JP2018019789A - Image encoding device and control method thereof - Google Patents

Abstract

PROBLEM TO BE SOLVED: To efficiently encode a set of image data composed of a plurality of pieces of slice image data along a body axis such as CT and MRI while maintaining high encoding accuracy.SOLUTION: An image encoding device encodes a slice image data set composed of a plurality of pieces of slice image data for a subject. The image encoding device includes: an acquisition part for acquiring information on an interval in a physical space with respect to a pixel interval in the slice image data, and on an interval in the physical space with respect to an interval between the slice image data; an encoding part for performing motion compensation encoding for each piece of the slice image data in the slice image data set; and a determination part for determining a motion search range in the motion compensation encoding by the encoding part based on the information acquired by the acquisition part.SELECTED DRAWING: Figure 3

Description

  The present invention relates to an image data encoding technique.

  In recent years, with the development of imaging techniques such as CT and MRI, the imaging time has been shortened, the slice interval density has been increased, and imaging conditions have been diversified, and the number of slice images has increased. It has become common to generate 2000 to 3000 tomographic images even when only one part of the human body such as the chest or abdomen is imaged. Since the amount of data is enormous, Compression technology becomes important.

  The medical image is used for identifying a lesion site or the like or for diagnosis. For this reason, conventionally, each slice image obtained by photographing is compressed using an international standard lossless encoding technique such as JPEG lossless method or JPEG2000. However, if each slice image is individually lossless encoded, the compression effect cannot be expected so much.

  Due to the recent development of photographing techniques, the density of slice images is increasing to 0.5 mm thickness or 1.0 mm thickness. Therefore, a technique is known in which a differential image between a slice image to be encoded and an adjacent slice image is generated, and the generated differential image is encoded to improve compression performance (Patent Document 1).

  In addition, a technique is known that improves the compression performance using the concept of motion compensation used in moving images when generating a difference between slice images (Non-Patent Document 1). Furthermore, a method is also known in which a motion search range that affects the processing speed and motion estimation accuracy in motion compensation is determined according to how many frames are away from a reference frame (Patent Document 2).

JP 2009-136437 A JP-A-10-262258

Shaou-Gang Miaou “A Lossless Compression Method for Medical Image Sequences Using JPEG-LS and Interframe Coding”

  In general, when compressing continuous images using motion compensation, setting a motion search range is important both in terms of compression performance and processing speed. The same applies to slice images in CT, MRI, and the like.

  In Non-Patent Document 1, the search range is set with a fixed value. However, depending on the shooting conditions and reconstruction conditions of the slice image, the search range becomes redundantly wide and causes a reduction in processing speed, or the search range is narrow and appropriate. It may happen that the movement cannot be acquired.

  In Patent Document 2, the search range is determined according to the number of frames from the reference image. However, even if the number of frames is replaced with the slice interval, it is difficult to determine the search range only by the slice interval because the slice image has a different range expressed by one pixel depending on the image reconstruction condition.

  The present invention has been made in view of the above points, and provides a technique for easily determining a search range in motion compensation in accordance with shooting conditions and image reconstruction conditions and improving the compression performance and processing speed of slice images. It is what.

In order to solve this problem, for example, an image encoding device of the present invention has the following configuration. That is,
An image encoding device for encoding a slice image data set composed of a plurality of slice image data of a subject,
Acquisition means for acquiring information about an interval in physical space with respect to a pixel interval in slice image data and an interval in physical space with respect to an interval between slice image data;
Encoding means for performing motion compensation encoding on each slice image data in the slice image data set;
And determining means for determining a motion search range when performing motion compensation encoding by the encoding means based on the information acquired by the acquiring means.

  According to the present invention, it is possible to efficiently encode a set of image data composed of a plurality of slice image data of a subject such as CT and MRI while maintaining high encoding accuracy.

The figure which shows an example of the whole structure of CT apparatus in embodiment. The figure which shows an example of the hardware constitutions of a control apparatus. The block block diagram of the image coding part in embodiment. The conceptual diagram for demonstrating a slice space | interval. The conceptual diagram for demonstrating an effective visual field. The flowchart which shows the process of the search range determination part in 1st Embodiment. The figure for demonstrating the relationship between a pixel space | interval, a slice space | interval, and a motion amount. The flowchart which shows the process of the motion compensation encoding part in 1st Embodiment. The figure for demonstrating a motion search range. The flowchart which shows the process of the search range determination part in 2nd Embodiment. The figure for demonstrating the relationship between a search angle and a motion search range. The flowchart which shows the process of the motion compensation encoding part in 3rd Embodiment.

  Embodiments according to the present invention will be described below in detail with reference to the drawings. In the embodiment described below, a CT apparatus is used as an example of a slice image generation apparatus. However, the present invention is not limited to this, and other apparatuses that perform slice image generation, such as an MRI apparatus, may be used. In CT and MRI, various parameters are set during imaging (scanning) and image reconstruction. Among them, there are a slice interval and an effective field of view (FOV). The slice interval means a distance in the physical space between adjacent slice images, and the effective visual field means a range in the physical space expressed in the slice image.

FIG. 1 is a diagram illustrating an overall configuration example of a CT apparatus according to an embodiment. The CT apparatus is roughly divided into a CT imaging apparatus 101 and a control apparatus 102 that controls the CT imaging apparatus 101. The CT imaging apparatus 101 is an apparatus that performs CT imaging, and generally includes a bed on which a subject lies and a gantry that irradiates X-rays and acquires sensor data (raw data). The control device 102 is a device that performs instructions to the CT imaging device, slice image reconstruction, and encoding.
The control device 102 includes an imaging condition instruction unit 103, an image reconstruction unit 104, and an image encoding unit 105. A hardware configuration example of the control device 102 is shown in FIG.

  The control device 102 has the same configuration as a general personal computer. That is, the control device 102 includes a bus 210 and a CPU 201, RAM 202, ROM 203, keyboard 204, mouse 205, display device 206, external storage device 207, storage medium drive 208, and I / F 209 connected to the bus 210. .

  The CPU 201 controls the entire apparatus using programs and data stored in the RAM 202 and the ROM 203 and executes an image encoding process to be described later. The RAM 202 stores programs and data downloaded from the external device via the external storage device 207, the storage medium drive 208, or the I / F 209. The RAM 202 is also used as a work area used when the CPU 201 executes various processes. The ROM 203 stores a boot program, a setting program for the apparatus, and data. A keyboard 204 and a mouse 205 are devices that transmit an instruction input from a user to the CPU 201. The display device 206 includes a CRT, a liquid crystal screen, and the like, and can display information such as images and characters. The display device 206, the keyboard 204, and the mouse 205 constitute a user interface.

  The external storage device 207 is a large-capacity information storage device such as a hard disk drive device. Here, an OS and a program for image encoding processing to be described later are stored. In the embodiment, it is assumed that image data to be encoded is also stored in the external storage device 207. The storage medium drive 208 reads programs and data recorded on a storage medium such as a CD-ROM or DVD-ROM, and the read programs and data are stored in the RAM 202 and the external storage device 207. Note that a program for image encoding processing and an image to be encoded, which will be described later, may be recorded on this storage medium. In this case, the storage medium drive 208 stores these programs and data under the control of the CPU 201. A predetermined area on the RAM 202 is loaded.

  The I / F 209 connects the present apparatus and an external apparatus so that they can communicate with each other. For example, image data to be encoded is input to the RAM 202 or the external storage device 207 of the present apparatus via the I / F 209, or conversely, the image encoded data generated from the RAM 202 or the external storage apparatus 207 of the present apparatus is input. Can be output outside the device. The CT imaging apparatus 101 is also connected via this I / F 209.

  In the above configuration, when the CPU 201 executes a program stored in the RAM or ROM, the CPU 201 functions as the imaging condition instruction unit 103, the image reconstruction unit 104, and the image encoding unit 105 in FIG.

  Returning to the description of FIG. The CT imaging apparatus 101 performs a series of imaging according to imaging conditions from the imaging condition instruction unit 103. The image reconstruction unit 104 receives sensor data imaged by the CT imaging apparatus 101 via the I / F 209 and temporarily stores it in the external storage device 207. Then, the image reconstruction unit 104 generates slice image information according to a predetermined image reconstruction condition. The slice image information includes slice image data and header information, and the header information includes conditions such as shooting conditions and image reconstruction conditions in addition to image parameters such as width and height. The image encoding unit 105 receives a series of slice image data, performs encoding, and stores the encoded image as a file in the external storage device 207.

  In the foregoing, the configuration of the CT apparatus in the embodiment has been roughly described. Next, a specific example as the image encoding unit 105 will be described.

[First Embodiment]
FIG. 3 is a block configuration diagram of the image encoding unit 105 according to the present embodiment. The image encoding unit 105 includes a slice image data set input unit 301, a search range determination unit 302, a motion compensation encoding unit 303, and a code output unit 304. In such a configuration, a method for encoding a slice image will be described below.

First, as a premise, a slice image data set to be encoded by the image encoding unit 105 according to the present embodiment includes a plurality of slice image data and header information. The header information includes shooting conditions, but at least the following information is included.
The number of pixels W in the horizontal direction of the slice image (hereinafter referred to as the horizontal direction)
The number of pixels H in the slice image vertical direction (hereinafter referred to as the vertical direction)
・ Horizontal effective field of view FOVx (unit: mm)
・ Vertical effective field of view FOVy (unit: mm)
・ Slice interval Pz (unit is mm)

  The slice image data set input unit 301 inputs a slice image data set. This slice image data set is a plurality of slice image data obtained from the sensor data acquired by the CT imaging apparatus 101 under the same image reconstruction conditions. The same image reconstruction condition indicates that each slice image data is generated by unifying the slice interval, the effective field of view, and the like to form one slice image data set.

  Here, the slice interval will be described. The slice interval is a value that determines the distance between adjacent slice positions, and is designated by the operator of the CT apparatus according to the site to be diagnosed, symptoms, and the like. For example, FIG. 4 is an example of slicing so as to be orthogonal to the body axis of the human body (subject), and is a conceptual diagram showing the relationship between the slice position and the slice interval. In the figure, reference numeral 401 denotes a human body axis, reference numeral 402 denotes a human body, reference numerals 403 and 404 denote slice positions in adjacent slice images, and reference numeral 405 denotes a slice interval (Pz). In the example shown in the figure, the slice interval 405 is 1 mm.

  Next, the effective visual field will be described. The effective visual field is a value that defines a range to be drawn as a slice image in a slice plane at a certain slice position, and is designated by the operator of the CT apparatus according to a site to be diagnosed, a symptom, and the like. For example, FIG. 5 shows an example of a slice plane orthogonal to the human body axis as a conceptual diagram. Reference numeral 501 in FIG. 5 indicates a slice of the human chest, and a frame indicated by reference numeral 502 is an effective visual field. The effective visual field has a horizontal length (unit: mm) of FOVx and a vertical length of FOVy. When the number of pixels of the slice image to be generated is the same, increasing the effective field of view increases the pixel interval (distance (mm) in the physical space represented by two adjacent pixels), and conversely, reducing the effective field of view results in a pixel. The interval is also reduced.

  For example, if FOVx = FOVy = 100 mm and the number of horizontal pixels W = 500 in the effective field of slice image data, the distance in the physical space represented by two adjacent pixels in the slice image data is 100/500 = 0.2 mm. If FOVx = FOVy = 50 mm, the distance in the physical space between two adjacent pixels in the slice image data is 50/500 = 0.1 mm.

  Returning to FIG. 3, the search range determination unit 302 determines a search range used for motion compensation. The processing performed by the search range determination unit 302 will be described using the processing flow of FIG.

First, in step S601, the search range determination unit 302 sets a reference parameter. In the present embodiment, the following five reference parameters are used.
-Horizontal reference search range stdRx (unit: pixels)
-Vertical reference search range stdRy (unit is pixel)
-Horizontal reference pixel interval stdPx (unit: mm / pixel)
Reference pixel interval stdPy in vertical direction (unit: mm / pixel) Reference slice interval stdPz (unit: mm)
An arbitrary value may be set by the operator as the above value, or a predetermined value may be designated. For example, stdRx = 1 (pixel), stdRy = 1 (pixel), stdPx = 1 (mm / pixel), stdPy = 1 (mm / pixel), stdPz = 1 (mm), and the like. When these values are set, the process proceeds to step S602.

  Next, in step S602, the search range determination unit 302 acquires the width W and height H of the slice image. As described above, W is the number of pixels in the horizontal direction, and H is the number of pixels in the vertical direction. These values can be obtained from the header information in the slice image information.

  Next, in step S603, the search range determination unit 302 acquires a horizontal effective visual field FOVx and a vertical effective visual field FOVy. As described above, the effective visual field is a value set by the operator when the slice image is reconstructed. This value may be obtained by referring to the header information in the slice image information. If the effective visual fields FOVx and FOVy are acquired, the process proceeds to step S604.

  In step S604, the search range determination unit 302 calculates the physical pixel interval Px in the horizontal direction and the physical pixel interval Py in the vertical direction in the slice image data set to be encoded. These values are obtained by the following equation (1).

  Next, the search range determination part 302 acquires the slice space | interval Pz in the slice image data set which is an encoding object in step S605. As described above, the slice interval is a value set by the operator when the slice image is reconstructed. This value may be obtained by referring to the header information in the slice image information.

  In the next step S606, the search range determination unit 302 calculates a horizontal direction search range Rx and a vertical direction search range Ry in motion compensation. These values may be scaled based on the pixel interval and slice interval values. Specifically, it is calculated based on the following equation (2).

  Here, the relationship between the search range, the slice interval, and the pixel interval will be described. If the slice interval and the pixel interval are determined as physical sizes, the pixels in each slice image data can be regarded as voxels in a three-dimensional space. However, as described above, the operator sets arbitrary values for the pixel interval and the slice interval, and does not necessarily become a general isotropic voxel.

  For example, FIG. 7A shows voxels when the pixel intervals Px and Py and the slice interval Pz of the image reconstruction condition have the same value. Since Px, Py, and Pz have the same value, this case is isotropic. FIG. 7D is a diagram in which a part of the tissue is three-dimensionally expressed by the isotropic voxel of FIG. The z axis is the slice interval direction (body axis direction), and the x and y planes are slice planes. FIG. 7G shows the motion by superimposing a part of two adjacent slice images at this time.

  In general, the horizontal right direction of an image is expressed as a positive direction of the x-axis, and the vertical downward direction is expressed as a positive direction of the y-axis. Then, if the motion amount (corresponding to the motion vector) indicated by the arrow in FIG. 7G is shown in the (x, y) format, (−2, +1) is obtained. Based on this point, further examination will be made.

  FIG. 7B shows voxels when the slice interval Pz is fixed at the same value as in FIG. 7A and the pixel intervals Px and Py are larger than Pz. In this case, it becomes anisotropic. In the case of such a relationship, since the range expressed per pixel of the slice image becomes wider than in the case of FIG. 7A, as a result, the change between the slice images becomes smaller. FIG. 7E shows a three-dimensional representation of a part of the tissue with the anisotropic voxels in FIG. 7B. Further, FIG. 7H shows a part of two adjacent slice images superimposed at this time. It can be seen that the amount of motion indicated by the arrow in FIG. 7H is (−1, +1), and the magnitude (absolute value) is smaller than that in FIG.

  FIG. 7C shows voxels when the pixel intervals Px and Py are fixed to the same values as in FIG. 7A and the slice interval Pz is larger than Px and Py. Again, this is anisotropic. In the case of such a relationship, the range expressed per pixel of the slice image is the same as in the case of FIG. 7A, but the distance between the slice images becomes large, resulting in a change between the slice images. growing. FIG. 7F shows a three-dimensional representation of a part of the tissue with the anisotropic voxels in FIG. FIG. 7 (i) shows a part of two adjacent slice images superimposed at this time. The amount of movement indicated by the arrow in FIG. 7 (i) is (−6, −4), and it can be seen that the magnitude (absolute value) is larger than FIG. 7 (g).

  From the above, it can be said that the amount of motion between slice images is proportional to the slice interval pz and inversely proportional to the pixel intervals Px and Py.

  As described above, the search range of the slice image data set to be encoded can be determined according to the image reconstruction condition by the processing from steps S601 to S606.

  In this embodiment, it is assumed that the slice information includes the slice interval in the header information of the slice image data. However, when the slice position is included in the header information instead of the slice interval, the value is used. Also good. The same can be achieved by using the difference in slice position values between adjacent slice image data as the slice interval.

  In the present embodiment, it is assumed that the effective visual field is included in the header information of the slice image data. However, when the pixel interval itself is included in the header information, the value may be used. In that case, S603 and S604 in FIG. 6 can be omitted.

  Returning to FIG. 3, the motion compensation encoding unit 303 encodes the slice image using motion compensation. Hereinafter, the processing performed by the motion compensation encoding unit 303 will be described with reference to the flowchart shown in FIG.

Prior to the description, the slice image data set will be described. As described above, the slice image data set is a series of slice image data along the body axis obtained under the same image reconstruction conditions. In embodiments, the slice image data in the slice image data sets, in order from the _{beginning, I 0, I 1, I} 2, ..., expressed as I _n. The motion compensation coding unit 303, the top slice image data I _0, encodes sequentially one by one until the slice image data I _n in this order. In this encoding, a slice image to be encoded is referred to as I _t, and a slice image referred to during motion compensation is referred to as I _r .

First, the motion compensation coding unit 303 encodes the slice image data I ₀ alone (step S801). This is because the first piece in the slice image data set cannot take a difference. It can be easily understood that it corresponds to an intra frame in moving picture coding. The encoding method may be any lossless encoding, and the type thereof is not limited. For example, a technique such as JPEG, JPEG2000, JPEG-LS may be used. When the encoding of the slice image data I0 is completed, the motion compensation encoding unit 303 advances the process to step S802.

  In step S <b> 802, the motion compensation encoding unit 303 sets an initial value “1” to a counter k indicating the number of the slice image being encoded. When this process is finished, the motion compensation encoding unit 303 proceeds to step S803.

In step S803, the motion compensation encoding unit 303 sets the slice image data I _k-1 as the slice image data I _r that is referred to by motion compensation. When the process of step S803 is performed for the first time, the value of the counter k is “1”, which means that the slice image data I _r to be referred to becomes the slice image data I ₀ .

In the next step SS804, the motion compensation coding unit 303, the slice image data I _k, is set as a slice image data I _t to be coded. In step S805, the motion compensation encoding unit 303 divides the slice image data It to be encoded into a plurality of blocks. The divided block is a coding unit for motion compensation. Note that the raster scan order in units of blocks is the order in which encoding is performed. Therefore, the blocks in this order are expressed as B0, B1,.

  In step S806, the motion compensation encoding unit 303 sets an initial value “0” in the counter m indicating the number of the block to be encoded, and moves the process to step S807.

In step S807, the motion compensation coding unit 303 performs motion search block B _m to be coded. The motion search is for searching for a block (hereinafter referred to as a reference block B _r ) in the reference slice image data I _r that minimizes the cost of the block B _{m being} processed.

As the motion search range, the values Rx and Ry determined by the search range determination unit 302 may be used. 9 illustrates the search range in the reference slice image data I _r. Reference numeral 901 in FIG. 9 refers to the area of the block B _m the same position of the coding target. Reference numeral 902 _denotes a search range in the reference slice image data Ir, which means that a search is performed in a range of ± Rx pixels in the horizontal direction and ± Ry pixels in the vertical direction.

With regard to the cost calculation method for motion search, the absolute value sum of each pixel in the encoding target block and each pixel in the candidate block of the reference block within the search range is calculated to obtain the absolute value sum of the differences. Therefore, the candidate block with the minimum absolute value sum may be determined as the final reference block _Br . Note that the cost calculation method is not limited to this, the sum of mean square errors may be calculated, and each region is actually encoded using the encoding means after motion compensation, and the amount of codes is used as the cost. Also good. As for the search method, a full search may be performed, or a method such as step search or diamond search may be used for speeding up.

By this processing of step S807, the relative coordinate position of the block Bm to be coded relative to the position of the reference block B _r is extracted as the motion vector data. This motion vector data may be output as it is, or may be encoded and output by some method.

At next step S808, the motion compensation coding unit 303 generates a difference block between the block B _m to be coded and the reference block B _r, it proceeds to processing in step S809.

  In step S809, the motion compensation encoding unit 303 encodes the difference block generated in the previous step to generate encoded data. For this encoding method, an existing technology such as JPEG, JPEG2000, JPEG-LS may be used. When this process is finished, the motion compensation encoding unit 303 moves to step S810.

  In step S810, the motion compensation encoding unit 303 compares the value indicated by the counter m with the number of all blocks to determine whether or not the encoding process has been completed for all blocks of the target slice image data. . If not, the motion compensation encoding unit 303 moves the process to step S811, and if yes, moves the process to step S812.

  In step S811, the motion compensation encoding unit 303 increases the counter m by “1”, thereby setting the next block as an encoding target. Then, the motion compensation encoding unit 303 returns the process to step S807.

  On the other hand, when the process proceeds to step S812, the motion compensation encoding unit 303 compares the value of the counter k with n to determine whether or not the encoding of the slice image data set (all slice image data) has been completed. Determine whether. If not, the motion compensation encoding unit 303 increments the value of the counter k by “1” and returns the process to step S803. On the other hand, when the encoding process of the slice image data set is completed (when the determination in step S803 is Yes), the motion compensation encoding unit 303 ends this process.

  Through the above processing, a slice image data set composed of a plurality of slice images can be encoded using motion compensation. When the encoding process of the image data set is completed, the code output unit 304 in FIG. 3 outputs the generated encoded data together with the header information necessary for decoding as a file to the external storage device 207 or the like. The output destination may be a network, another device, or a portable storage medium, and the type thereof is not limited.

  According to the above method, the search range in motion compensation can be set appropriately based on the relationship between the slice interval and the pixel interval, redundant motion search processing can be reduced, and efficient encoding can be performed. .

[Second Embodiment]
In the first embodiment, as shown in Expression (2), the search range determination unit 302 uses a method of scaling based on the values of the pixel intervals Px and Py and the slice interval pz based on the reference search range. As described above, the amount of motion depends on the slice interval and the pixel interval. However, the amount of motion in the reference pixel interval and the reference slice interval in the first embodiment depends on the shape of the photographic object. In order to enable setting of a search range in consideration of the shape of the photographed object, an angle (hereinafter referred to as a search angle) may be determined as a reference for defining the search range. In the second embodiment, a method of determining based on the search angle will be described as a method of determining the search range. The apparatus configuration is the same as that of the first embodiment, and the description thereof is omitted.

  Processing for obtaining the motion search range of the search range determination unit 302 in the second embodiment will be described with reference to the flowchart of FIG.

  First, the search range determination unit 302 sets a reference parameter in step S1001. In the second embodiment, the reference parameter is the search angle θ. This value may be set to an arbitrary value by the operator, or a predetermined value may be designated. For example, θ = π / 3 (rad).

  Here, the search angle θ will be described with reference to FIG. Reference numeral 1101 in FIG. 11 denotes slice image data to be encoded, and reference numeral 1102 denotes a motion search source region in the slice image data to be encoded. Reference numeral 1103 denotes a slice image referred to in motion search, and reference numeral 1104 denotes a motion search range defined by the search angle θ in the reference slice image data. As can be seen from FIG. 11, it can be seen that the search range increases as the distance of the z-axis (body axis) from the encoding target slice image data to the reference slice image data increases. That is, by determining the search angle θ so that the change in the shape of the photographed object in the z-axis direction is within this search range, a more appropriate search range can be determined. In the case of a CT apparatus, the search angle θ may be obtained based on the amount of change in the z-axis direction (generally the body axis direction) expected in a desired tissue.

  Returning to FIG. 10, after setting the search angle θ, the search range determination unit 302 advances the process to step 1002.

  Steps SS1002 to S1005 may be the same as steps S602 to S605 in FIG. 6 of the first embodiment.

  In step S1006, the search range determination unit 302 calculates a horizontal direction search range Rx and a vertical direction search range Ry in motion compensation. These values are determined based on the pixel interval Px, Py, the slice interval Pz, and the search angle θ in a three-dimensional space. Specifically, the calculation is performed by adding tan θ (tangent) as shown in the following equation (3).

  The encoding process after the search range is determined as described above is the same as that in the first embodiment.

  As described above, according to the second embodiment, in addition to the operational effects of the first embodiment, the search angle corresponding to the shape of the desired photographing object can be reflected in the determination of the search range.

[Third Embodiment]
In the first embodiment, the method of performing motion search based on the search range determined by the search range determination unit 302 in the motion compensation encoding unit 303 has been described. In some cases, it may be desired to reduce the time required for encoding as compared to the first embodiment. In this case, the motion search in the slice image data set having a small compression performance improvement effect or a small search range may be omitted. In the third embodiment, for speeding up, a technique that makes it possible to bypass the motion search process depending on the value of the search range will be described. The apparatus configuration is the same as that of the first embodiment, and the description thereof is omitted.

  FIG. 12 is a flowchart of the encoding process of the motion compensation encoding unit 303 in the third embodiment.

  Steps S1201 to S1204 may be the same as steps S801 to S804 in FIG. 8 of the first embodiment.

  In step S1205, the motion compensation encoding unit 303 determines whether the search ranges Rx and Ry are each equal to or less than the threshold value T. This threshold value T may be set according to the processing capability of the processing system and the required throughput. For example, T = 1 may be set. When the search ranges Rx and Ry are both equal to or smaller than the threshold value, the motion compensation encoding unit 303 advances the process to step S1209. On the other hand, if either of the search ranges Rx and Ry exceeds the threshold T, the process proceeds to step S1206. Note that the motion vector in the case where the process from step S1205 to step S1209 is skipped and the process proceeds to step S1209 is assumed to be (0, 0).

  Steps S1206 to S1214 may be the same as steps S805 to S813 in FIG. 8 of the first embodiment.

  With the processing flow as described above, motion search can be omitted for a slice image data set with a small search range, and the processing speed can be increased.

  In addition to the above method, the search range determination unit may be designed such that the search range becomes 0, and the motion search is virtually not performed. Since the expression (2) in the first embodiment is obtained by rounding up, it takes a value of 1 or more. This is to make it possible to cover the motion search range after the decimal point by rounding up, but by rounding this rounding up to the following equation (4), search range = 0 is generated. Can be made.

[Modification]
The present invention is not limited to the embodiment described above. For example, although the above embodiment has been described on the assumption that the motion search accuracy is 1 pixel, it may be designed to correspond to 1/2 accuracy or 1/4 accuracy. In this case, for example, Equation (2) used in determining the search range may be modified as shown in the following equation, where N is a value indicating the pixel accuracy value (N = 1, 2, 4,...). .

  In the above-described embodiment, the search range is obtained for each of x and y. However, in general, the pixel interval is often designed to be x = y, and in that case, only one of the values is used. What is necessary is just to determine a search range.

  In the above-described embodiment, one search range is determined for the slice image data set, and the search range is used for all slice images. However, this search range is applied only to the representative image. The slice image may be dynamically changed. In such a case, the design may be designed such that the search range distribution actually used is fed back and the search range of the next slice image is determined.

  In addition, as represented by the equation (2), in the above-described embodiment, the equation is such that the motion search range is linearly changed. However, when it is desired to suppress the search range for speeding up, or to suppress the slice image data set for motion search, this may be modified. For example, when the upper limit search range is Tmax, Equation (2) may be modified as the following equation.

  In the above-described embodiment, the motion search range is determined based on mathematical formulas, but this may be realized by a lookup table.

  In the above embodiment, the processing of the control device 102 in the CT apparatus 100 has been described. However, the control device 102 is the same as an information processing device such as a general personal computer (PC) in hardware. Therefore, data captured by the CT imaging apparatus 101 may be temporarily stored in a portable storage medium, or may be encoded by a PC via a network.

(Other examples)
The present invention supplies a program that realizes one or more functions of the above-described embodiments to a system or apparatus via a network or a storage medium, and one or more processors in a computer of the system or apparatus read and execute the program This process can be realized. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

DESCRIPTION OF SYMBOLS 101 ... CT imaging device, 102 ... Control apparatus, 103 ... Imaging condition instruction | indication part, 104 ... Image reconstruction part, 105 ... Image coding part, Slice image data set input part, 302 ... Search range determination part, 303 ... Motion compensation Encoding unit, 304 ... code output unit

Claims (6)

An image encoding device for encoding a slice image data set composed of a plurality of slice image data of a subject,
Acquisition means for acquiring information about an interval in physical space with respect to a pixel interval in slice image data and an interval in physical space with respect to an interval between slice image data;
Encoding means for performing motion compensation encoding on each slice image data in the slice image data set;
An image encoding apparatus comprising: a determination unit that determines a motion search range when performing motion compensation encoding of the encoding unit based on information acquired by the acquisition unit. The determining means includes
Inversely proportional to the physical space distance to the pixel spacing in the slice image data,
A value proportional to a distance in physical space between slice image data along the body axis is determined as the search range;
The image coding apparatus according to claim 1. The determination means further determines, as a search range, a value proportional to the tangent of the search angle θ in the set three-dimensional space.
The image coding apparatus according to claim 2, wherein: The encoding means includes
A judgment means for judging whether or not the search range is equal to or less than a preset threshold;
The slice image data is encoded by omitting a motion vector search process when the determination unit determines that the search range is equal to or less than the threshold value. The image encoding device according to any one of claims. A control method of an image encoding device for encoding a slice image data set composed of a plurality of slice image data of a subject,
An obtaining step for obtaining information on an interval in the physical space with respect to a pixel interval in the slice image data and an interval in the physical space with respect to an interval between the slice image data;
An encoding step in which encoding means performs motion compensation encoding on each slice image data in the slice image data set; and
And a determination step of determining a motion search range when performing motion compensation encoding in the encoding step based on the information acquired in the acquisition step.   The program for making a computer function as each means of the apparatus of any one of Claim 1 thru | or 4 when a computer reads and executes.

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