by a maximum of half a pixel size due to the shift in the discretization position between the images to be compared. Then, the difference of the position of interest is calculated based on the density value of the position of interest on the first converted image and the density values ​​of a plurality of pixels in the comparison region set around the corresponding position on the second converted image, and a three-dimensional difference image is generated in which the value is set as the density value of the position of interest on the three-dimensional difference image. In this way, by calculating the difference value from a comparison region of the minimum necessary size, the user can observe a 3D difference image in which noise due to the shift in discretization position is reduced while minimizing the elimination of signals necessary for diagnosis, such as differences due to changes over time. The configuration and processing of this embodiment will be described below with reference to Figs. 1 to 4.

[0011] Fig. 1 shows the configuration of an image diagnostic system according to this embodiment. As shown in the figure, an image processing device 100 in this embodiment is connected to a data server 110 and a display unit 120. The image diagnostic system may include a modality (imaging device), and an image captured by the modality may be transmitted to the image processing device without going through the data server. In this case, the data server may not be included in the system.

[0012] The data server 110 holds a first image and a second image designated by a user as targets for generating a difference image. The first image and the second image are three-dimensional tomographic images (volume data) obtained by imaging a subject in advance with the same modality under different conditions (date and time, contrast conditions, imaging parameters, etc.). The modality for imaging the three-dimensional tomographic images may be an MRI device, an X-ray CT device, a three-dimensional ultrasound imaging device, a photoacoustic tomography device, a PET / SPECT, an OCT device, etc. In addition, the first image and the second image may be images of the same patient captured with the same modality and in the same position at different dates and times for follow-up observation, or may be images of the same patient captured with different contrast conditions or different imaging parameters. In addition, they may be images of different patients, or an image of the patient and a standard image. The first image and the second image are input to the image processing device 100 via the data acquisition unit 1010.

[0013] The display unit 120 is a monitor that displays an image generated by the image processing device 100. Specifically, the display unit 120 is a monitor that displays a difference image generated using the calculated difference value as a density value.

[0014] The image processing device 100 is composed of the following components. The data acquisition unit 1010 acquires a first image and a second image input to the image processing device 100. The converted image acquisition unit 1020 acquires a first converted image and a second converted image obtained by converting the resolution of the first image and the second image, respectively. The deformation information acquisition unit 1030 acquires deformation information representing the correspondence relationship between the positions on the first converted image and the second converted image. The comparison area size determination unit 1040 determines the size of the comparison area based on the pixel sizes of the first image and the second image. The position acquisition unit 1050 acquires a focus position on the first converted image, and acquires a corresponding position on the second converted image that corresponds to the focus position on the first converted image, using the deformation information acquired by the deformation information acquisition unit 1030. The comparison area setting unit 1060 sets a comparison area having the size of the comparison area around the corresponding position on the second converted image. The combination determination unit 1070 determines a combination of the density value of the focus position on the first converted image and the density values ​​of multiple positions in the comparison area on the second converted image as targets for comparison processing (calculation of differences). The difference calculation unit 1080 calculates a difference value of the focus position based on the combination of density values ​​determined by the combination determination unit 1070, i.e., the density value of the focus pixel on the first converted image and the density values ​​of multiple pixels in the comparison area on the second converted image. The difference image generation unit 1090 generates a difference image in which the calculated difference value is the density value of the focus position. The display control unit 1100 performs display control to display the first image, the second image, and the difference image side by side on the display unit 120.

[0015] FIG. 2 is a flowchart showing the overall processing procedure performed by the image processing device 100.

[0016] (S2000) (Data Acquisition) In step S2000, the data acquisition unit 1010 acquires the first image and the second image input to the image processing device 100. Then, the data acquisition unit 1010 outputs the acquired first image and the second image to the converted image acquisition unit 1020. In addition, the data acquisition unit 1010 outputs information on the pixel sizes of the first image and the second image to the comparison region size determination unit 1040.

[0017] (S2010) (Acquisition of converted image) In step S2010, the converted image acquisition unit 1020 acquires a first converted image obtained by converting the resolution of the first image so that the pixel size is different, and a second converted image obtained by converting the resolution of the second image so that the pixel size is different. For example, when the pixel size of the original image is anisotropic, an image with an isotropic pixel size is acquired so that the image alignment performed in the subsequent processing can be performed with high accuracy. For example, when the first image and the second image are general CT images, the resolution in the slice plane is high relative to the distance between the slices, so a process of upsampling pixels in the inter-slice direction according to the resolution in the slice plane is performed. Similarly, when the pixel sizes of the first image and the second image do not match, a process of converting the resolution of at least one of the images to make the pixel sizes of the respective images uniform is performed. Usually, the resolution is converted to be uniform to the image with the higher resolution. Then, the generated converted image is output to the deformation information acquisition unit 1030, the position acquisition unit 1050, the comparison area setting unit 1060, the combination determination unit 1070, and the difference calculation unit 1080.

[0018] In addition, if resolution conversion processing is not required (for example, if the pixel sizes of the first image and the second image are isotropic and equal), this step is not performed, and the original image is treated as a converted image and subsequent processing is performed.

[0019] In this embodiment, a known image processing method can be used for interpolating density values ​​during resolution conversion, such as nearest neighbor interpolation, linear interpolation, or cubic interpolation.

[0020] (S2020) (Acquisition of deformation information) In step S2020, the deformation information acquisition unit 1030 acquires deformation information so that pixels representing the same part between the first converted image and the second converted image are approximately the same. That is, a registration process (deformation estimation process) is performed between the first converted image and the second converted image. Then, the acquired deformation information is output to the position acquisition unit 1050. That is, the deformation information acquisition unit 1030 acquires deformation information between the reference image and the second converted image when the first converted image is used as the reference image.

[0021] In this embodiment, the deformation information is obtained by a known image processing method. For example, the deformation information is obtained by deforming one image so that the image similarity between the images after deformation is high. As the image similarity, a known method such as the commonly used Sum of Squared Difference (SSD), mutual information, or cross-correlation coefficient can be used. As a model of image deformation, a deformation model based on a radial basis function such as Thin Plate Spline (TPS), or a known deformation model such as Free Form Deformation (FFD) or Large Deformation Diffeomorphic Metric Mapping (LDDMM) can be used. Note that, when only a difference in position and orientation exists between the first image and the second image (can be approximated in this way), rigid registration between the images may be performed, and transformation parameters of the position and orientation may be obtained as deformation information. Also, affine transformation parameters between the images may be obtained as deformation information. Also, when there is no positional deviation between the images (can be approximated in this way), the processing of this step is unnecessary.

[0022] (S2030) (Determining the size of the comparison area) In step S2030, the comparison region size determination unit 1040 determines the size of the comparison region used to calculate the difference value based on the pixel size of the first image and the pixel size of the second image, and outputs the determined size of the comparison region to the comparison region setting unit 1060.

[0023] In this embodiment, the size of the comparison region is determined by utilizing the property that the pixel position at which the original imaging signal of the subject is most reflected between the first converted image and the second converted image shifts by a maximum of the sum of the half pixel sizes of each original image due to the shift in the discretization position when generating the first image and the second image. In other words, the sum of the half pixel sizes of each of the first image and the second image is determined as the size of the comparison region.

[0024] FIG. 3 is a diagram for explaining how a shift occurs in the observed values ​​of the same part of a subject due to a shift in the discretization position between images. In FIG. 3(a), graphs 3000 and 3040 show how the imaging signals appear when the imaging positions of the subject relative to the modalities are shifted in opposite directions, with the vertical axis showing the signal value when the subject is imaged by the modality and the horizontal axis showing the position in the x-axis direction. 3020 and 3060 are signals acquired by imaging the same subject, and 3010 and 3050 shown by dotted lines show the same position on the x-axis. Here, 3010 and 3050 are signals when images are taken at the same position, and this position is referred to as the reference position for convenience. FIG. 3(a) shows that when images are generated from signals 3020 and 3060 acquired from the same subject, the respective discretization positions are shifted in different directions relative to the reference position. Furthermore, the equally spaced lines 3030 in FIG. 3(a) are the boundary positions of discretization, and when generating an image, the signals indicated by 3020 and 3060 are combined in the area separated by the line to generate one pixel.

[0025] In Fig. 3(b), graph 3070 shows pixel information generated by discretizing signal 3020 in Fig. 3(a), with the vertical axis representing density value and the horizontal axis representing position in the x-axis direction. For example, pixel 3080 in Fig. 3(b) is a pixel generated from an area containing a large amount of signal 3020, and shows a large density value. Similarly, in Fig. 3(b), graph 3090 shows pixel information generated by discretizing signal 3060, with the vertical axis representing density value and the horizontal axis representing position in the x-axis direction. At this time, as described above, the discretization positions of signals 3020 and 3060 are shifted in different directions from each other, so the density values ​​at the same position are different between graphs 3070 and 3090.

[0026] In FIG. 3(c), graphs 3100 and 3120 respectively represent the density values ​​and positions of pixels obtained by converting the resolution of the pixels represented by graphs 3070 and 3090 in FIG. 3(b). That is, graphs 3070 and 3090 can be regarded as the first image and the second image, and graphs 3100 and 3120 can be regarded as the signal value graphs of the first converted image and the second converted image. In this case, pixels 3110 and 3130 are pixels that most closely reflect the signals 3020 and 3060 of the subject, respectively. When the signals 3020 and 3060 are shifted in opposite directions, the shift of the discretized positions of the signals relative to the reference positions 3010 and 3050 is at most half the pixel size of the original image. When the signals 3020 and 3060 are shifted in opposite directions, respectively, by half a pixel size, the shift between the pixels 3110 and 3130 is the sum of the respective half pixel sizes.

[0027] In FIG. 3, a one-dimensional graph in only the x-axis direction is used to simplify the illustration, but in an actual three-dimensional image, the discretization position may shift in each of the x-, y-, and z-axis directions, so the size of the comparison region is determined based on the pixel size in each axial direction. In addition, since the resolution in a slice (=pixel size in the x- and y-directions) is often sufficient in a general CT image, noise reduction may not be performed in the x- and y-directions. In this case, the size of the comparison region in the x- and y-axis directions may be set to 0, and only the size of the comparison region in the z-axis direction may be determined by the above method. Also, the size of the comparison region in the x- and y-axis directions may be set to a predetermined fixed value (for example, 1 mm), and only the size of the comparison region in the z-axis direction may be determined by the above method. This can speed up the calculation.

[0028] In this embodiment, the size of the comparison region is the sum of the half pixel sizes of the first image and the second image, but the sum of the pixel sizes of the first image and the second image may be multiplied by a predetermined constant (for example, an expected value of the discretization position shift), or a predetermined constant may be added. The predetermined constant may be changed based on a method for aligning the first image and the second image. For example, when alignment is performed so that the difference in density value between the images is reduced, the pixel position shift due to the discretization position shift may be corrected, and the positions of pixels representing the same part between the images may become closer. Therefore, the predetermined constant may be reduced, and a value smaller than the maximum value of the discretization position shift may be used as the size of the comparison region. This reduces the size of the comparison region, and since an unnecessary range is not searched, the processing speed and accuracy can be improved. Also, a value mapped by a predetermined nonlinear function with the pixel sizes of the first image and the second image as input variables may be used as the size of the comparison region. Also, the size of the comparison region may be determined based on the pixel size of only one of the first image and the second image. For example, the size of the comparison area may be determined based only on the pixel size of the first image, which is the reference image. Alternatively, the size of the comparison area may be determined based on the pixel size of the first image or the second image, whichever has a larger pixel size. In this case, too, the size of the comparison area may be determined by multiplying the pixel size to be used by a predetermined constant.

[0029] Moreover, in a registration method that reduces the distance between corresponding positions (feature points) between images instead of the difference in density values, the pixel position shift due to the discretization position shift is not necessarily reduced. In general, the registration accuracy is high near the feature points between images used for registration, and the further away from the feature points, the lower the registration accuracy. When the registration accuracy is low, the pixel position shift between images may become large due to the addition of registration errors to the discretization position shift. In such a case, the predetermined constant may be changed for each position on the image according to the distance from the feature point on the image. For example, the predetermined constant may be made small at positions near the feature points on the image, and made large at positions away from the feature points.

[0030] (S2040) (Getting location) In step S2040, the position acquisition unit 1050 acquires a position of interest on the first converted image (position of interest on the reference image), and acquires a corresponding position on the second converted image corresponding to the position of interest using the deformation information acquired in step S2020. That is, the position acquisition unit 1050 corresponds to an example of a position acquisition means that acquires a position of interest on one image and a corresponding position on the other image that corresponds to the position of interest. Then, the position acquisition unit 1050 outputs the acquired position to the comparison area acquisition unit 1060, the combination determination unit 1070, and the difference calculation unit 1080.

[0031] (S2050) (Setting comparison area) In step S2050, the comparison area setting unit 1060 sets a comparison area having the size determined in step S2030 around the corresponding position on the second converted image. Then, information on the set comparison area is output to the combination determination unit 1070.

[0032] FIG. 4 is a diagram for explaining a comparison region set on a converted image. In FIG. 4, graphs 3100 and 3120 respectively show the same graphs as graphs 3100 and 3120 in FIG. 3(c). Here, an example is shown in which the pixel size in the x-axis direction is 5 mm in both the first image and the second image, and upsampling is performed so that the pixel size is 1 mm. In this case, the size of the comparison region in the x-axis direction is the sum of the half pixel sizes of the first image and the second image, so it is 2.5 mm + 2.5 mm = 5 mm. In FIG. 4, it is assumed that pixel 3110 on the first converted image is set as the target position, and the corresponding position (calculated based on the deformation information) on the second converted image is pixel 4030. In this case, 4040 shows a comparison region of size 5 mm set at pixel 4030, which is the corresponding position. Considering the case where the discretization position is shifted by a maximum of 5 mm in the x-axis direction, a comparison region of 5 mm is set in each of the +x and -x directions centered on pixel 4030. Here, only the x-axis direction has been described to simplify the illustration, but in an actual 3D image, the comparison region is a rectangle whose size is determined based on the pixel size in each of the x-, y-, and z-axis directions.

[0033] (S2060) (Decision of combination) In step S2060, the combination determination unit 1070 determines a combination of density values ​​to be subjected to the comparison process (calculation of difference). First, the combination determination unit 1070 interpolates the density value of the attention position on the first converted image acquired in step S2040 and the density value of the pixel in the comparison area on the second converted image. A known image processing method can be used for the interpolation of the density value. For example, nearest neighbor interpolation, linear interpolation, cubic interpolation, etc. can be used. Also, interpolation is not necessarily required. Note that the combination determination unit 1070 may not interpolate the density value of the attention position on the first converted image, but may interpolate the density value of the pixel in the comparison area on the second converted image. The combination determination unit 1070 may determine a combination of density values ​​such that the difference between the density value of the attention position on the first converted image and the density values ​​of all pixels in the comparison area on the second converted image is calculated. The combination determination unit 1070 may also sample at least one pixel from among the pixels included in the comparison region, and determine the combination of the density value of the pixel and the density value of the attention position as the combination to be calculated for the difference. For example, the combination determination unit 1070 samples the maximum density value and the minimum density value from among the pixels included in the comparison region. Then, the combination of the maximum density value included in the comparison region and the density value of the attention position and the combination of the minimum density value included in the comparison region and the density value of the attention position are determined as the combination to be calculated for the difference. Note that the density values ​​to be sampled are not limited to the maximum and minimum, and three or more values ​​may be sampled, or a single value such as the maximum density value or the minimum density value may be sampled. Alternatively, a density range with the maximum density value and the minimum density value in the comparison region as both ends (upper limit and lower limit) may be obtained, and the density value of the attention position and the density range in the comparison region may be obtained as the combination to be calculated for the difference. Note that the density range in the comparison region may be other than the maximum and minimum density values. For example, it may be the maximum and minimum values ​​after removing outliers of the density values.

[0034] The combination determination unit 1070 outputs information indicating the determined combination of density values ​​to be used for calculating the difference to the difference calculation unit 1080. The information indicating the combination of density values ​​output by the combination determination unit 1070 may be information indicating all combinations of density values ​​of the focus position on the first converted image and density values ​​of pixels in the comparison region on the second converted image, or may output only information indicating combinations of density values ​​of pixels sampled from among the pixels included in the comparison region and density values ​​of the focus position.

[0035] (S2070) (Calculation of the difference value) In step S2070, the difference calculation unit 1080 obtains a difference value to be given to the difference image based on a combination of the density value of the attention position on the first converted image determined in step S2060 and the density value in the comparison area on the second converted image. The difference calculation unit 1080 calculates the difference between the density value of the attention position on the reference image and each of the density values ​​of multiple positions in the comparison area on the second converted image, or the difference between the density value of the multiple positions and the position having the closest density value. Then, it outputs the result to the difference image generation unit 1090.

[0036] 4, by calculating the difference between the density value of pixel 3110 of the first converted image and each density value in comparison region 4040 on the second converted image, the difference value between pixel 3110 of the first difference image and pixel 3130 of the second converted image with the minimum difference is obtained. That is, it is possible to calculate the difference value of the density values ​​between pixels that best reflects the signal of the subject in FIG. 3.

[0037] In this embodiment, the pixels in the comparison region on the second converted image for which the difference with the density value of the position of interest on the first converted image is calculated may be all pixels output from the combination determination unit 1070. Alternatively, they may be pixels obtained by sampling the pixels output from the combination determination unit 1070 at a predetermined interval, or pixels obtained by randomly sampling a predetermined number of pixels. They may also be pixels in a spherical region inscribed in the comparison region. This reduces the number of times the difference is calculated, and the processing can be speeded up.

[0038] As another method of using the difference between the density value of the target position on the first converted image and the density value of each pixel in the comparison region on the second converted image, the average value of the differences or the second smallest difference may be calculated instead of the minimum value of the differences and used as the difference value of the difference image. This may leave more noise than when the minimum value of the differences is obtained. However, on the other hand, although the difference between the target pixel on the first converted image on the second converted image is small, it is possible to prevent the difference between the pixel at a non-corresponding position (such as an artifact or a pixel at another site) from being obtained as the minimum value. This makes it possible to prevent the difference value from being significantly smaller than the difference between the pixel at the original corresponding position.

[0039] Also, the difference value may be obtained by calculating distribution information of density values ​​in the comparison area on the second converted image and comparing the distribution information with the density value of the target position on the first converted image. For example, when the density range in the comparison area is acquired in step S2060, the difference value may be obtained by comparing the density range with the density value of the target position on the first converted image. For example, the difference value may be set to 0 when the density value of the target position is included in the density range in the comparison area. Also, the difference value to be given to the difference image may be the difference value from the maximum value (upper limit value) when the density value of the target position is greater than the maximum value (upper limit value) of the density range, or the difference value from the minimum value (lower limit value) when the density value of the target position is smaller than the minimum value (lower limit value) of the density range. In this case, the density range in the comparison area on the second converted image represents a range in which the density value of the target position of the first converted image can change depending on the difference in the discretization position. Therefore, even if the density values ​​of the same part between images do not match perfectly due to the effects of discretization and a small difference remains, the difference can be set to zero as long as it is within the range that can change due to differences in the discretization position, thereby further reducing noise.

[0040] However, when the comparison region includes pixels whose density values ​​differ greatly due to a lesion or artifact, the difference between the maximum and minimum values ​​of the density values ​​in the comparison region becomes large, and the difference at the attention position may be erroneously set to 0. Therefore, the difference may be set to 0 only when the density value of the attention position is between the maximum and minimum values ​​of the density values ​​in the comparison region and the difference between the maximum and minimum values ​​of the density value of the attention position is equal to or less than a threshold value. Alternatively, the distribution of density values ​​in the comparison region may be classified into multiple clusters, and the same processing as above may be performed based on a comparison between the minimum and maximum values ​​of each cluster. That is, if the density value of the attention position is within a cluster, the difference value may be set to 0, and if it is outside the cluster, the difference value may be set to the (signed) distance from the nearest cluster. Note that the classification of density values ​​in the comparison region may be performed based only on the density value, or may be performed based on the pixel position and density value. In the former case, for example, a clustering process may be performed on the histogram of density values ​​in the comparison region. In the latter case, for example, clustering may be performed by performing area division process on the comparison region based on the continuity of density values ​​between pixels.

[0041] In this embodiment, the comparison area may be set not on the second converted image but around the corresponding position on the original second image, and the difference between the density value of the target position on the first converted image and the density value in the comparison area on the second image may be calculated. In this case, density values ​​of multiple positions in the comparison area may be obtained at intervals smaller than the pixel size. The density values ​​of these positions are obtained by interpolating from the surrounding density values. If the interpolation method is the same as when the second converted image was obtained in step S2010, it is possible to calculate a difference value equivalent to that when the comparison area is set on the second converted image.

[0042] Alternatively, the difference value calculated based on the density value of the position of interest on the first converted image and the density value of each pixel in the comparison region on the second converted image as described above may be used as the first difference value, and the difference (second difference value) between the density value of the position of interest on the first converted image and the density value of the corresponding position on the second converted image may be calculated separately, and the difference value to be given to the difference image may be calculated based on the first difference value and the second difference value. For example, the weighted average value of the first difference value and the second difference value may be used as the difference value of the difference image. This reduces the risk of erasing signals that are not noise.

[0043] (S2080) (Change focus?) In step S2080, the position acquisition unit 1050 determines whether or not the difference values ​​at all positions (all pixels) on the first converted image have been calculated. If the difference values ​​at all positions have been calculated, the process proceeds to step S2090. On the other hand, if the difference values ​​at all positions have not been acquired, the process returns to step S2040.

[0044] In this embodiment, the difference values ​​are calculated not only for all positions on the first converted image, but also for some positions on the first converted image extracted in advance by a known image processing technique, thereby reducing the processing time required for noise reduction.

[0045] (S2090) (Generation of difference image) In step S2090, the difference image generating unit 1090 generates a difference image (first difference image) in which the difference value at each position on the first converted image is used as the density value. Then, the obtained difference image is stored in the data server 110. Alternatively, it may be stored in a memory in the image processing device 100. Also, it is output to the display control unit 1100. Note that a general difference image (second difference image) in which the second difference value calculated in step S2060 (the difference between the density value of the target position on the first converted image and the density value of the corresponding position on the second converted image) is used as the density value may also be generated.

[0046] (S2100) (display of difference image) In step S2100, the display control unit 1100 performs control to display on the display unit 120 the difference image (first difference image) generated in step S2090.

[0047] As an example of the display, for example, one screen may be divided vertically or horizontally to display the first image, the second image, and the difference image side by side. Also, a difference image (first difference image) drawn in a color different from the first image or the second image may be displayed by superimposing it, or only one of the first image, the second image, and the difference image may be selected and displayed (freely switched to the same position). Also, one of the images may be enlarged or reduced to match the resolution of the other image, or they may be displayed side by side so that the corresponding position of the second image corresponding to one focus position on the first image and the focus position of the difference image are aligned. Also, the first difference image and the second difference image may be displayed by switching them.

[0048] In this manner, the processing of the image processing device 100 is carried out.

[0049] As a result, by calculating the difference value from a comparison area of ​​the minimum necessary size taking into account the shift in the discretization position, the user can observe a difference image in which the necessary signals are retained in the difference image and noise resulting from differences in density values ​​due to the shift in the discretization position between images is reduced.

[0050] (Modification 1-1) (Calculating image similarity taking into account discretization position shift) In this embodiment, when calculating the difference between pixels of interest, a method of setting a comparison region of a size determined based on the pixel size around the pixels and using the density value within the region is used to reduce noise when generating a difference image. However, this method can also be used in other situations where comparison between pixels of interest is performed. For example, in step S2020, the deformation information acquisition unit 1030 acquires image similarity using a known image processing method, but this method can also be used in the process of acquiring image similarity for image registration. That is, when calculating the difference in density values ​​of a pixel pair between images as in SSD, the pixel pair may be set as a target position and a corresponding position, and the difference value may be calculated by the same process as steps S2050, S2060, and S2070. In the registration process in which the deformation information is repeatedly optimized so that the image similarity is high, the image similarity acquired is evaluated based on the difference value calculated by the same step as the noise-reduced image finally observed by the user at each optimization step. This makes it possible to calculate image similarity taking into account the shift in discretization position, and as a result, a difference image with reduced noise can be acquired.

[0051] (Modification 1-2) (Reducing noise at a position specified by the user) In this embodiment, in step S2080, all positions (all pixels) on the first converted image or some positions extracted in advance by a known image processing technique are selected, but the user may specify the positions. That is, the generation process of a difference image with reduced noise may be performed for all positions or some positions in an area specified in advance by the user. Also, only the second difference image may be generated and displayed, and the process of steps S2040 to S2090 may be performed only on the area near the attention position interactively specified by the user, and only the area near the attention position may be replaced with the first difference image and displayed. This reduces noise only at the minimum necessary positions, thereby reducing the time required for noise reduction. Furthermore, positions that the user determines are not noise can be excluded from the target of noise reduction process, so that it is possible to prevent the signal from being erased too much.

[0052] <Second embodiment> The image processing device according to this embodiment is a device that generates a three-dimensional difference image between a first image and a second image, similar to the first embodiment. The image processing device according to this embodiment is characterized in that it judges whether or not to execute noise reduction processing according to the pixel size of the input image, and generates a three-dimensional difference image by a method according to the judgment. The image processing device according to this embodiment determines the size of the comparison region based on the pixel sizes of the first image and the second image, similar to the first embodiment. At this time, if the pixel sizes of the first image and the second image are less than a predetermined threshold, it is judged that the deviation of the discretization position is small, and a difference image is generated without performing noise reduction processing. On the other hand, if the pixel size is equal to or greater than a predetermined threshold, a difference image in which noise reduction processing has been performed is generated, similar to the first embodiment. This makes it possible to suppress excessive erasure of the density value difference between images when the deviation of the discretization position is small. In addition, the processing time required for noise reduction can be shortened. Hereinafter, the configuration and processing of this embodiment will be described with reference to FIG. 1 and FIG. 5.

[0053] The configuration of the image processing device according to this embodiment is the same as that of the first embodiment. However, the comparison region size determination unit 1040 and the difference calculation unit 1080 have different functions from those of the first embodiment, and therefore their functions will be described below. The other components have the same functions as those of the first embodiment, and therefore their description will be omitted.

[0054] The comparison region size determination unit 1040 determines whether or not to perform noise reduction processing based on the pixel sizes of the first image and the second image. Also, similar to the first embodiment, the size of the comparison region is determined based on the pixel sizes of the first image and the second image. When noise reduction processing is not performed, the difference calculation unit 1080 calculates the difference value between the density value of the target position on the first converted image and the density value of the corresponding position on the second converted image as the difference value of the target position. On the other hand, when noise reduction processing is performed, the same processing as in the first embodiment is performed.

[0055] Fig. 5 shows a flowchart of the overall processing procedure performed by the image processing device 100. Steps S5000 to S5020 and S5030 to S5100 are similar to steps S2000 to S2020 and S2030 to S2100 in the first embodiment, respectively, and therefore will not be described. Only the differences from the flowchart in Fig. 2 will be described below.

[0056] (S5025) (Do you perform noise reduction processing?) In step S5025, the comparison region size determination unit 1040 determines whether or not to perform noise reduction processing based on the pixel sizes of the first and second images.

[0057] Here, if the pixel sizes of both the first image and the second image are less than a predetermined threshold, it is determined that the discretization position deviation is small, it is determined that noise reduction is not required, and the process proceeds to step S5100. On the other hand, if the pixel size is equal to or greater than the predetermined threshold, the process proceeds to step S5030, and noise reduction processing is performed similarly to the first embodiment. For example, the threshold is set to a value according to the lesion size or the resolution of the modality, or a value previously determined by the user.

[0058] In this embodiment, the decision as to whether or not to perform noise reduction processing is made based on the pixel size of each of the first image and the second image, but the decision may be made based on the sum of the pixel sizes of each of the first image and the second image. The predetermined threshold may be different values ​​for each of the x, y, and z axis directions of the image. The necessity of noise reduction may be determined for each axis, and the implementation or non-implementation of noise reduction processing may be controlled for each axis. For example, if the pixel size in the x and y axis directions of each of the first image and the second image is less than the threshold and the pixel size in the z axis direction is equal to or greater than the threshold, it may be determined that noise reduction is unnecessary in the x and y axis directions, and the size of the comparison region may be set to 0, and it may be determined that noise reduction is necessary only in the z axis direction, and the size of the comparison region may be determined in the same manner as in the first embodiment. Then, if it is determined that noise reduction is unnecessary in all three axis directions, the process proceeds to step S5100, and otherwise the process proceeds to step S5030.

[0059] In addition, since the resolution within a slice (= pixel size in the x and y directions) is often sufficient in general CT images, it is possible to always not perform noise reduction in the x and y directions without making a judgment based on the image size. In other words, it is only necessary to judge whether or not to perform noise reduction in the z direction based on the slice interval (= pixel size in the z direction) of the input image. In this way, it is possible to determine that noise reduction should not be performed if the input image is thin sliced, and that noise reduction should be performed if the input image is thick sliced.

[0060] (S5110) (Calculation of the difference value of the corresponding position) In step S5110, the difference calculation unit 1080 calculates the difference value (the second difference value in the first embodiment) between the density values ​​of corresponding positions between the first converted image and the second converted image. At this time, the corresponding positions between the images are obtained by using the deformation information in the same manner as in step S5040.

[0061] According to this embodiment, by determining whether or not noise reduction processing is required depending on the pixel size, when the pixel size of the input image is sufficiently small and the noise due to discretization is small, unnecessary calculations can be omitted. Also, compared to the first embodiment, there is an effect of preventing excessive erasure of the original difference value.

[0062] <Third embodiment> The image processing device according to this embodiment is a device that generates a three-dimensional difference image between a first image and a second image, similar to the first embodiment. The image processing device according to this embodiment is characterized in that it generates a three-dimensional difference image with reduced noise by using a deformation comparison area in which a comparison area is projected onto a deformation image that has been deformation-aligned so that identical parts between the images are approximately aligned. The image processing device according to this embodiment, like the first embodiment, acquires a first converted image and a second converted image in which the first image and the second image are respectively converted so that their resolutions are different from those of the original images. Then, the image processing device sets a comparison area around a corresponding position on the second converted image that corresponds to a position of interest on the first converted image. Then, using deformation information, it projects a comparison area onto a second deformation-aligned image acquired by deformation-aligning the second converted image so that the density values ​​of each pixel are similar to those of the first converted image. Then, the difference of the attention position is calculated based on the density value of the attention position on the first transformed image and the density values ​​of a plurality of pixels in a transformation comparison region set around the corresponding position on the second transformed transformed image, and a 3D difference image is generated with the calculated value as the density value of the attention position on the 3D difference image. Since it is possible to obtain a transformed image and a difference image of the second image in which the positions of the same parts on the first image and the second image are approximately the same, by displaying these images side by side, the user can easily confirm which position of the density value of the first image and the transformed image the difference value on the difference image was calculated from. Hereinafter, the configuration and processing of this embodiment will be described with reference to Figs. 6 and 7.

[0063] 6 shows the configuration of an image diagnostic system according to this embodiment. Here, the data server 110 and the display unit 120 are the same as those in the first embodiment, and therefore their explanations are omitted. The image processing device 600 is composed of the following components. The data acquisition unit 1010, the converted image acquisition unit 1020, the deformation information acquisition unit 1030, the comparison region size determination unit 1040, the position acquisition unit 1050, the comparison region setting unit 1060, the difference image generation unit 1090, and the display control unit 1100 have the same functions as those in the first embodiment, and therefore their explanations are omitted.

[0064] The deformed image acquisition unit 1610 acquires a second deformed and transformed image by deforming the second transformed image using the deformation information acquired by the deformation information acquisition unit 1030. The comparison area projection unit 1620 acquires a deformed comparison area by projecting the comparison area set by the comparison area setting unit 1060 on the second transformed and transformed image using the deformation information acquired by the deformation information acquisition unit 1030. The combination determination unit 1070 determines a combination of the density value of the attention position on the first transformed image and the density values ​​of multiple positions in the comparison area on the second transformed image as targets for comparison processing (calculation of difference). The difference calculation unit 1080 calculates a difference value of the attention position based on the combination of density values ​​determined by the combination determination unit 1070, that is, the density value of the attention pixel on the first transformed image and the density values ​​of multiple pixels in the comparison area on the second transformed image. FIG. 7 shows a flowchart of the overall processing procedure performed by the image processing device 600. Steps S7000 to S7050 and S7080 to S7100 are similar to steps S2000 to S2050 and S2080 to S2100 in the first embodiment, respectively, and therefore will not be described below. Only the differences from the flowchart in FIG.

[0065] (S7052) (Acquisition of deformation image) In step S7052, the deformed image acquisition unit 1610 acquires a second deformed and transformed image by deforming the second transformed image using the deformation information acquired in step S7020. Then, the acquired second deformed and transformed image is output to the comparison area projection unit 1720 and the difference calculation unit 1080.

[0066] (S7054) (Projection of comparison area) In step S7054, the comparison area projection unit 1620 projects the comparison area set on the second converted image in step S7050 onto the second transformed image as a transformed comparison area using the transformation information acquired in step S7020. Then, the comparison area projection unit 1620 outputs the transformed comparison area to the difference calculation unit 1080.

[0067] Here, the comparison area on the second transformed image to be projected may be the entire area within the comparison area, or may be multiple locations sampled from within the comparison area. When the entire area within the comparison area is projected, the entire area within the outline of the comparison area projected onto the second transformed image using the transformation information can be set as the transformed comparison area.

[0068] (S7060) (Decision of combination) In step S7060, the combination determination unit 1070 determines a combination of density values ​​to be subjected to the comparison process (calculation of the difference). First, the combination determination unit 1070 interpolates the density value of the attention position on the first converted image acquired in step S7040 and the density value of the pixel in the comparison area on the second converted image. A known image processing method can be used for the interpolation of the density value. For example, nearest neighbor interpolation, linear interpolation, cubic interpolation, etc. can be used. Also, the density value of the pixel in the comparison area on the second converted image does not necessarily need to be interpolated. A combination of density values ​​may be determined so that the difference between the density value of the attention position on the first converted image and the density values ​​of all pixels in the comparison area on the second converted image is calculated. Also, at least one pixel may be sampled from among the pixels included in the comparison area, and the combination of the density value of the pixel and the density value of the attention position may be set as the combination to be subjected to the calculation of the difference. For example, the combination determination unit 1070 samples the maximum density value and the minimum density value from among the pixels included in the comparison area. Then, a combination of the maximum density value included in the comparison region and the density value of the attention position, and a combination of the minimum density value included in the comparison region and the density value of the attention position are determined as combinations for which the difference is to be calculated. The density values ​​to be sampled are not limited to the maximum and minimum, and three or more values ​​may be sampled, or a single value such as the maximum density value or the minimum density value may be sampled. Alternatively, a density range having the maximum density value and the minimum density value in the comparison region as both ends (upper limit and lower limit) may be obtained, and the density value of the attention position and the density range in the comparison region may be obtained as a combination for which the difference is to be calculated. The density range in the comparison region may be other than the maximum and minimum density values. For example, it may be the maximum and minimum values ​​after removing outliers in the density values.

[0069] The combination determination unit 1070 outputs information indicating the determined combination of density values ​​to be used for calculating the difference to the difference calculation unit 1080. The information indicating the combination of density values ​​output by the combination determination unit 1070 may be information indicating all combinations of density values ​​of the focus position on the first converted image and density values ​​of pixels in the comparison region on the second converted image. Alternatively, the combination determination unit 1070 may output only information indicating combinations of density values ​​of pixels sampled from among the pixels included in the comparison region and density values ​​of the focus position.

[0070] (S7070) (Calculation of the difference value) In step S7070, difference calculation unit 1080 obtains a difference value to be given to the difference image based on a combination of the density value of the target position on the first converted image obtained in step S7060 and the density value in the deformation comparison area on the second transformed image projected in step S7054. The only difference from the process of step S2060 in the first embodiment is that the second converted image is changed to the second transformed image and the comparison area is changed to a deformation comparison area, and the other processes are the same.

[0071] In this manner, the processing of the image processing device 600 is carried out.

[0072] According to this embodiment, the same part between the deformed image of the second image in which the position of the same part on the first image and the image is approximately the same as that of the second image and the noise-reduced difference image can be easily compared and observed. Therefore, compared to the first embodiment, there is an advantage that the user can easily determine whether the difference value on the difference image is due to a lesion or not.

[0073] (Modification 3-1) (Calculating image similarity taking into account discretization position shift) As in the modified example 1-1 of the first embodiment, the image similarity may be obtained based on a difference value in which noise due to the shift in discretization position is reduced when calculating the image similarity. Here, the minimum value of the difference between the density value of the target position on the first transformed image and each density value in the deformation comparison area on the second transformed transformed image is used. This makes it possible to obtain an image similarity that takes into account the shift in discretization position, and as a result, a difference image with further reduced noise can be obtained.

[0074] <Fourth embodiment> The image processing device according to this embodiment is a device that generates a difference image between three-dimensional images, similar to the first embodiment. The image processing device according to this embodiment is characterized in that it sets a comparison area at both the position of interest in the first converted image and the corresponding position in the second converted image, and calculates a difference value at the position of interest based on the density value of pixels in each comparison area. Here, similar to the first embodiment, the direction in which a comparison area is set on the second converted image and a difference is calculated from the position of interest on the first converted image is defined as a forward direction. Also, the direction in which a comparison area is set on the first converted image and a difference is calculated from the corresponding position on the second converted image is defined as a reverse direction. The image processing device according to this embodiment calculates difference values ​​in the forward direction and the reverse direction at the position of interest on the difference image, and the representative difference value obtained by integrating the two difference values ​​is defined as the density value of the difference image to be generated. This makes it possible to leave a signal that cannot be captured by calculation in only one direction in the difference image. Hereinafter, the configuration and processing of this embodiment will be described with reference to FIG. 1 and FIG. 8.

[0075] The configuration of the image processing device according to this embodiment is the same as that of the first embodiment. However, the comparison area setting unit 1060, the combination determination unit 1070, and the difference calculation unit 1080 have different functions from those of the first embodiment, and therefore their functions will be described below. The other components have the same functions as those of the first embodiment, and therefore their description will be omitted.

[0076] The comparison area setting unit 1060 sets comparison areas each having the size of the comparison area around the position of interest on the first converted image and around the corresponding position on the second converted image. The combination determination unit 1070 determines a combination of the density value of the position of interest on the first converted image and the density values ​​of multiple positions in the comparison area on the second converted image as targets for comparison processing (calculation of differences). The difference calculation unit 1080 calculates the difference value in the forward direction and the difference value in the reverse direction based on the combination of density values ​​determined by the combination determination unit 1070, and obtains a representative difference value by integrating the two difference values.

[0077] Fig. 8 shows a flowchart of the overall processing procedure performed by the image processing device 100. Steps S8000 to S8040 and S8080 to S8100 are similar to steps S2000 to S2040 and S2080 to S2100 in the first embodiment, respectively, and therefore their explanations are omitted. Only the differences from the flowchart in Fig. 2 will be explained below.

[0078] (S8050) (Setting comparison area) In step S8050, the comparison region setting unit 1060 sets a first comparison region having the size of the comparison region determined in step S8030 around the position of interest on the first converted image. Similarly to step S2050 in the first embodiment, a second comparison region having the size of the comparison region determined in step S8030 is set around the corresponding position on the second converted image. Then, information on the set first comparison region and second comparison region is output to the combination determination unit 1070.

[0079] (S8060) (Determination of bidirectional combination) In step S8060, the combination determination unit 1070 interpolates the density value of the focus position on the first converted image acquired in step S8040 and the density value of the pixel in the comparison region on the second converted image to determine a combination (forward direction). Furthermore, the combination determination unit 1070 interpolates the density value of the corresponding position on the second converted image and the density value of each pixel in the first comparison region on the first converted image to determine a combination (reverse direction). This process is simply a case of exchanging the focus position and the corresponding position, and can be performed in the same manner as step S2060 in the first embodiment. Note that the various methods described in step S2060 can be used to determine the combination.

[0080] (S8070) (Calculation of bidirectional differential values) In step S8070, the difference calculation unit 1080 calculates a (forward) difference value at the target position based on a combination of the density value at the target position on the first converted image and each pixel in the second comparison region on the second converted image, similarly to step S2070 in the first embodiment. Furthermore, the difference calculation unit 1080 calculates a (reverse) difference value at the target position based on the density value at the corresponding position on the second converted image and each pixel in the first comparison region on the first converted image. This process is simply a case of exchanging the target position and the corresponding position, and can be performed in the same manner as step S2070 in the first embodiment. Note that the calculation of the difference value can use various methods described in step S2070.

[0081] (S8075) (Calculation of representative difference value) In step S8075, the difference calculation unit 1080 integrates the forward difference value and the backward difference value calculated in step S8070 to calculate a representative difference value. For example, the absolute values ​​of both are compared, and the difference value with the larger absolute value is obtained as the representative difference value. Then, the obtained representative difference value is output to the difference image generation unit 1080 as the density value of the difference image at the target position.

[0082] In the case of a signal from a small lesion that exists only in one of the first and second images, the difference value may be captured in either the forward or reverse direction, but not in the other direction. In some cases, the signal may disappear in the difference value in one direction, but by calculating a representative difference value using the difference values ​​in both directions, such difference values ​​can be left on the difference image.

[0083] In this embodiment, the difference value with the larger absolute value is set as the representative difference value, but the difference value with the smaller absolute value may be set as the representative difference value. Also, the average value of the forward difference value and the reverse difference value may be set as the representative difference value. This reduces the difference value with respect to a signal that exists only in one image, while further suppressing noise signals.

[0084] In this embodiment, the size of the comparison region does not necessarily have to be adaptively determined based on the pixel size of the input image. In other words, a comparison region size suitable for a typical pixel size may be set as a default value in advance and used. In this case, the comparison region size determination unit 1040 and the process of step S8030 are unnecessary.

[0085] This embodiment has the advantage of reducing the risk of erasing signals such as a small lesion that is present only in one of the images, or of a lesion being displayed smaller than its actual size, compared to the first embodiment.

[0086] <Fifth embodiment> The image processing device according to this embodiment is a device that generates a three-dimensional difference image between a plurality of three-dimensional images (a first image and a second image) in the same manner as in the first embodiment. In this embodiment, an example in which the present invention is implemented with a simpler configuration will be described. The configuration and processing of this embodiment will be described below with reference to Figs. 9 and 10.

[0087] 9 shows the configuration of an image diagnostic system according to this embodiment. The data server 110 and the display unit 120 have the same functions as those in the first embodiment, so a description thereof will be omitted.

[0088] The image processing device 900 is composed of the following components. The data acquisition unit 1010, the comparison region size determination unit 1040, the difference image generation unit 1090, and the display control unit 1100 have the same functions as those in the first embodiment, so their explanations are omitted. The functions of the other components will be explained below.

[0089] The deformation information acquisition unit 1030 acquires deformation information that indicates the correspondence relationship between positions on the first image and the second image. The position acquisition unit 1050 acquires a focus position on the first image, and acquires a corresponding position on the second image that corresponds to the focus position on the first image, using the deformation information acquired by the deformation information acquisition unit 1030. The comparison area setting unit 1060 sets a comparison area having a size of the comparison area around the corresponding position on the second image. The combination determination unit 1070 determines a combination of the density value of the focus position on the first converted image and the density values ​​of multiple positions in the comparison area on the second converted image as targets for comparison processing (calculation of difference). The difference calculation unit 1080 calculates a difference value of the focus position based on the combination of density values ​​determined by the combination determination unit 1070, i.e., the density value of the focus pixel on the first converted image and the density values ​​of multiple pixels in the comparison area on the second converted image.

[0090] Fig. 10 shows a flowchart of the overall processing procedure performed by the image processing device 900. Step S10100 performs the same process as step S2100 in the first embodiment, and therefore the explanation is omitted. Only the differences from the flowchart in Fig. 2 will be explained below.

[0091] (S10000) (Data Acquisition) In step S10000, data acquisition unit 1010 acquires the first image and the second image to be input to image processing device 900. Then, the acquired first image and second image are output to deformation information acquisition unit 1030, position acquisition unit 1050, comparison area setting unit 1060, combination determination unit 1070, and difference calculation unit 1080. In addition, information regarding the pixel sizes of the first image and the second image is output to comparison area size determination unit 1040.

[0092] (S10020) (Obtaining deformation information) In step S10020, the deformation information acquisition unit 1030 acquires deformation information so that pixels representing the same part between the first image and the second image are approximately the same. That is, it performs a registration process (deformation estimation process) between the first image and the second image. Then, it outputs the acquired deformation information to the position acquisition unit 1050.

[0093] In this embodiment, the deformation information can be obtained by a known image processing method, similarly to the first embodiment.

[0094] (S10030) (Determining the size of the comparison area) In step S10030, the comparison region size determination unit 1040 determines the size of the comparison region used to calculate the difference value based on the pixel size of the first image and the pixel size of the second image, and outputs the determined size of the comparison region to the comparison region setting unit 1060.

[0095] In this embodiment, as in the first embodiment, the property that the pixel position at which the original imaging signal of the subject is most reflected shifts by a maximum of the sum of the half pixel size of each original image due to the shift of the discretization position when generating the first image and the second image is utilized. In other words, the sum of the half pixel size of each of the first image and the second image is determined as the size of the comparison region.

[0096] (S10040) (Getting location) In step S10040, the position acquisition unit 1050 acquires a position of interest (pixel of interest) on the first image, and acquires a corresponding position on the second image that corresponds to the position of interest using the deformation information acquired in step S10020. The acquired position is then output to the comparison region setting unit 1060, the combination determination unit 1070, and the difference calculation unit 1080.

[0097] (S10050) (Setting comparison area) In step S10050, the comparison region setting unit 1060 sets a comparison region having the size determined in step S10030 around the corresponding position on the second image. Then, information about the set comparison region is output to the combination determination unit 1070.

[0098] (S10060) (Decision of combination) In step S10060, the combination determination unit 1070 determines a combination of density values ​​to be subjected to the comparison process (calculation of the difference). First, the combination determination unit 1070 interpolates the density value of the attention position on the first converted image acquired in step S10040 and the density value of the pixel in the comparison area on the second converted image. A known image processing method can be used for the density value interpolation. For example, nearest neighbor interpolation, linear interpolation, cubic interpolation, etc. can be used. Also, the density value of the pixel in the comparison area on the second converted image does not necessarily need to be interpolated. A combination of density values ​​may be determined so that the difference between the density value of the attention position on the first converted image and the density values ​​of all pixels in the comparison area on the second converted image is calculated. Also, at least one pixel may be sampled from among the pixels included in the comparison area, and the combination of the density value of the pixel and the density value of the attention position may be set as the combination to be subjected to the calculation of the difference. For example, the combination determination unit 1070 samples the maximum density value and the minimum density value from among the pixels included in the comparison area. Then, a combination of the maximum density value included in the comparison region and the density value of the attention position, and a combination of the minimum density value included in the comparison region and the density value of the attention position are determined as combinations for which the difference is to be calculated. The density values ​​to be sampled are not limited to the maximum and minimum, and three or more values ​​may be sampled, or a single value such as the maximum density value or the minimum density value may be sampled. Alternatively, a density range having the maximum density value and the minimum density value in the comparison region as both ends (upper limit and lower limit) may be obtained, and the density value of the attention position and the density range in the comparison region may be obtained as a combination for which the difference is to be calculated. The density range in the comparison region may be other than the maximum and minimum density values. For example, it may be the maximum and minimum values ​​after removing outliers in the density values.

[0099] (S10070) (Calculation of the difference value) In step S10070, the difference calculation unit 1080 obtains a difference value to be given to the difference image based on a combination of the density value of the position of interest on the first image determined in step S10060 and density values ​​of multiple positions in the comparison area on the second image. Then, the difference calculation unit 1080 outputs the difference value to the difference image generation unit 1090.

[0100] In the first embodiment, the difference value is calculated from the density values ​​of the reference image (the first image or the first converted image) and the second converted image, but in this embodiment, the difference value is calculated from the density values ​​of the first image and the second image in the same manner as in step S2070 of the first embodiment. That is, the difference between the density value of the target position on the first image and the density values ​​at each of the multiple positions in the comparison area on the second image is calculated, and the minimum value among them is obtained as the difference value to be given to the difference image. When obtaining density values ​​from multiple positions in the comparison area on the second image, the positions of all pixels in the comparison area may be set as the multiple positions, and density values ​​may be obtained from each pixel. Alternatively, measurement points at a predetermined interval finer than the pixel pitch may be set in the comparison area as the multiple positions in the comparison area, and the density values ​​at each measurement point may be obtained by interpolating the density values ​​of neighboring pixels.

[0101] (S10080) (Change focus?) In step S10080, the position acquisition unit 1050 determines whether or not the difference values ​​have been calculated at all positions (all pixels) on the first image. If the difference values ​​have been calculated at all positions, the process proceeds to step S10090. On the other hand, if the difference values ​​have not been acquired at all positions, the process returns to step S10040.

[0102] In this embodiment, the difference values ​​are not necessarily calculated for all positions on the first image, but may be calculated for some positions on the first image extracted in advance by a known image processing technique, thereby reducing the processing time required for noise reduction.

[0103] (S10090) (Generation of difference images) In step S10090, the difference image generating unit 1090 generates a difference image (first difference image) in which the difference value at each position (pixel) on the first image is used as the density value. Then, the obtained difference image is stored in the data server 110. It is also output to the display control unit 1100. Note that a general difference image (second difference image) in which the second difference value calculated in step S10070 (the difference between the density value at the position of interest on the first image and the density value at the corresponding position on the second image) is used as the density value may also be generated.

[0104] In this manner, the processing of the image processing device 900 is carried out.

[0105] As a result, it is possible to obtain the same effect as in the first embodiment without obtaining the first converted image and the second converted image. That is, by calculating the difference value from a comparison area of ​​the minimum necessary size considering the shift in the discretization position, the user can observe a difference image in which the necessary signals remain on the difference image and noise caused by the difference in density value due to the shift in the discretization position between the images is reduced. Note that each of the second to fifth embodiments can also be implemented without obtaining the first converted image and the second converted image, as in this embodiment.

[0106] Sixth Embodiment The image processing device according to this embodiment is a device that generates a three-dimensional difference image between a first image and a second image, similar to the first embodiment. However, the image processing device according to this embodiment is characterized in that, when the pixel sizes of the images are different, the image processing device generates a difference image in which noise caused by the difference in density values ​​between the images due to the difference in pixel sizes is reduced. The image processing device according to this embodiment will be described below.

[0107] Usually, when converting continuous signal data obtained from a subject such as a CT image into discretized pixel density values ​​to reconstruct an image, a weighted average value of signal data in a predetermined section (for example, pixel size in a slice image plane or slice thickness) is used. That is, the density value of a pixel with a large pixel size is calculated by smoothing a wide range of signal data compared to a pixel with a small pixel size. In the image processing device of this embodiment, when the pixel size of the second image is smaller than that of the first image, the density value of the second image is approximately regarded as signal data. Then, the image processing device of this embodiment smoothes the density values ​​of pixels in an area on the second image that is the same size as one pixel of the first image, and approximately obtains density values ​​generated from signal data of an area that is the same size as one pixel of the first image, and generates a second smoothed image by smoothing the second image. Then, the generated second smoothed image is used instead of the second image to perform a process of generating a difference image similar to that of the first embodiment. As a result, a smoothed area on the second image in which the difference between the density value of the target pixel of the first image and the density value is the smallest is selected, so that a change in density value caused by a minute shift of the area to be smoothed can be absorbed. On the other hand, when the pixel size of the first image is smaller than that of the second image, the first image is smoothed and the first smoothed image is used instead of the first image to generate a difference image similar to that of the first embodiment. This allows the user to observe a difference image with less noise than that of the first embodiment when two images with different pixel sizes are input. The configuration and processing of this embodiment will be described below with reference to Figs. 11 and 12.

[0108] 11 shows the configuration of an image diagnostic system according to this embodiment. The function of a smoothed image acquisition unit 11010 will be described below. The other components are the same as those in the first embodiment, so the description will be omitted.

[0109] The smoothed image acquisition unit 11010 determines which of the pixel size of the first image and the pixel size of the second image acquired from the data acquisition unit 1010 is larger, and acquires a second smoothed image obtained by smoothing the second image if the pixel size of the second image is smaller than the pixel size of the first image. On the other hand, if the pixel size of the first image is smaller than the pixel size of the second image, acquires a first smoothed image obtained by smoothing the first image.

[0110] Fig. 12 shows a flowchart of the overall processing procedure performed by the image processing device 1100. Steps S12030 to S12110 are similar to steps S2020 to S2100 in the first embodiment, respectively, and therefore their explanation will be omitted. Only the differences from the flowchart in Fig. 2 will be explained below.

[0111] (S12000) (Data Acquisition) In step S12000, the data acquisition unit 1010 acquires the first image, the second image, and the pixel size of each image input to the image processing device 1100. Then, the data acquisition unit 1010 outputs the acquired first image, the second image, and the pixel size of each image to the smoothed image acquisition unit 11010. In addition, the data acquisition unit 1010 outputs information on the pixel sizes of the first image and the second image to the comparison region size determination unit 1040.

[0112] (S12010) (Acquisition of smoothed image) In step S12010, the smoothed image acquisition unit 11010 determines which of the pixel size of the first image and the pixel size of the second image acquired from the data acquisition unit 1010 is larger. When the first image has the larger pixel size of the two pixel sizes (when the pixel size of the second image is smaller than the pixel size of the first image), the smoothed image acquisition unit 11010 smoothes the second image to acquire a second smoothed image. Then, the smoothed image acquisition unit 11010 outputs the acquired second smoothed image and the first image to the converted image acquisition unit 1020. In this case, the image processing device 1100 replaces the second smoothed image with the second image and performs the subsequent processes. On the other hand, when the first image has the smaller pixel size of the two pixel sizes, the smoothed image acquisition unit 11010 acquires a first smoothed image obtained by smoothing the first image. Then, the smoothed image acquisition unit 11010 outputs the acquired first smoothed image and second image to the converted image acquisition unit 1020. In this case, the image processing device 1100 replaces the first image with the first smoothed image and performs the subsequent processes. Note that the smoothed image acquisition unit 11010 is capable of executing the above processes since it acquires the pixel size of each image from the data acquisition unit 1010.

[0113] Specifically, an example in which the first image has a first pixel size will be described. In this embodiment, the smoothed image acquisition unit 11010 smoothes the second image having a smaller pixel size by using a kernel of the same size as the pixel size of the first image, in order to perform a process approximating the process for reconstructing the first image having a larger pixel size from the signal data. For example, assume that the pixel sizes of the first image in the x, y, and z axis directions are 1.5 mm, 1.5 mm, and 5 mm, respectively, and the pixel sizes of the second image are 0.5 mm, 0.5 mm, and 1 mm, respectively. In this case, the kernel size is 1.5 mm x 1.5 mm x 5 mm, which corresponds to a size of 3 x 3 x 5 pixels on the second image. A known smoothing process is performed using this kernel. The smoothing process may be a process of uniformly averaging the density values ​​of 3 x 3 x 5 pixels, or a process of calculating a weighted average, such as a smoothing process using a Gaussian filter. In general CT images, the resolution within a slice (= pixel size in the x and y directions) is often high enough that noise reduction in the x and y directions may not be performed. In this case, the kernel size in the x and y directions is set to 1 pixel, and only the density value in the z direction is smoothed.

[0114] In the above example, the ratio of pixel sizes between the images is an odd number of pixels. That is, the kernel size is an odd number of pixels in each axis direction on the second image. Below, an example in which the ratio of pixel sizes between the images is an even number of pixels will be described. For example, if the pixel sizes in the x, y, and z axis directions of the first image are 0.5 mm, 0.5 mm, and 4 mm, respectively, and the pixel sizes in the second image are 0.5 mm, 0.5 mm, and 1 mm, respectively, the kernel size is 1×1×4 pixels on the second image. In general, when performing filtering using a kernel, the kernel size in the axis direction is an odd number of pixels, and the filtering target pixel and the pixels in the positive and negative directions of the axis centered on that pixel are used evenly (in the case of 5 pixels, 2 pixels each) to perform the filtering. However, when the kernel size is an even number of pixels such as 4 pixels, the pixels in the positive and negative directions of the axis cannot be used evenly. Therefore, an image is generated by converting the resolution of the second image so that the pixel size of the first image is an odd number of pixels compared to the second image. More specifically, the pixel size of the second image is converted so that the pixel size of the first image is an odd multiple of the image obtained by converting the resolution of the second image, and is the closest value that is equal to or smaller than the pixel size of the original second image. In the above example, the pixel size is an even multiple only in the z-axis direction, so the resolution is converted only in the z-direction. That is, by converting the pixel size of the second image to 0.5 mm, 0.5 mm, and 0.8 mm, the kernel size becomes 1×1×5 pixels on the image obtained by converting the resolution, and the density value can be smoothed by evenly using the pixels in the positive and negative directions of the axis. In this case, the pixel size of the first image may be converted so that the pixel size of the first image is an odd multiple of the image obtained by converting the resolution of the second image, and is the closest value that is equal to or smaller than the pixel size of the original first image.

[0115] In this embodiment, the density values ​​of the second image are approximately regarded as signal data, and the density values ​​of the smoothed image are calculated from the approximated signal data. It is preferable that the method of calculating the density values ​​from this signal data is similar to the method of actually generating the density values ​​of the first image from the signal data and reconstructing the image. In other words, if the reconstruction algorithm of the first image is known, the density values ​​of the smoothed image may be calculated according to that algorithm.

[0116] In the above example, an example was described in which the first image has a first pixel size, but if the second image has the first pixel size, a first smoothed image can be obtained by smoothing the first image in a similar manner.

[0117] When calculating the smoothed value of the density values ​​of the pixels within the range indicated by the kernel, all the pixels within the range may be used, or the density values ​​of pixels sampled at any interval may be smoothed. By sampling the pixels, the smoothing process can be speeded up.

[0118] In this embodiment, if the pixel sizes of the first image and the second image are equal, or if the difference in pixel size is equal to or less than a threshold, the first image and the second image may be output to the converted image acquisition unit 1020 and this step may be omitted. In this case, the same process as in the first embodiment is performed.

[0119] (S12020) (Acquisition of converted image) In step S12020, the converted image acquisition unit 1020 acquires a first converted image obtained by converting the resolution of the first image (or the first smoothed image) and a second converted image obtained by converting the resolution of the second image (or the second smoothed image) so that the pixel sizes of the two images are the same, as in the first embodiment. For example, if the first image has a first pixel size that is the larger pixel size of two pixel sizes and the second image has a second pixel size that is the smaller pixel size of two pixel sizes, the pixel size of the first image is converted to the second pixel size. Then, the generated converted image is output to the deformation information acquisition unit 1030, the position acquisition unit 1050, the comparison area setting unit 1060, the combination determination unit 1070, and the difference calculation unit 1080. Note that the converted image acquisition unit 1020 does not necessarily have to perform resolution conversion.

[0120] In this manner, the processing of the image processing device 1100 is carried out.

[0121] In this embodiment, between images with different pixel sizes, the image with the smaller pixel size is smoothed so that the pixel size is approximated to the pixel size of the image with the larger pixel size, and then the difference is calculated. Therefore, according to this embodiment, the user can observe a difference image in which noise caused by the difference in pixel size is reduced more than in the first embodiment.

[0122] In the above embodiment, when the pixel size of the second image is smaller than that of the first image, the smoothing process is performed on the second image, but the same effect can be obtained by performing the smoothing process on the second converted image. Similarly, when the pixel size of the first image is smaller than that of the second image, the smoothing process may be performed on the first converted image instead of the first image. In this case, the smoothing kernel size may be determined based on the pixel size of the original image, not the pixel size of the converted image.

[0123] In addition, the second to fifth embodiments can also perform the same processing as in this embodiment. That is, after acquiring image data, a smoothed image is generated by smoothing the image having a smaller pixel size of the first and second images to match the image having a larger pixel size, and the smoothed image is replaced with the original image for subsequent processing, thereby obtaining a similar noise reduction effect. Here, in the third embodiment, when the pixel size of the second image is smaller than that of the first image, a smoothed image may be generated by performing a smoothing process on the second transformed image, and used in place of the second transformed image. In addition, in each embodiment, the first and second images (or their transformed images) that are not smoothed may be used in the transformation information acquisition process performed by the transformation information acquisition unit 1030, and the smoothed image (or its transformed image) may be used only in the difference value calculation process performed by the difference calculation unit 1080.

[0124] (Variation 6-1) (Acquire deformation information from outside) In this embodiment, the deformation information is acquired using the image after the smoothing process. However, if a similar conversion process has been performed previously to acquire the deformation information, the deformation information acquired by the deformation process may be stored in the data server 110, and the previously acquired deformation information may be acquired from the data server 110, and the process of acquiring the deformation information may be skipped. Then, the deformation information may be used to generate a difference image between the first image or the first converted image and the second smoothed image. For example, if a user who has observed the difference image generated by the image processing device of the first embodiment determines that it is necessary to reduce noise caused by differences in pixel size, the image processing device of this embodiment can generate a difference image in which noise has been reduced by using the already acquired deformation information. This allows the process of acquiring the deformation information to be skipped, thereby speeding up the process.

[0125] (Variation 6-2) (non-pixel-by-pixel smoothing method) In this embodiment, the image obtained by converting the resolution of the second image is smoothed so that the pixel size of the first image is an odd multiple of that of the second image, but the resolution does not necessarily have to be converted. For example, a first region having the same pixel size as that of the first image may be set around the pixel to be smoothed on the second image, and smoothing processing may be performed according to the density value of the pixel included in the first region and the volume ratio of the pixel. More specifically, when the pixel of the second image is completely included in the first region, the weighting coefficient related to the density value of the pixel is set to 1. On the other hand, when only half of the pixel is included in the first region, the weighting coefficient related to the density value is set to 0.5. Then, a second smoothed image can be obtained in which the weighted average density value of all pixels included in the first region is set as the density value. This allows the same effect to be obtained without converting the resolution of the second image so that the pixel size of the first image is an odd multiple of that of the second image.

[0126] Seventh embodiment The image processing device according to this embodiment is a device that generates a three-dimensional difference image between a first image and a second image, similar to the sixth embodiment. However, the image processing device according to this embodiment automatically determines the size relationship of the pixel sizes between the images, and when the pixel sizes between the images are different, obtains the size of the comparison region based on the larger pixel size. As a result, compared to the sixth embodiment, it is characterized by generating a difference image with reduced noise for the smoothed image. The image processing device according to this embodiment will be described below.

[0127] 13 shows the configuration of an image diagnostic system according to this embodiment. The functions of a pixel size determination unit 13010 and a smoothed image acquisition unit 11010 are described below. The other components are the same as those in the sixth embodiment, and therefore the description thereof is omitted.

[0128] The pixel size determination unit 13010 automatically determines which of the pixel sizes of the first image and the second image is larger, and acquires the larger pixel size as the first pixel size. That is, it determines whether the pixel sizes of the first image and the second image are different. If the pixel size of the second image is smaller than the pixel size of the first image as a result of the determination by the pixel size determination unit 13010, the smoothed image acquisition unit 11010 acquires a second smoothed image obtained by smoothing the second image. On the other hand, if the pixel size of the first image is smaller than the pixel size of the second image, it acquires a first smoothed image obtained by smoothing the first image.

[0129] Fig. 14 shows a flowchart of the overall processing procedure performed by the image processing device 1300. Steps S14020, S14030, S14050, and S14070 to S14110 perform the same processing as steps S12020, S12030, S12050, and S12070 to S12110 in the sixth embodiment, respectively, and therefore description thereof will be omitted. Only differences from the flowchart in Fig. 12 will be described below.

[0130] (S14000) (Data Acquisition) In step S14000, the data acquisition unit 1010 acquires the first image and the second image input to the image processing device 1300. The data acquisition unit 1010 also acquires information on the pixel sizes of the first image and the second image in the predetermined axis direction. That is, the data acquisition unit 1010 corresponds to an example of an image acquisition means for acquiring the first image and the second image. The data acquisition unit 1010 also corresponds to an example of a pixel size acquisition means for acquiring a first pixel size, which is the pixel size in the predetermined axis direction of each of the first image and the second image captured at different times, and a second pixel size different from the first pixel size. Then, the acquired first image and the second image and information on the pixel sizes of the first image and the second image are output to the pixel size determination unit 13010. The information on the pixel sizes of the first image and the second image are also output to the comparison area size determination unit 1040. At this time, only information on the pixel sizes of each of the first image and the second image in the predetermined axis direction may be output to the comparison area size determination unit 1040. For example, the data acquisition unit 1010 outputs only the pixel size in the z-axis direction to the comparison region size determination unit 1040. Note that, although the present embodiment shows a case where the image processing device 1300 includes the functions of 1010 to 1100, the present invention is not limited to this.

[0131] (S14002) (Determining the difference in pixel size) In step S14002, the pixel size determination unit 13010 automatically determines whether the pixel sizes of the first image and the second image are different and the relationship between the pixel sizes of the first image and the second image. That is, the pixel size determination unit 13010 corresponds to an example of a determination unit that determines whether the first pixel size and the second pixel size acquired by the pixel size acquisition unit are different. The pixel size determination unit 13010 further determines whether the difference in pixel size between the first image and the second image is greater than a threshold value. If the difference in pixel size is greater than the threshold value, the process proceeds to step S14005. On the other hand, if the difference is equal to or less than the threshold value, the first image and the second image are output to the conversion image acquisition unit 1020, and the processes of steps S14005 and S14010 are omitted. In this case, the same process as in the first embodiment is performed.

[0132] For example, it is determined whether or not the difference in at least one of the pixel sizes on each of the x, y, and z axes (a value indicating the difference between the first pixel size and the second pixel size) is greater than a threshold value. Here, the threshold value may be set as the ratio between the first pixel size and the second pixel size (e.g., 1.5 times), or as the difference in size (e.g., 3 mm). Also, any method of comparing two numerical values ​​may be used. It is also possible to use whether or not there is a difference in pixel size as the determination condition without setting the above threshold value.

[0133] In this embodiment, the determination is made as to whether the difference in pixel size between the first image and the second image is greater than a threshold value, but the determination may be made based on the volume of one voxel, or based only on the pixel size in a predetermined axis direction. For example, in the case of a general CT image, the pixel size in the slice plane (x, y axis directions) is sufficiently small and the difference is small, so the pixel size difference may be determined based only on the pixel size in the z axis direction (slice thickness).

[0134] (S14005) (Obtaining the first pixel size) In step S14005, the pixel size determination unit 13010 acquires the larger pixel size as the first pixel size and the smaller pixel size as the second pixel size of the pixel sizes of the first image and the second image acquired from the data acquisition unit 1010. Then, the acquired first pixel size is output to the smoothed image acquisition unit 11010 and the comparison region size determination unit 1040.

[0135] For example, the pixel size of the first image or the second image, whichever has the larger volume of one voxel, is acquired as the first pixel size. Alternatively, the pixel size of the image with the larger pixel size in a predetermined axis direction (e.g., z-axis direction) may be acquired as the first pixel size. Note that in general CT images, the z-axis direction corresponds to the body axis direction. Also, the larger pixel size may be selected for each of the x, y, and z axes, and the combination may be used as the first pixel size.

[0136] (S14010) (Acquisition of smoothed image) In step S14010, the smoothed image acquisition unit 11010 acquires a smoothed image obtained by smoothing the first image or the second image based on the first pixel size acquired in step S14005. Specifically, when the first image has the first pixel size, the same process as in step S12010 is performed. That is, the first pixel size is used as the kernel size of smoothing to smooth the second image. Note that, when the image with a larger pixel size is different on each of the x, y, and z axes, the first image and the second image may be defined for each axis, and smoothing processing may be performed on the second image in the direction of the axis. On the other hand, when the first image has a second pixel size smaller than the first pixel size, the first image may be processed to be smoothed. That is, the first image is smoothed using the first pixel size as the kernel size of smoothing.

[0137] (S14040) (Determining the size of the comparison area) In step S14040, the comparison region size determination unit 1040 determines the size of the comparison region. If the first pixel size is acquired in step S14005, the comparison region size determination unit 1040 determines the size of the comparison region based on the first pixel size. That is, when the first pixel size is different from the second pixel size, the comparison region size determination means corresponds to an example of a determination means that determines the size in a predetermined axis direction of the comparison region, which is a region including a plurality of density values ​​in the other image of the first image and the second image that is different from the other image of the first image and the second image to be compared with the density value of the position of interest in one of the first image and the second image, based on the larger pixel size of the first pixel size and the second pixel size. The comparison region size determination unit 1040 outputs the determined size of the comparison region to the comparison region setting unit 1060.

[0138] For example, the comparison region size determination unit 1040 determines only the size of the comparison region in the predetermined axis direction based on the first pixel size. In general CT images, the resolution in a slice (= pixel size in the x and y directions) is often sufficient, so the comparison region in the x and y directions may not be determined based on the first pixel size. For example, in the x and y axis directions, the density value is compared only between the density value of the target position in the first image and the density value of the corresponding position in the second image. Also, the size of the comparison region in the x and y axis directions may be set to a predetermined fixed value (for example, 1 mm), and only the size of the comparison region in the z axis direction may be determined by the above method. This can speed up the calculation. Also, in the x and y axis directions, as in the first embodiment, the comparison region size determination unit 1040 may determine the sum of the half pixel sizes of the first image and the second image as the size of the comparison region. In addition, the comparison region size determination unit 1040 may determine the comparison region to be 0 in the x- and y-axis directions so that only the difference between the density value of the focus position in the first image and the density value of the corresponding position in the second image is calculated.

[0139] The reason why the size of the comparison region is obtained based on the first pixel size will be described below.

[0140] For example, assume that the predetermined axis direction is the z-axis, there is a first image having a first pixel size, and a second image having a second pixel size, and the pixel sizes are Dmm and dmm, respectively (D=n*d). FIG. 15 is an example showing how the difference in coordinates of the end points of each graph changes when the discretization position of the first image is shifted, focusing on pixels reflecting the same lesion in the first image and the second image having different pixel sizes. For simplicity of explanation, D=3*d and the lesion in the original image is described as a sphere with a diameter of dmm, but the size of the first pixel size and the shape and size of the lesion are not limited to the above. In FIG. 15, the first image and the second image are images of, for example, a body, and the predetermined axis direction, the z-axis direction, indicates the body axis direction. That is, the pixel size in the z-axis direction indicates the slice thickness. In addition, the processing of this embodiment is not limited to processing in the z-axis direction, and can also be applied to pixels in the x and y directions.

[0141] (1) When the lower ends of the discretization positions of the two pixels are aligned Fig. 15(a) is a diagram showing a schematic example of a case where the lower ends of the discretization positions of two pixels are aligned, in which the vertical axis represents the position in the z-axis direction.

[0142] First, a first image and a second image obtained by imaging (discretizing) an original image are obtained. This step corresponds to step S14000 in this embodiment. Graphs 15010 and 15020 respectively show the pixel values ​​of the pixels on the second image obtained by discretizing and imaging the lesion 15005 in the original image, and the pixel values ​​of the pixels on the first image. That is, they show the density value of the first pixel of the first image showing a predetermined part of the subject, and the density value of the second pixel of the second image. Note that graph 15010 shows the pixel of the second image that best reflects the lesion 15005 in the original image among the two images. On the other hand, graph 15020 shows the pixel of the first image that best reflects the lesion 15005 in the original image among the pixels. Note that the reference symbol 15005 is not limited to a lesion, and may be a structure such as a bone.

[0143] Next, the smoothed image acquisition unit 11010 performs a smoothing process corresponding to step S14010 of this embodiment. A graph 15030 shows values ​​obtained by smoothing the density values ​​of the graph 15010 based on the pixel size of the first image. Specifically, the graph shows values ​​obtained by smoothing the density values ​​of the second image using the pixel size of the first image as the kernel size. In other words, the smoothed image acquisition unit 11010 corresponds to an example of a smoothing means that smoothes an image having a smaller pixel size of the first pixel size and the second pixel size using a kernel size based on the larger pixel size.

[0144] Next, the converted image acquisition unit 1020 performs density value interpolation corresponding to step S14070 of this embodiment (step S12020 in the sixth embodiment). The graphs 15040 and 15050 show values ​​obtained by linearly interpolating the density values ​​of the graphs 15030 and 15020 with adjacent pixels, respectively. That is, the graph 15050 corresponds to an example of a first interpolated value obtained by interpolating the density value of a first pixel of a first image and the density value of a pixel adjacent to the first pixel. The graph 15040 corresponds to an example of a second interpolated value obtained by interpolating the density value of a second pixel after smoothing the density value of a second pixel of a second image with a first pixel size and the density value of a pixel adjacent to a pixel indicating the density value of the second pixel after smoothing. The height in the horizontal axis direction in the graphs 15040 and 15050 indicates the density value. Note that a known image processing method can be used for the density value interpolation. For example, it is possible to use nearest neighbor interpolation, linear interpolation, cubic interpolation, etc. In this case, the coordinates of the endpoints in the positive direction of the z-axis in each graph are (5 / 2)*d in graph 15040 and (3 / 2)*D in graph 15050.

[0145] In this case, the difference 15060 between the coordinates of the endpoints of each of the graphs described above is {(3 / 2)*D-(5 / 2)*d}=2*d.

[0146] (2) In the first image, the lesion 15005 in the original image is discretized at the center. FIG. 15(b) is a diagram schematically showing an example where the lesion of the original image is discretized at the center in the first image. In FIG. 15(b), the vertical axis represents the position in the z-axis direction.

[0147] In this case, since the object is discretized at the center, the graph 15020, which is the pixel in the first image that most reflects the lesion 15005 of the original image, consists of two consecutive pixels.

[0148] Next, when these two pixels 15020 are linearly interpolated in the same manner as in FIG. 15(a), the coordinate of the end point in the positive z-axis direction in the graph 15050 is \((1 / 2)*d+(3 / 2)*D=(5 / 3)*D\). At this time, the difference 15060 between the coordinates of the end points of each graph is \((5 / 3)*D-(5 / 2)*d = 2.5*d\).

[0149] (3) When the lesion 15005 of the original image is discretized at the end in the first image FIG. 15(c) is a diagram schematically showing an example where the lesion of the original image is discretized at the end (upper end) in the first image. In FIG. 15(c), the vertical axis represents the position in the z-axis direction. Note that in FIG. 15(c), it is assumed that the discretization occurs at an end d' (<d) that is infinitely close to the contact point (z = d) of the lesion 15005 of the original image.

[0150] In this case, since the object is discretized at the end, the graph 15020, which is the pixel that contains more of the lesion within the discretization interval among the two pixels reflecting the lesion 15005 of the original image, becomes the pixel that most reflects the lesion 15005 of the original image.

[0151] Next, two pixels reflecting the lesion 15005 in the original image are linearly interpolated. At this time, the coordinates of the endpoint in the positive direction of the z-axis in graph 15050 are {d'+(3 / 2)*D} (<{d+(3 / 2)*D}=(11 / 6)*D). Specifically, the value is smaller by the amount of deviation in the discretization positions of the first image and the second image, but since FIG. 15(c) assumes that the deviation in the discretization positions is infinitesimal, this value can be approximated to 0. In this case, the difference 15060 in the coordinates of the endpoints of each graph is {(11 / 6)*D-(5 / 2)*d}≒3*d. This value coincides with the first pixel size.

[0152] (4) When the top ends of the discretization positions of the two pixels are aligned Fig. 15(d) is a diagram showing a schematic example of a case where the upper ends of the discretization positions of two pixels are aligned, where the vertical axis represents the position in the z-axis direction.

[0153] 15(a) and comparing the coordinates of the end points of graphs 15040 and 15050, the difference 15060 is |[{d-(3 / 2)*D}-{-(3 / 2)*d}]|=|-(2*d)|=2*d.

[0154] Therefore, from Fig. 15(a) to (d), it can be seen that the difference in the coordinates of the end points when the pixel that best reflects the lesion 15005 of the original image is linearly interpolated with the adjacent pixels changes between 2*d to 3*d. Therefore, by adaptively determining the size of the comparison region to 3*d=D, that is, the first pixel size, it is possible to search for a density value that reflects the lesion 15005 of the original image between two images with a minimum necessary size. From a different perspective, it is possible to search for a corresponding value other than the maximum value of the interpolated value by setting a comparison region of a size based on the amount of deviation between the corresponding positions of a value other than the maximum value in the first interpolated value (graph 15050) and a value other than the maximum value in the second interpolated value (graph 15040) in one of the first image and the second image. Note that the amount of deviation between the minimum value of the first interpolated value and the corresponding minimum value of the second interpolated value may be maximized, and the size of the comparison region may be determined based on this amount of deviation, but the size of the comparison region may also be determined based on the amount of deviation between a value other than the maximum and minimum of the first interpolated value and a value other than the maximum and minimum of the second interpolated value.

[0155] The comparison region size determination unit 1040 may determine the size of the comparison region by multiplying the first pixel size (the larger pixel size) by a predetermined coefficient. The predetermined coefficient may be 0.5 or another value. In this embodiment, the predetermined coefficient is set to 0.5 because the degree of difference between the first and second interpolated values ​​is random, and the above-mentioned various cases appear randomly.

[0156] As can be seen from the processing of steps S14002, 14005, and 14010, when the value indicating the difference between the first pixel size and the second pixel size is greater than or equal to a threshold, the comparison area size determination unit 1040 determines the size of the comparison area in a predetermined axis direction based on the larger pixel size.

[0157] On the other hand, if the first pixel size is not acquired in step S14005, the comparison region size determination unit 1040 determines the size of the comparison region based on, for example, the pixel sizes of the first image and the second image, as in the sixth embodiment. Specifically, the comparison region size determination unit 1040 determines the size of the comparison region to be the sum of half the pixel size of the first image and half the pixel size of the second image. That is, if the value indicating the difference between the first pixel size and the second pixel size is less than the threshold, the comparison region size determination unit 1040 determines the size of the comparison region in the predetermined axis direction based on the first pixel size and the second pixel size.

[0158] If the first pixel size is not acquired in step S14005, the comparison region size determination unit 1040 may determine the comparison region to be 0 so that only the difference between the density value of the focus position of the first image and the density value of the corresponding position of the second image is calculated. Then, the determined size of the comparison region is output to the comparison region setting unit 1060. As in the above embodiment, the comparison region size determination unit 1040 may determine the size of the comparison region by multiplying the first pixel size (the larger pixel size) by a predetermined coefficient. The predetermined coefficient may be 0.5 or another value. In this embodiment, the predetermined coefficient is set to 0.5 because the degree of separation between the first interpolation value and the second interpolation value is random, and various cases such as those described above appear randomly. Also, if it is determined in S14002 that the difference between the two pixel sizes is greater than the threshold, step S14040 is not limited to this processing procedure, and may be performed before any of S14030, S14020, and S14010.

[0159] (S14060) (Setting comparison area) In step S14060, the comparison region setting unit 1060 sets a comparison region having the size of the comparison region determined in step 14040, based on the corresponding position on the second image. For example, the comparison region is set based on the corresponding position on the smoothed image. Note that the region in which the comparison region is set is not limited to the second image. For example, when a focus position is set on the second image, the comparison region may be set on the first image based on the corresponding position on the first image corresponding to the focus position. The comparison region setting unit 1060 corresponds to an example of a setting means for setting a comparison region for the other image based on the corresponding position on the other image. For example, the comparison region setting unit 1060 sets the comparison region around the corresponding position on the second image. That is, the comparison region setting unit 1060 sets a comparison region of the size determined by the determining means, centered on the corresponding position on the other image. At this time, the comparison region may be set so as not to exceed a position separated from the corresponding position by the first pixel size in at least one of the three-dimensional axial directions of x, y, and z. That is, in an n-dimensional image, the comparison area setting unit 1060 sets the comparison area in at least one of the n-dimensional axial directions so that the comparison area does not exceed a position that is the larger pixel size away from the corresponding position on the other image.

[0160] For example, consider a case where a rectangular comparison region is set around the corresponding position on the second image. First, assume that the coordinates of the corresponding position are (x, y, z) = (1, 1, 1) and the size of the comparison region is D = 4. In this case, if the center of the comparison region is set to (x, y, z) = (1, 1, 2), the coordinates of the end points of the rectangular comparison region are (x, y, z) = (1 + 4, 1 + 4, 2 + 4) = (5, 5, 6). This exceeds the position (z = 5) that is the first pixel size away from the corresponding position in the z direction, but does not exceed the position (x = 5, y = 5) that is the first pixel size away from the corresponding position in the x and y directions, so it corresponds to a comparison region that does not exceed the position that is the first pixel size away from the corresponding position in at least one of the above axial directions. Also, the comparison region may be set so as not to exceed the position that is the first pixel size away from the corresponding position in all axial directions of the three-dimensional axis. Then, information on the set comparison region is output to the difference calculation unit 1080.

[0161] In this embodiment, when the smoothing process of the second image is performed using a kernel of the same size as the first pixel size, the smoothed image obtained by smoothing the second image can be regarded as an image discretized in an area of ​​the same size as the first pixel size, like the first image. In other words, since the discretization position is shifted by a maximum of half the size of the first pixel between the smoothed image and the first image, the size of the comparison area is set to a large pixel size (= half the size of the first pixel size + half the size of the first pixel size), it is possible to reduce noise caused by the shift in the discretization position between the smoothed image and the first image.

[0162] The size of the comparison region in the x and y directions, which are different from the predetermined axis direction, can be a predetermined value. For example, specifically, the comparison region size determination unit 1040 may determine the size of the comparison region in the x and y directions as the sum of half the pixel size of the first image and half the pixel size of the second image in the corresponding direction, or may be a predetermined constant. Also, the size of the comparison region in the x and y directions, which are different from the predetermined axis direction, may be set to 0 so that only the density value of the focus position and the density value of the corresponding position are compared.

[0163] (S14070) (Decision of combination) In step S14070, the combination determination unit 1070 determines a combination of density values ​​to be subjected to the comparison process (calculation of the difference). First, the combination determination unit 1070 interpolates the density value of the attention position on the first converted image acquired in step S14050 and the density value of the pixel in the comparison area on the second converted image. A known image processing method can be used for the interpolation of the density value. For example, nearest neighbor interpolation, linear interpolation, cubic interpolation, etc. can be used. Also, the density value of the pixel in the comparison area on the second converted image does not necessarily need to be interpolated. A combination of density values ​​may be determined so that the difference between the density value of the attention position on the first converted image and the density values ​​of all pixels in the comparison area on the second converted image is calculated, or at least one pixel may be sampled from among the pixels included in the comparison area, and the combination of the density value of that pixel and the density value of the attention position may be set as the combination to be subjected to the calculation of the difference. For example, the combination determination unit 1070 samples the maximum density value and the minimum density value from among the pixels included in the comparison area. Then, a combination of the maximum density value included in the comparison region and the density value of the attention position, and a combination of the minimum density value included in the comparison region and the density value of the attention position are determined as combinations for which the difference is to be calculated. The density values ​​to be sampled are not limited to the maximum and minimum, and three or more values ​​may be sampled, or a single value such as the maximum density value or the minimum density value may be sampled. Alternatively, a density range having the maximum density value and the minimum density value in the comparison region as both ends (upper limit and lower limit) may be obtained, and the density value of the attention position and the density range in the comparison region may be obtained as a combination for which the difference is to be calculated. The density range in the comparison region may be other than the maximum and minimum density values. For example, it may be the maximum and minimum values ​​after removing outliers in the density values.

[0164] The combination determination unit 1070 outputs information indicating the combination of density values ​​to be the target of the determined difference calculation to the difference calculation unit 1080. The difference calculation unit 1080 calculates the difference between the density value of the focus position on one image and the density values ​​of multiple positions in the comparison area on the other image, for example, as described above. The information indicating the combination of density values ​​output by the combination determination unit 1070 may be information indicating all combinations of the density values ​​of the focus position on the first converted image and the density values ​​of pixels in the comparison area on the second converted image, or may output only information indicating combinations of the density values ​​of pixels sampled from among the pixels included in the comparison area and the density values ​​of the focus position.

[0165] In this manner, the processing of the image processing device 1300 is carried out.

[0166] In this embodiment, between images with different pixel sizes, the relationship of pixel size is automatically determined, and a smoothing process is performed so that the image with the smaller pixel size is approximated to the image with the larger pixel size, and a smoothed image is obtained. As a result, both the smoothed image and the first image can be considered to have been discretized in an area of ​​the same size as the first pixel size. Then, by using a value based on the size of the discretization area (first pixel size) as the size of the comparison area, the user can observe a difference image in which noise caused by the difference in pixel size is reduced more than in the sixth embodiment. That is, the size of the comparison area that can reduce noise more can be adaptively determined. Also, according to this embodiment, the size of the comparison area is determined based on the first pixel size that is larger than the sum of half the pixel sizes of the two images, so that even a relatively weak signal among signals indicating a predetermined object is less likely to be imaged as noise.

[0167] Eighth embodiment In the above embodiment, a single image processing device acquires two images taken at different times and performs a series of processes up to generating a difference image. However, the image processing described in this specification is also performed when the comparison region size determination unit 1040 is provided in a separate image processing device. The components provided in each of the two image processing devices in this case are shown in FIG. 16. The functions of the image acquisition unit 16010, pixel size determination unit 16020, pixel size determination unit 16030, and pixel size determination unit 16030' will be described below. Descriptions of other components will be omitted.

[0168] The image acquisition unit 16010 acquires the first image and the second image input to the image processing device 1610 from the data server 110 .

[0169] The pixel size acquisition unit 16020 acquires the first pixel size and the second pixel size input to the image processing device 1620 from the data server 110. At this time, it is not necessary to acquire the first image and the second image themselves.

[0170] A pixel size determination unit 16030 determines which of the pixel sizes of the first image and the second image input from the image acquisition unit 16010 is larger, and sets the larger pixel size as the first pixel size.

[0171] The pixel size determination unit 16030' determines which of the two pixel sizes input from the pixel size acquisition unit 16020 is larger, and sets the larger pixel size as the first pixel size. At this time, between the two devices, only the pixel size determination unit 16030 may determine which of the pixel sizes is larger and transmit the determination result to the separate image processing device 1620, or only the pixel size determination unit 16030' may determine which of the pixel sizes is larger and transmit the determination result to the separate image processing device 1610.

[0172] FIG. 17 is a flowchart showing the overall processing procedure performed by the image processing device 1620.

[0173] Each process will be explained below.

[0174] (S17000) (Data Acquisition) In step S17000, pixel size acquisition unit 16020 outputs information relating to the pixel size of the first image and the pixel size of the second image input to image processing device 1620 to pixel size determination unit 16030'.

[0175] (S17100) (Determine pixel size) In step S17100, pixel size determination unit 16030′ acquires the larger of the pixel sizes of the first image and the second image acquired from pixel size acquisition unit 16020 as the first pixel size, and acquires the smaller of the pixel sizes as the second pixel size. Then, pixel size determination unit 16030′ outputs the acquired first pixel size to comparison region size determination unit 16040.

[0176] For example, the pixel size of the first image or the second image, whichever has the larger volume of one voxel, is acquired as the first pixel size. Alternatively, the pixel size of the image with the larger pixel size in a predetermined axis direction (e.g., z-axis direction) may be acquired as the first pixel size. Note that in general CT images, the z-axis direction corresponds to the body axis direction. Also, the larger pixel size may be selected for each of the x, y, and z axes, and the combination may be used as the first pixel size.

[0177] (S17200) (Determining the size of the comparison area) In step S17200, the comparison region size determination unit 16040 determines the size of the comparison region. If the first pixel size has been acquired in step S17200, the comparison region size determination unit 16040 determines the size of the comparison region based on the first pixel size.

[0178] Then, the result is output to the comparison region setting unit 1060 of the image processing device 1610.

[0179] <Ninth embodiment> In the above embodiment, the case where the difference image is generated by the difference calculation unit 1080 and the difference image generation unit 1090 has been mentioned, but the image generated by the image processing device according to the present invention is not limited to a difference image as long as it is an image showing the difference between two images taken at different times. For example, the image processing device may calculate the ratio of density values ​​between two images and generate an image showing the ratio of density values ​​between the two images (division result) based on the ratio. In this case, the ratio of the unchanged part is 1 and the ratio of the changed part is a value other than 1, so that the change over time can be visualized as in the above-mentioned difference image. In addition, when generating an image showing the ratio of density values, a ratio calculation unit that calculates the ratio and an image generation unit that generates an image showing the ratio may be provided instead of the difference calculation unit 1080 and the difference image generation unit 1090. Here, since calculating the difference between multiple density values ​​and calculating the ratio between multiple density values ​​can both be said to be comparing multiple density values, the difference calculation unit 1080 and the ratio calculation unit can be collectively referred to as a comparison unit. That is, the difference calculation section 1080 or the ratio calculation section corresponds to an example of a comparison means that compares the density value of a position of interest on one image with density values ​​of a plurality of positions within a comparison region on the other image.

[0180] <Other embodiments> Although the embodiment has been described above in detail, the present invention can be embodied as, for example, a system, an apparatus, a method, a program, a recording medium (storage medium), etc. Specifically, the present invention may be applied to a system composed of multiple devices (for example, a host computer, an interface device, an imaging device, a Web application, etc.), or may be applied to an apparatus composed of a single device.

[0181] Needless to say, the object of the present invention can be achieved by the following. That is, a recording medium (or storage medium) on which a program code (computer program) of software for realizing the functions of the above-mentioned embodiment is recorded is supplied to a system or device. The storage medium is, of course, a computer-readable storage medium. Then, a computer (or a CPU or MPU) of the system or device reads and executes the program code stored in the recording medium. In this case, the program code itself read from the recording medium realizes the functions of the above-mentioned embodiment, and the recording medium on which the program code is recorded constitutes the present invention. Note that each function of the image processing device in the above-mentioned embodiment is realized by at least one processor of the image processing device executing a program stored in at least one memory. The type of processor does not matter, and multiple types of processors may be used.

[0182] Although the preferred embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and variations are possible within the scope of the gist of the present invention described in the claims.

[0183] Any of the above-described embodiments may be combined. [Explanation of symbols]

[0184] 1010 Data Acquisition Unit 1040 Comparison area size determination unit 13010 Pixel size determination unit

Claims

1. An image processing device that performs image processing to reduce noise caused by a discretization position shift between two images captured with different pixel sizes of a common subject, comprising: an image acquisition means for acquiring a first image captured at a predetermined time and a second image captured at a time different from the predetermined time; a pixel size acquisition means for acquiring pixel sizes in a predetermined axis direction in the first image and the second image, respectively; a smoothing means for smoothing one of the first image and the second image, which has a smaller pixel size, by using a kernel size based on the pixel size of the other of the first image and the second image to generate a smoothed image; a determining means for determining a size of a first comparison region in the predetermined axis direction based on a pixel size of the other image, the size being determined for a first comparison region including a plurality of positions on the other image whose density values ​​are compared with a position of interest on the smoothed image; a position acquisition means for acquiring the position of interest on the smoothed image and a corresponding position on the other image corresponding to the position of interest; a setting means for setting a position of the first comparison area based on the corresponding position; a difference acquiring means for acquiring a first difference value between the density value of the target position and an interpolated value obtained by interpolating density values ​​of a plurality of positions on the other image; 13. An image processing device comprising:

2. The image processing device of claim 1, wherein the first image and the second image include three-dimensional images.

3. An image processing device as described in claim 1 or 2, wherein the determination means determines the size of the first comparison area so as not to be based on the pixel size of the one of the images.

4. An image processing device as described in claim 1, further comprising a differential image generating means for generating a differential image based on the first differential value.

5. The image processing device described in Claim 4, characterized in that the determination means determines the size of a second comparison region in the specified axial direction for a second comparison region including a plurality of positions on the smoothed image whose density values ​​are compared with corresponding positions on the other image based on the pixel size of the other image.

6. The image processing device according to claim 5, characterized in that the setting means sets the position of the second comparison area based on the focus position.

7. An image processing device as described in Claim 5 or 6, characterized in that the difference acquisition means acquires a second difference value between the density value of the corresponding position and density values ​​of multiple positions on the smoothed image.

8. The image processing device described in Claim 7, characterized in that the difference image generating means generates the difference image based on a representative difference value obtained from the first difference value and the second difference value.

9. The image processing device described in Claim 8, characterized in that the representative difference value is either the difference value between the first difference value and the second difference value which has a larger absolute value, the difference value between the first difference value and the second difference value which has a smaller absolute value, or an average value of the first difference value and the second difference value.

10. 10. The image processing apparatus according to claim 1, wherein the first image and the second image are images of a body, and the predetermined axis direction is a body axis direction.

11. 11. The image processing apparatus according to claim 1, wherein the determining means determines the size of the first comparison area by multiplying a pixel size of the other image by a predetermined coefficient.

12. 12. The image processing apparatus according to claim 11, wherein the predetermined coefficient is 0.

5.

13. the determining means determines a size of the first comparison region in the predetermined axis direction based on a pixel size of the other image when a ratio of a pixel size of the other image to a pixel size of the one image is greater than a threshold value; 13. The image processing device according to claim 1, wherein, when the ratio is equal to or smaller than a threshold value, the size of the first comparison area in the specified axis direction is determined based on the pixel size of the other image and the pixel size of the one image.

14. 14. The image processing apparatus according to claim 13, wherein the determining means determines the size of the first comparison region to be a predetermined value in an axial direction different from the predetermined axial direction.

15. 14. The image processing apparatus according to claim 13, wherein the determining unit determines to compare the density value of the target position with the density value of the corresponding position in an axial direction different from the predetermined axial direction.

16. each of the first image and the second image is an n-dimensional image, The image processing device according to any one of claims 1 to 15, characterized in that the setting means sets the position of the first comparison area so that, in at least one of the n-dimensional axial directions, the first comparison area does not exceed a position away from the corresponding position on the other image by a pixel size of the other image.

17. 17. The image processing device according to claim 1, wherein the setting means sets the position of the first comparison area having a size in the specified axis direction determined by the determination means, centered on the corresponding position on the other image.

18. The image processing device according to claim 13, wherein the threshold value is 1.

5.

19. An image processing device as claimed in any one of claims 1 to 18, further comprising a combination determination means for determining a combination of density values ​​to be used for calculating the first difference value.

20. An image processing device as described in claim 7, having a combination determination means for determining a combination of density values ​​for which the first difference value is calculated, and a combination of density values ​​for which the second difference value is calculated.

21. 21. An image diagnostic system comprising: the image processing device according to claim 1; and an imaging device that captures the first image and the second image.

22. The imaging diagnostic system of claim 21, further comprising a data server for storing the first image and the second image.

23. An image diagnostic system comprising an image processing device according to any one of claims 4 to 9 and a monitor for displaying the difference image.

24. An image processing method for performing image processing to reduce noise due to a discretization position shift between two images captured with different pixel sizes of a common subject, comprising: an image acquiring step of acquiring a first image captured at a predetermined time and a second image captured at a time different from the predetermined time; a pixel size acquisition step of acquiring pixel sizes in a predetermined axis direction in the first image and the second image, respectively; a smoothing step of smoothing one of the first image and the second image, which has a smaller pixel size, using a kernel size based on the pixel size of the other of the first image and the second image to generate a smoothed image; a determining step of determining a size of a first comparison region in the predetermined axis direction based on a pixel size of the other image, the size being determined for a first comparison region including a plurality of positions on the other image whose density values ​​are compared with a position of interest on the smoothed image; a position acquiring step of acquiring the position of interest on the smoothed image and a corresponding position on the other image that corresponds to the position of interest; a setting step of setting a position of the first comparison area based on the corresponding position; a difference obtaining step of obtaining a first difference value between the density value of the target position and an interpolated value obtained by interpolating density values ​​around a plurality of positions on the other image; 13. An image processing method comprising:

25. The image processing method according to claim 24, further comprising a differential image generating step of generating a differential image based on the first differential value indicating a predetermined part of the subject.

26. A program for causing a computer to execute each step of the image processing method according to claim 24 or 25.

Images