JP6748508B2 - Image coding apparatus and control method thereof - Google Patents

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 intervals have been increased in density, and imaging conditions have been diversified, and the number of slice images has increased. It is becoming common to generate 2000 to 3000 tomographic images even if only one part of the human body such as the chest or abdomen is imaged, and the amount of data is huge. 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 losslessly encoded individually, the compression effect cannot be expected so much.

With the recent development of imaging technology, the density of slice images is increasing, such as 0.5 mm and 1.0 mm. Therefore, there is known a technique of improving compression performance by generating a difference image between a slice image to be encoded and an adjacent slice image and encoding the generated difference image (Patent Document 1).

There is also known a technique for improving compression performance by using the concept of motion compensation used in moving images when generating a difference between slice images (Non-Patent Document 1). Further, there is also known a method of determining a motion search range that influences a processing speed and a motion estimation accuracy in motion compensation according to how many frames are apart from a reference frame (Patent Document 2).

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

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

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

In Non-Patent Document 1, the search range is set to a fixed value, but depending on the imaging conditions and reconstruction conditions of the slice images, the search range becomes redundantly wide and the processing speed decreases, or the search range is narrow and appropriate. It is possible 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 based only on the slice interval because the slice image has a different range represented by one pixel depending on the image reconstruction conditions.

The present invention has been made in view of the above points, and it is an object of the present invention to provide a technique for easily determining a search range in motion compensation according to 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, the image coding apparatus 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,
An acquisition unit that acquires 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 a determination unit that determines a motion search range when performing motion compensation coding by the coding unit based on the information acquired by the acquisition unit.

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 the CT apparatus in embodiment. The figure which shows an example of the hardware constitutions of a control apparatus. FIG. 3 is a block configuration diagram of an image encoding unit according to the embodiment. The conceptual diagram for demonstrating a slice space|interval. The conceptual diagram for demonstrating an effective visual field. 6 is a flowchart showing the processing of the search range determination unit in the first embodiment. The figure for demonstrating the relationship between a pixel space|interval, a slice space|interval, and a motion amount. 6 is a flowchart showing the processing of the motion compensation encoding unit according to the first 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. 9 is a flowchart showing the processing of the motion compensation encoding unit according to the third embodiment.

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

FIG. 1 is a diagram showing an example of the overall configuration of a CT apparatus according to an embodiment. The CT device is roughly divided into a CT imaging device 101 and a control device 102 that controls the CT imaging device 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 for instructing a CT imaging device, reconstructing slice images, and encoding.
The control device 102 includes a shooting condition instruction unit 103, an image reconstruction unit 104, and an image coding unit 105. FIG. 2 shows an example of the hardware configuration of the control device 102.

The control device 102 has the same configuration as a general personal computer. That is, the control device 102 has a bus 210, and a CPU 201, a RAM 202, a ROM 203, a keyboard 204, a mouse 205, a display device 206, an external storage device 207, a storage medium drive 208, and an I/F 209 which are 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 also executes an image encoding process described later. The RAM 202 stores programs and data downloaded from the external storage device 207, the storage medium drive 208, or the external device via 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 of this device, and data. The keyboard 204 and the mouse 205 are devices that transmit an instruction input from the 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. An OS and a program for image coding processing described later are stored here. Further, in the embodiment, it is assumed that the external storage device 207 also stores image data to be encoded. The storage medium drive 208 reads out programs and data recorded in a storage medium such as a CD-ROM or a DVD-ROM, and the read programs and data are stored in the RAM 202 or the external storage device 207. It should be noted that a program for an image encoding process, which will be described later, and an image to be encoded may be recorded in this storage medium. In that case, the storage medium drive 208 controls these programs and data under the control of the CPU 201. It is loaded in a predetermined area on the RAM 202.

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

In the above configuration, the CPU 201 executes the program stored in the RAM or the ROM to function as the shooting condition instruction unit 103, the image reconstructing unit 104, and the image encoding unit 105 in FIG. 1.

Returning to the explanation of FIG. The CT imaging apparatus 101 performs a series of imaging according to the imaging conditions from the imaging condition instruction unit 103. The image reconstruction unit 104 receives the sensor data captured 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 is composed of slice image data and header information. The header information includes image parameters such as width and height as well as conditions such as imaging conditions and image reconstruction conditions. The image encoding unit 105 receives a series of slice image data, encodes it, and stores it in the external storage device 207 as a file.

The configuration of the CT apparatus according to the embodiment has been roughly described above. Next, a specific example of 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 coding unit 105 includes a slice image data set input unit 301, a search range determination unit 302, a motion compensation coding unit 303, and a code output unit 304. A method for encoding a slice image in such a configuration will be described below.

First, as a premise, the 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.
-Number of pixels in the slice image horizontal direction (hereinafter, horizontal direction) W
-Number H of pixels in the slice image vertical direction (hereinafter, 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 by using the sensor data acquired by the CT imaging apparatus 101 under the same image reconstruction conditions. The same image reconstruction condition means that each slice image data is generated by unifying slice intervals, effective fields of view, etc., and one slice image data set is obtained.

Here, the slice interval will be described. The slice interval is a value that determines the distance between adjacent slice positions, and is specified 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 slice positions and slice intervals. In the figure, reference numeral 401 is a human body axis, reference numeral 402 is a human body, reference numerals 403 and 404 are slice positions in adjacent slice images, and reference numeral 405 is a slice interval (Pz). In the illustrated case, 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 on the slice plane at a certain slice position, and is specified by the operator of the CT apparatus according to the site to be diagnosed, symptoms, 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 chest of the human body, and the frame indicated by reference numeral 502 is the effective visual field. The horizontal length (unit is mm) of this effective visual field is FOVx, and the vertical length is FOVy. When the number of pixels of the slice image to be generated is the same, the pixel interval (distance (mm) in the physical space expressed by two adjacent pixels) increases when the effective field of view is increased, and conversely, when the effective field of view is decreased The interval also becomes smaller.

For example, if FOVx=FOVy=100 mm and the number of pixels in the horizontal direction W of the slice image data in the effective field of view=the number of pixels in the vertical direction H=500, the distance in the physical space represented by two adjacent pixels in the slice image data is , 100/500=0.2 mm. Then, 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 the 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 this embodiment, the following five reference parameters are used.
-Horizontal reference search range stdRx (unit is pixel)
-Standard reference range stdRy in the vertical direction (unit is pixel)
・Reference pixel spacing stdPx in the horizontal direction (unit: mm/pixel)
-Standard pixel interval stdPy in the vertical direction (unit is mm/pixel-reference slice interval stdPz (unit is mm)
The above values may be set to arbitrary values by the operator, or predetermined values 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. After setting these values, the process proceeds to step S602.

Next, in step S602, the search range determination unit 302 acquires the width W and the 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 acquired from the header information in the slice image information.

Next, in step S603, the search range determination unit 302 acquires the effective visual field FOVx in the horizontal direction and the effective visual field FOVy in the vertical direction. As described above, the effective visual field is a value set by the operator when the slice image is reconstructed. This value may be acquired by referring to the header information in the slice image information. When 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 a physical pixel interval Px in the horizontal direction and a 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, in step S605, the search range determining unit 302 acquires the slice interval Pz in the slice image data set that is the encoding target. As described above, the slice interval is a value set by the operator when reconstructing slice images. This value may be acquired by referring to the header information in the slice image information.

In next step S606, the search range determination unit 302 calculates the horizontal search range Rx and the vertical search range Ry in motion compensation. These values may be obtained by scaling the reference search range based on the values of the pixel interval and the slice interval. 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. When the slice interval and the pixel interval are determined as physical sizes, the pixel in each slice image data can be regarded as a voxel in the three-dimensional space. However, as described above, the operator sets arbitrary values for the pixel interval and the slice interval, and does not always become a general isotropic voxel.

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

Generally, the horizontal right direction of the image is expressed as the positive direction of the x-axis and the vertical downward direction is expressed as the positive direction of the y-axis, and this embodiment also follows it. Then, if the motion amount (corresponding to the motion vector) indicated by the arrow in FIG. 7G is shown in the (x, y) format, it becomes (-2, +1). Further consideration will be given to this point.

FIG. 7B is a voxel when the slice interval Pz is fixed to the same value as in FIG. 7A and the pixel intervals Px and Py are set to values larger than Pz. In this case, it becomes anisotropic. In the case of such a relationship, the range represented by one pixel of the slice image becomes wider than that in the case of FIG. 7A, and as a result, the change between slice images becomes small. FIG. 7E is a diagram in which a part of the tissue is three-dimensionally expressed by the anisotropic voxels of FIG. 7B. Further, FIG. 7(h) shows a part of two adjacent slice images at this time by overlapping. It can be seen that the amount of movement indicated by the arrow in FIG. 7(h) is (−1, +1), and its magnitude (absolute value) is smaller than that in FIG. 7(g).

FIG. 7C shows a voxel in which the pixel intervals Px and Py are fixed to the same values as in FIG. 7A and the slice interval Pz is set to a value larger than Px and Py. Also in this case, it is anisotropic. In the case of such a relationship, the range represented by one pixel of the slice image is the same as that in the case of FIG. 7A, but the distance between the slice images becomes large, and as a result, the change between slice images is growing. FIG. 7(f) is a diagram in which a part of the tissue is three-dimensionally expressed by the anisotropic voxels of FIG. 7(c). Further, FIG. 7I shows a part of two adjacent slice images at this time by superimposing them. It can be seen that the amount of movement indicated by the arrow in FIG. 7I is (−6, −4), and the magnitude (absolute value) thereof is larger than that in FIG.

From the above, it can be said that the amount of movement between slice images has a relationship that 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 conditions by the processing of steps S601 to S606.

In the present embodiment, it is assumed that the header information of the slice image data includes the slice interval, but if the slice position is included in the header information instead of the slice interval, that value is used. Good. The same can be achieved by using the difference between the slice position values between adjacent slice image data as the slice interval.

Further, in the present embodiment, it is assumed that the header information of the slice image data includes the effective visual field, but when the pixel interval itself is included in the header information, that 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. The processing performed by the motion compensation coding unit 303 will be described below with reference to the flowchart shown in FIG.

Before explanation, 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, the slice image to be encoded will be referred to as I _t, and the slice image referred to during motion compensation will be referred to as I _r .

First, the motion compensation coding unit 303 independently codes the slice image data I ₀ (step S801). This is because the first one in the slice image data set cannot take the difference. It is easy to say that it corresponds to an intra frame in video encoding. Any encoding method may be used as long as it is lossless encoding, and any type thereof may be used, and for example, a technique such as JPEG, JPEG2000, JPEG-LS may be used. Upon completion of encoding the slice image data I0, the motion compensation encoding unit 303 advances the process to step S802.

In step S802, the motion compensation encoding unit 303 sets an initial value “1” to a counter k indicating the position of the slice image being encoded. Upon completion of this process, the motion compensation coding unit 303 moves to step S803.

In step S803, the motion compensation encoding unit 303 sets the slice image data I _k−1 as slice image data I _r to be referred to in 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 referred slice image data I _r is the slice image data I ₀ .

In next step SS804, the motion compensation encoding unit 303 sets the slice image data I _k as the slice image data I _{t to be} encoded. Then, 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 blocks serve as coding units for motion compensation. Note that the raster scan order in blocks is the encoding order. 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” to 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 encoding unit 303 performs a motion search of the block B _{m to be} encoded. The motion search is a search 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. FIG. 9 illustrates the search range in the reference slice image data I _r . Reference numeral 901 in FIG. 9 means an area at the same position as the block B _m to be encoded. Reference numeral 902 represents a search range in the reference slice image data I _r , which means that the search is performed in a range of ±Rx pixels in the horizontal direction and ±Ry pixels in the vertical direction.

As for the cost calculation method for motion estimation, the sum of absolute values of each pixel in the block to be coded and each pixel in the candidate block of the reference block in the search range is calculated as the sum of absolute differences. Then, the candidate block having the smallest sum of absolute values may be determined as the final reference block B _r . Note that the cost calculation method is not limited to this, and the sum of mean square errors may be calculated, or each area is actually coded using the coding means after motion compensation, and the code amount is used as the cost. 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 the process of step S807, the relative coordinate position of the block Bm to be encoded with respect to the position of the reference block B _r is extracted as motion vector data. This motion vector data may be output as it is, or may be encoded by some method and output.

In the next step S808, the motion compensation coding unit 303 generates a difference block between the coding target block B _m and the reference block B _r, and moves to the processing of 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 ends, 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 total number of blocks to determine whether or not the encoding process for all blocks of the slice image data of interest has been completed. .. In the case of no, the motion compensation encoding unit 303 moves the process to step S811, and in the case of yes, moves the process to step S812.

In step S811, the motion compensation encoding unit 303 increments the counter m by “1” to set the next block as an encoding target. Then, the motion compensation coding unit 303 returns the processing 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 the encoding of the slice image data set (all slice image data) is completed. Determine whether. In the case of no, 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.

With the above processing, a slice image data set including a plurality of slice images can be encoded while 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 required 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 its type 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 coding can be performed. ..

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

The process of obtaining the motion search range by the search range determination unit 302 according to 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) or the like.

Here, the search angle θ will be described with reference to FIG. 11. 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. Further, reference numeral 1103 is a slice image referred to in the motion search, and reference numeral 1104 represents 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 shape change of the imaged object in the z-axis direction falls within this search range, it is possible to more appropriately determine the search range. In the example of the CT apparatus, the search angle θ may be obtained based on the amount of change expected in the desired tissue in the z-axis direction (generally the body axis direction).

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.

Then, in step S1006, the search range determination unit 302 calculates the horizontal search range Rx and the vertical search range Ry in motion compensation. These values are determined based on the pixel intervals Px and Py, the slice interval Pz, and the search angle θ in the three-dimensional space. Specifically, it is calculated by adding tan θ (tangent) as in the following expression (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 effects of the first embodiment, it is possible to reflect the search angle according to the desired shape of the imaged object in the determination of the search range.

[Third Embodiment]
In the first embodiment, a method has been described in which the motion compensation coding unit 303 performs a motion search based on the search range determined by the search range determination unit 302. In some cases, it may be desired to reduce the time required for encoding as compared with the first embodiment. In this case, it suffices to omit the motion search in the slice image data set that has a small improvement effect on the compression performance or has a small search range. In the third embodiment, a technique for enabling the motion search process to be bypassed depending on the value of the search range for speeding up will be described. The device 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 of FIG. 8 of the first embodiment.

In step S1205, the motion compensation encoding unit 303 determines whether the search ranges Rx and Ry are equal to or less than the threshold value T, respectively. This threshold value T may be set according to the computing capacity of the processing system and the required throughput, and for example, T=1. When both search ranges Rx and Ry are equal to or less than the threshold value, the motion compensation coding unit 303 advances the process to step S1209. On the other hand, if either of the search ranges Rx and Ry exceeds the threshold value T, the process proceeds to step S1206. It should be noted that, from step S1205, the process of steps S1206 to S1208 is skipped, and the motion vector when the process proceeds to step S1209 is regarded as (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, the motion search can be omitted for the slice image data set having a small search range, and the processing speed can be increased.

In addition to the above method, the search range determining unit may be designed so that the search range may be 0 and the motion search may not be performed in practice. Since the expression (2) of the first embodiment is rounded up to obtain the value, it takes a value of 1 or more. This is because it is possible to cover the motion search range below the decimal point by rounding up, but by rounding up this rounding up as in the following equation (4), search range = 0 is generated. Can be made.

[Modification]
The present invention is not limited to the above embodiments. For example, the above embodiment has been described on the premise that the motion search accuracy is 1 pixel, but the motion search accuracy may be designed to correspond to 1/2 accuracy and 1/4 accuracy. In this case, for example, the equation (2) used for determining the search range is set to N (N=1, 2, 4,...) As the value indicating the pixel accuracy value, and the following equation may be modified. ..

Further, in the above-described embodiment, the search range is obtained for each of x and y, but in general, the pixel interval is often designed to be x=y, and in that case, only one of the values is used. The search range may be determined.

Further, 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, but this is applied only to the representative image, and other The slice image may be changed dynamically. In that case, the distribution of the actually used search range may be fed back to determine the search range of the next slice image.

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

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

Further, in the above-described embodiment, the processing is described as the processing of the control device 102 in the CT device 100, but the control device 102 is the same in hardware as an information processing device such as a general personal computer (PC). Therefore, the 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 embodiments)
The present invention supplies a program that implements 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. It can also be realized by the processing. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

101... CT imaging device, 102... Control device, 103... Imaging condition instruction unit, 104... Image reconstruction unit, 105... Image coding unit, slice image data set input unit, 302... Search range determination unit, 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,
An acquisition unit that acquires 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 determining unit that determines a motion search range when performing motion compensation encoding of the encoding unit based on the information obtained by the obtaining unit. The determining means is
Inversely proportional to the distance in physical space to the pixel spacing in slice image data,
A value proportional to the distance in the physical space between slice image data along the body axis of the subject is determined as the search range,
The image coding apparatus according to claim 1, wherein
The determining means further determines, as the 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 is
Further comprising a determination means for determining whether the search range is less than or equal to a preset threshold,
4. When the determination means determines that the search range is equal to or less than the threshold value, the motion vector search process is omitted and the slice image data is encoded. The image encoding device according to any one of items. A method of controlling an image encoding device for encoding a slice image data set composed of a plurality of slice image data of a subject,
An acquisition step in which the acquisition means acquires information about the interval in the physical space with respect to the interval between the pixel intervals in the slice image data and the interval between the slice image data;
Coding means, each slice image data in the slice image data set, a coding step of performing motion compensation coding,
And a determining step of determining a motion search range when performing motion compensation encoding in the encoding step, based on the information obtained in the obtaining step. A program for causing the computer to function as each unit of the apparatus according to claim 1, when the computer reads and executes the program.

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