JP5472897B2 - Image processing device - Google Patents

Description

  The present invention relates to an image processing apparatus that performs image processing on a plurality of volume data sets related to a plurality of scan times.

  In recent X-ray computed tomography apparatuses, multi-row and high speed have been advanced. Thus, the X-ray computed tomography apparatus can collect a plurality of volume data sets (so-called dynamic scan) by repeatedly scanning a wide range of the same position at a plurality of scan times. Using these multiple volume data sets, temporal changes in pixel values in the blood vessel due to the contrast agent can be displayed as a moving image. However, when observing a blood vessel region with a moving image display, the bone region interferes with the observation. Therefore, it is necessary to remove the bone region for each of a plurality of volume data sets, but the time required to remove the bone region for all the volume data becomes enormous.

  Also, in the case of moving image display, the information drawn in the previous display image disappears every time the display image is switched. Therefore, the only way to grasp the shape of the entire blood vessel is to rely on the user's memory.

  An object of the present invention is to provide an image processing apparatus that realizes reduction in labor and improvement in efficiency in blood vessel image diagnosis.

An image processing apparatus according to a first aspect of the present invention includes a storage unit that stores a plurality of volume data sets related to a plurality of scan times, and a single projection volume data set by performing time projection processing on the plurality of volume data sets. A first generating unit for generating a voxel region in the projection volume data set indicating a specific pixel value change along the plurality of scan times, and a three-dimensional image in the projection volume data set An image processing apparatus comprising: a second generation unit that performs processing to generate single first image data indicating the specified voxel region; and a display unit that displays the first image. The second generation unit performs three-dimensional image processing on the plurality of volume data sets to generate data of a plurality of second images indicating the voxel regions, respectively. No, the display unit displays the plurality of second image to the first image superimposed respectively to the scan order of time, and wherein the.

  According to the present invention, it is possible to provide an image processing apparatus that realizes reduction in labor and improvement in efficiency in blood vessel image diagnosis.

  Hereinafter, an image processing apparatus according to an embodiment of the present invention will be described with reference to the drawings. The image processing apparatuses according to the first embodiment and the second embodiment are intended to reduce labor and improve efficiency in diagnosis of a plurality of blood vessel regions along a plurality of scan times.

(First embodiment)
FIG. 1 is a diagram showing an outline of processing by the image processing apparatus according to the first embodiment of the present invention. The image processing apparatus according to the first embodiment includes a plurality of volume data sets VDs (not shown) to VDa to VDb to a plurality of scan times ts to te generated by an X-ray computed tomography apparatus or a magnetic resonance imaging apparatus. Data of VDc to VDe (not shown) are stored. The scan times ta, tb, and tc are times between the scan start time ts and the scan end time te, and there is a relationship of ts <ta <tb <tc <te between these scan times. The plurality of volume data sets VDs to VDe are generated by repeatedly scanning the same imaging region (for example, the head) of the subject (so-called dynamic scan). During the scan, a contrast medium is injected into the subject. The injected contrast agent is gradually imaged from the cerebral blood vessels near the injection part of the contrast agent. Eventually, the contrast agent spreads to every corner of the cerebral blood vessel while reducing its concentration, and is discharged from the head. Therefore, the volume data sets VDs to VDe include not only bone regions HRs (not shown) to HRa to HRb to HRc to HRe (not shown) and brain regions (not shown), but also blood vessel regions KRs derived from contrast agents. (Not shown) to KRa to KRb to KRc to KRe (not shown). The position of the blood vessel region and the pixel value change every moment as the scan time elapses.

  Image processing is performed on the plurality of volume data sets VDs to VDe to generate a single volume data set VDp. Image processing for generating a single volume data set VDp includes temporal pixel value projection processing (hereinafter referred to as time projection processing) along a plurality of scan times. Hereinafter, the volume data set generated by the time projection process will be referred to as a projected volume data set. The pixel value of each voxel of the projection volume data set VDp has a maximum value, a minimum value, an average value, or a median value among the pixel values taken by the voxel between the scan times ts to te. Note that the projection volume data set VDp in FIG. 1 takes the maximum value. The plurality of projection volume data sets VDp includes a bone region HRp and a blood vessel region KRp.

  In the display image generated by performing the three-dimensional image processing of the projection volume data set VDp as it is to diagnose the blood vessel region KRp, the blood vessel region KRp is hidden in the shadow of the bone region HRp. It ’s hard. Therefore, the image processing apparatus according to the first embodiment performs a three-dimensional image processing target region (in FIG. 1) from the projection volume data set VDp based on the temporal change of the pixel value at each voxel position of the projection volume data set VDp. The blood vessel region KRp) is determined. Then, the projection volume data set Ip is limited to the blood vessel region KRp (target region) and three-dimensional image processing is performed to generate display image Ip data related to the blood vessel region KRp. Since the bone region is not depicted in the generated display image Ip, it is easy to observe the blood vessel region. Note that the target region need not be limited to the blood vessel region. For example, any region such as a bone region, a brain region, and an organ region can be determined as a target region.

  Next, the configuration of the image processing apparatus according to the first embodiment will be described. FIG. 2 is a diagram illustrating a configuration of the image processing apparatus 1 according to the first embodiment. As shown in FIG. 1, the image processing apparatus 1 has a control unit 10 as a center, a storage unit 12, an operation unit 14, a projection volume data set generation unit 16, a time density curve creation unit 18, a region determination unit 20, a display image. A generation unit 22 and a display unit 24 are provided.

  The storage unit 12 stores a plurality of volume data sets related to a plurality of scan times. A plurality of volume data sets are stored in association with a plurality of scan times. As described above, the plurality of volume data sets are generated by dynamic scanning by an X-ray computed tomography apparatus or a magnetic resonance imaging apparatus. Hereinafter, for the sake of specific explanation, it is assumed that the volume data set is generated by an X-ray computed tomography apparatus. It is assumed that the plurality of stored volume data sets are aligned with each other. In addition, the storage unit 12 stores a dedicated program for time projection processing in which processing targets are limited.

  The operation unit 14 receives various commands and information input from the user. As the operation unit 14, a pointing device such as a mouse or a trackball, a selection device such as a mode switch, or an input device such as a keyboard can be used as appropriate.

  The projection volume data set generation unit 16 generates a projection volume data set by performing image processing, that is, time projection processing on a plurality of volume data sets. The pixel value of the voxel of the projection volume data set has a representative value among the pixel values of the plurality of voxels at the same coordinates of the plurality of volume data sets. The type of representative value corresponds to the type of time projection processing. Examples of the time projection process include a maximum value projection process, a minimum value projection process, an average value projection process, and a median value projection process. That is, the representative value in the temporal maximum value projection process is the maximum value, the representative value in the temporal minimum value projection process is the minimum value, the representative value in the temporal average value projection process is the average value, The representative value in the temporal median projection process is the median. The type of the time projection process can be arbitrarily set by the user via the operation unit 14. The generated projection volume data set is stored in the storage unit 12. Details of the time projection processing will be described later.

  The time concentration curve creating unit 18 creates a time concentration curve for each voxel from a plurality of volume data sets. The time density curve is a curve in which a change in the pixel value at a certain coordinate is represented with time on the horizontal axis. The created time density curve data is stored in the storage unit 12 in association with the coordinates.

  The region determination unit 20 determines a target region for 3D image processing of the projection volume data set. More specifically, the region determination unit 20 refers to the time density curve to identify and identify the first voxel region in the projection volume data set that shows a specific pixel value change along a plurality of scan times. The voxel area is determined as the target area. Alternatively, the region determination unit 20 may determine a second voxel region other than the first voxel region in the projection volume data set as a target region. The target region is a region other than a bone region such as a blood vessel region or an organ region in the volume data set. Details of the target area determination processing will be described later.

  The display image generation unit 22 performs three-dimensional image processing on the projection volume data set and generates display image data related to the processing target area. As the three-dimensional image processing, volume rendering by the parallel projection method or perspective projection method, spatial pixel value projection processing, MPR (multi planar reconstruction) processing, CPR (curved planar reconstruction) processing, and SPR (streched CPR) processing are appropriate. It is.

  The display unit 24 displays a display image. As the display unit 24, for example, a display device such as a CRT display, a liquid crystal display, an organic EL display, or a plasma display can be used as appropriate.

  The control unit 10 reads out a dedicated program stored in the storage unit 12, develops it on its own memory, and controls each unit of the image processing apparatus 1, thereby executing a time projection process that limits a processing target.

  Next, details of the time projection process that limits the processing target performed under the control of the control unit 10 will be described. FIG. 3 is a diagram showing a typical flow of the time projection process in which the processing target is limited. It is assumed that the time projection process in FIG. 3 is a temporal maximum value projection process that is clinically useful. However, the time projection process according to the first embodiment is not limited to this, and the minimum value projection process, the average value projection process, and the median value projection process can be performed in the same manner as the maximum value projection process.

  The control unit 10 waits for an instruction to start processing via the operation unit 14. When the user gives an instruction to start processing via the operation unit 14, the control unit 10 arranges a plurality of volume data sets VDs to VDe stored in the storage unit 12 in order of scan time (step SA1). . Each volume data set is assumed to consist of L × M × N voxels. There may be any number of L, M, and N.

  When the arrangement is completed in the order of the scan times, the control unit 10 writes the volume data set VDs related to the scan time ts in a memory area for time projection processing (hereinafter referred to as a time projection area) (step SA2). This time projection area is assumed to be a memory area of the storage unit 12, for example. By writing, the same data as the volume data set VDs is copied to the time projection area.

  When writing is performed, the control unit 10 determines whether or not Step SA4 to Step SA6 have been performed on all volume data VDi (s <i ≦ e) (Step SA3).

  If it is determined in step SA3 that all volume data sets VDi are not subjected to steps SA4 to SA6 (step SA3: NO), the control unit 10 reads the volume data set VDi from the storage unit 12 (step SA4). Typically, volume data sets VDi are read one by one in order of scan time. The read volume data set VDi is supplied by the control unit 10 to the projection volume data set generation unit 16 and the time density curve creation unit 18. Steps SA4 to SA6 are repeated for each volume data set.

  When the reading is performed, the control unit 10 causes the projection volume data set generation unit 16 to perform a replacement process (step SA5). In the replacement process, the projection volume data set generation unit 16 detects the voxel pixel at the same coordinate j (for example, j = (x, y, z) = (0, 0, 0)) between the time projection area and the volume data set VDi. The magnitudes of the values are compared, and the larger pixel value is replaced with the pixel value of the voxel at coordinate j in the time projection area. Step SA5 and the next step SA6 are performed for each coordinate.

  When the replacement is performed, the control unit 10 causes the time density curve creating unit 18 to perform plot processing (step SA6). In the plot processing, the time density curve creating unit 18 creates a time density curve creating memory area (hereinafter referred to as a TDC memory) from the pixel value of the voxel at the coordinate j of the volume data set VDi in order to create the time density curve of the coordinate j. Plot it on The TDC memory is a memory area of the storage unit 12, for example.

  When the plotting is performed, the control unit 10 has performed steps SA5 and SA6 for all coordinates j (all coordinates of (0, 0, 0) to (L, M, N)) of the time projection area. Is determined (step SA7).

  If it is determined in step SA7 that steps SA5 and SA6 have not been performed for all coordinates j (step SA7: NO), the control unit 10 sets the coordinates j to be processed in steps SA5 and SA6 as the next coordinates. After changing (step SA8), the projection volume data set generation unit 16 and the time density curve creation unit 18 again perform steps SA5 and SA6, respectively.

  If it is determined in step SA7 that steps SA5 and SA6 have been performed for all coordinates j, the control unit 10 proceeds to step SA3 and repeats steps SA4 to SA7 with different volume data sets VDi. By repeatedly performing steps SA4 to SA7 for all volume data sets VDs to VDe, a projection volume data set is generated by the projection volume data set generation unit 16, and the time density curve generation unit 18 sets the time density for all coordinates j. A curve is created. The projection volume data set and the data of the time density curve are supplied to the region determination unit 20 by the control unit 10.

  If it is determined in step SA3 that steps SA4 to SA7 have been performed for all volume data sets VDs to VDe (step SA3: YES), the control unit 10 proceeds to step SA9. In step SA9, the control unit 10 causes the region determination unit 20 to perform region determination processing (step SA9). In the region determination process, the region determination unit 20 determines a target region for three-dimensional image processing in the projection volume data set based on the created time density curve. Data on the coordinates of the target area is stored in the storage unit 12.

  Hereinafter, the determination process of the target area by the area determination unit 20 will be described in detail. The target region determination processing is roughly classified into a method (method 1) for determining a region other than a bone region as a target region and a method (method 2) for determining a blood vessel region as a target region. Hereinafter, method 1 and method 2 will be described. Note that whether the method 1 or the method 2 is used as the target region determination process can be selected by the user via the operation unit 14. Both methods are performed for each voxel.

  (Method 1) First, each voxel constituting the projection volume data set is divided into a bone region and another region. FIG. 4 is a diagram showing a typical example of a time concentration curve derived from bone. Since the bone is not contrasted by the contrast agent, the temporal density curve derived from the bone has little change in the pixel value as the scan time elapses. That is, the pixel value derived from the bone changes within a very narrow pixel value width (for example, within 10 HU). Further, the pixel value derived from bone is higher than the pixel value of a tissue such as a blood vessel or a brain, and takes approximately 150 HU or more.

  Using the characteristic peculiar to such a bone-derived time concentration curve, the region determination unit 20 determines whether or not the processing voxel is a bone region by analyzing the time concentration curve of the processing target voxel. To do. That is, the time density curve of the processing voxel is located within the set pixel value width D1 (that is, the difference between the minimum pixel value and the maximum pixel value, for example, 10 HU), and the minimum pixel value of the time density curve is the set value V1. If it is above (for example, 150HU), it will determine with a process voxel being a bone area | region. When it is determined that the region is a bone region, the processing voxel is determined as a non-target region, and a code to that effect is assigned. On the other hand, if it is determined that the region is not a bone region, the processing voxel is determined as a target region, and a code to that effect is assigned. Note that the pixel value width D1 and the set value V1 can be arbitrarily set by the user via the operation unit 14.

  The brain region can also be determined as a non-target region by the same method as that for the bone region. FIG. 5 is a diagram showing a typical example of a brain-derived time concentration curve. As shown in FIG. 5, the brain is hardly imaged by the contrast agent. Therefore, the brain-derived time density curve, like the bone-derived time density curve, has little change in the pixel value as the scan time elapses. That is, the pixel value of the time density curve derived from the brain changes within a very narrow pixel value width. The pixel value derived from the brain is lower than the pixel value derived from a tissue such as a blood vessel or a bone. That is, if the time density curve of the processing voxel is located within the set pixel value width D2 (for example, 10HU) and the minimum pixel value of the time density curve is equal to or greater than the set value V2 (for example, 0HU), the processing voxel Is determined to be a brain region. The pixel value width D2 and the set value V2 can be arbitrarily set by the user via the operation unit 14.

(Method 2) First, each voxel constituting the projection volume data set is divided into a blood vessel region and another region. FIG. 6 is a diagram showing a typical example of a time concentration curve derived from a blood vessel. Since the blood vessel is imaged by the contrast agent, the time-density curve derived from the blood vessel changes according to a peculiar pattern of pixel values as the scan time elapses. Due to this unique pattern, the time concentration curve derived from blood vessels has a certain shape, that is, a convex shape upward. In other words, the pixel value increases and then decreases from the scan start time to the scan end time. More specifically, when the contrast agent flows in, the pixel value rapidly increases from the minimum value V3 (the pixel value of the blood vessel region that is not contrasted) to the maximum value V4. When the maximum value V4 is reached, the pixel value gradually falls and then returns to the original minimum value V3. The difference D3 between the minimum value V3 and the maximum value V4 varies depending on the position of the voxel and the type of the contrast agent, but is generally about 100 HU or more.
The region determination unit 20 determines whether or not the processing voxel is a blood vessel region by analyzing the time concentration curve of the processing voxel using such a characteristic peculiar to the blood vessel-derived time concentration curve. That is, by tracing the time density curve of the processing voxel from the start point, it is determined whether or not the pixel value increases and decreases from the scan start time to the scan end time. When it rises and descends, it is determined that the processing voxel is a blood vessel region, and a code to that effect is assigned. If it is not raised and not lowered, it is determined that the processing voxel is not a blood vessel region, and a code to that effect is assigned. Another method may be used as the method for determining the blood vessel region. For example, the difference between the minimum value and the maximum value of the pixel values in the time density curve is calculated, and it is determined whether or not the calculated difference value is a set value (for example, 100 HU) or more. If the value is equal to or greater than the set value, the processing voxel is determined to be a blood vessel region and determined as a target region. On the other hand, if it is equal to or less than the set value, the processing voxel is determined not to be a blood vessel region, and is determined as a non-target region. The setting value is set to 100 HU by default, but can be arbitrarily set by the user via the operation unit 14.

  In the time density curve derived from the boundary between the bone and the brain and between the blood vessel and the brain, as shown in FIG. . When such a time density curve is seen, it is possible to consider the time density curve of the surrounding voxels rather than determining whether or not to set the target region using only the time density curve of the processing voxel. .

  An average value of a plurality of pixel values constituting the time density curve may be calculated, and if the calculated average value is equal to or greater than a set value, the processing voxel may be determined as a target region or a non-target region.

  When the target area is determined, the control unit 10 causes the display image generation unit 22 to perform three-dimensional image processing (step SA10). In the three-dimensional image processing, the display image generation unit 22 generates display image data related to the target area based on the projection volume data set. More specifically, the projection volume data set is subjected to three-dimensional image processing limited to the target region to generate display image data.

  Ray tracing in 3D image processing assumes a ray that extends from a light spot through a volume data set to a pixel on the screen. In ray tracing, the pixel value of a pixel is calculated using the pixel value of the voxel on the target area determined in step SA9 among the plurality of voxels through which the ray penetrates. When calculating the pixel value of the pixel, the pixel value of the voxel in the non-target region determined in step SA9 is not used. Whether the voxel belongs to the target area or the non-target area is confirmed by referring to the code assigned to the voxel in step SA9.

  The display image generated in step SA10 is an image based on the temporal maximum value projection process. Therefore, the display image depicts the blood vessel into which the contrast medium has flowed in from one scan start time ts to the scan end time te in one image. That is, in the display image, not only the cerebral blood vessels that reach the contrast medium relatively early, but also the delayed blood vessels that reach the contrast medium later. Therefore, the user can grasp the entire shape of the cerebral blood vessel with a single image (display image).

  In general, the pixel value range derived from bone deviates from the pixel value ranges derived from other tissues. Further, the above-described bone region detection process is simpler than the blood vessel region detection process. Due to these factors, the detectability of the bone region is higher than the detectability of the blood vessel region and the brain region. Therefore, if the method 1 (method for determining a region other than a bone region as a target region) is used, only a bone region that hinders blood vessel diagnosis can be removed with high accuracy. Accordingly, by observing the display image based on the method 1, the user can observe the blood vessel region while referring to the positional relationship between the blood vessel region and the brain region. On the other hand, if Method 2 (method for determining a blood vessel region as a target region) is used, regions other than the blood vessel region most necessary for blood vessel diagnosis can be removed. Therefore, the user can observe only the blood vessel region in detail by observing the display image based on the method 2.

  When the display image data is generated, the control unit 10 causes the display unit 24 to perform display processing (step SA11). In the display process, the display unit 24 displays the generated display image.

  When the display image is displayed, the control unit 10 ends the time projection process that limits the processing target.

  Thus, the image processing apparatus 1 according to the first embodiment realizes reduction in labor and improvement in efficiency in blood vessel image diagnosis.

  In the above configuration, a projection volume data set is generated to generate display image data. However, the projection volume data set is only an intermediate product for generating display image data. Therefore, if the display image data can be generated without generating the projection volume data set, it is not always necessary to generate the projection volume data set. For example, a projection volume data set may be virtually generated in ray tracing in three-dimensional image processing.

(Modification)
The image processing apparatus 1 according to the modification synthesizes and displays the display images Ii generated from the individual volume data sets VDi in the order of the scan time with respect to the display images generated in step SA10, thereby displaying the blood flow. Can be displayed as a video. Hereinafter, an image processing apparatus 1 according to a modification will be described. In the following description, components having substantially the same functions as those of the present embodiment are denoted by the same reference numerals, and redundant description will be given only when necessary.

  The display image generation unit 22 generates data of a display image (hereinafter, referred to as a whole blood vessel image) in which only the blood vessel region is depicted in step SA10 in FIG. The whole blood vessel image is an image depicting the entire brain blood vessel.

  Further, the display image generation unit 22 performs three-dimensional image processing on each of the plurality of volume data sets VDs to VDe, and obtains data of a plurality of display images (hereinafter referred to as partial blood vessel images) Is to Ie related to the same cross section. Occur. At this time, the display image generation unit 22 reads the coordinate data of the target area stored in the storage unit 12 and performs three-dimensional coordinate processing on each of the plurality of volume data sets VDs to VDe limited to the read coordinates. A plurality of partial blood vessel images. The three-dimensional image processing is typically a spatial maximum value projection processing. The cross sections of the plurality of partial blood vessel images Is to Ie are the same as the cross section of the whole blood vessel image generated in step SA10. Each data of the plurality of partial blood vessel images Is to Ie is stored in the storage unit 12 in association with the scan time.

  The display unit 24 reads the whole blood vessel image and the plurality of partial blood vessel images from the storage unit 12, and synthesizes and displays the partial blood vessel images on the whole blood vessel image in order of scan time. Thereby, the flow of blood flow is displayed as a moving image. FIG. 8 is a diagram for explaining the moving image display of blood flow by the display unit 24. As shown in FIG. 8, the partial blood vessel regions BRa, b, and c of the partial blood vessel image are superimposed on the whole blood vessel region ZR on the whole blood vessel image in the order of scan times. The whole blood vessel region ZR and the partial blood vessel regions BRa, b, and c are displayed with different colors, brightness, brightness, and the like.

  Thus, according to the image processing apparatus 1 according to the modification, it is possible to reduce labor and improve efficiency in blood vessel image diagnosis.

(Second Embodiment)
The image processing apparatus according to the second embodiment will be described below. In the following description, components having substantially the same functions as those in the twenty-first embodiment are denoted by the same reference numerals, and redundant description is provided only when necessary.

  FIG. 9 is a diagram showing an outline of the second embodiment of the present invention. As shown in FIG. 9, the image processing apparatus according to the second embodiment performs three-dimensional image processing on each of a plurality of volume data sets VDs (not shown) to VDa to VDb to VDc to VDe (not shown). Data of a plurality of three-dimensional images Is (not shown) to Ia to Ib to Ic to Ie (not shown) is generated. Each of the three-dimensional images Is-Ia-Ib-Ic-Ie includes bone regions HSs (not shown) -HSa-HSb-HSc-HSe (not shown) and blood vessel regions KSs (not shown) -KSa-KSb- KSc to KSe (not shown) are included.

  In a display image generated by performing time projection processing of a plurality of three-dimensional image data as they are in order to perform image diagnosis of the blood vessel region, it is difficult to observe the blood vessel region because the blood vessel region is hidden behind the bone region. Therefore, the image processing apparatus according to the second embodiment is based on the temporal change of the pixel values of a plurality of pixels at the same coordinates of a plurality of three-dimensional images (for example, blood vessel regions KSa, b, c) is determined. Then, the data of a plurality of three-dimensional images Is to Ie is time-projected only in the blood vessel region KSa, b, c (target region), and data of a single display image Ip related to the blood vessel region KSp is generated. Since the bone region is not depicted in the generated display image Ip, it is easy to observe the blood vessel region. Note that the processing target region need not be limited to the blood vessel region. For example, any region such as a bone region, a brain region, and an organ region can be determined as a target region.

  Next, the configuration of the image processing apparatus according to the second embodiment will be described. FIG. 10 is a diagram illustrating a configuration of the image processing apparatus 2 according to the second embodiment. As shown in FIG. 10, the image processing apparatus 2 has the control unit 30 as a center, the storage unit 12, the operation unit 14, the three-dimensional image generation unit 32, the time density curve generation unit 18, the region determination unit 20, and the display image generation. The unit 34 and the display unit 24 are provided.

  The three-dimensional image generation unit 32 performs three-dimensional image processing on each of the plurality of volume data sets to generate a plurality of three-dimensional image data related to the same cross section. The position and orientation of the cross section can be arbitrarily set by the user via the operation unit 14. The generated data of the plurality of three-dimensional images are stored in the storage unit 12 in association with the plurality of scan times. As the three-dimensional image processing, volume rendering by the parallel projection method or perspective projection method, spatial pixel value projection, MPR processing, CPR processing, and SPR processing are appropriate.

  The time density curve creation unit 18 creates a time density curve for each coordinate from a plurality of three-dimensional images. The created time density curve data is stored in the storage unit 12 in association with the coordinates.

  The region determination unit 20 determines a target region for time projection processing described later from the same cross section of a plurality of three-dimensional images. More specifically, the region determination unit 20 refers to the time density curve, identifies the first pixel region on the cross section showing a specific pixel value change along a plurality of scan times, and identifies the identified first The pixel area is determined as the target area. Alternatively, the region determination unit 20 may determine a second pixel region other than the first pixel region on the same cross section as the target region.

  The display image generation unit 34 performs image processing, that is, time projection processing, on a plurality of three-dimensional image data, and generates single display image data regarding the target region. The pixel value of the pixel of the display image has a representative value among the pixel values of the plurality of pixels at the same coordinates of the plurality of three-dimensional images. The type of representative value corresponds to the type of time projection processing. Examples of the time projection process include a maximum value projection process, a minimum value projection process, an average value projection process, and a median value projection process. That is, the representative value in the temporal maximum value projection process is the maximum value, the representative value in the temporal minimum value projection process is the minimum value, the representative value in the temporal average value projection process is the average value, The representative value in the temporal median projection process is the median. The type of the time projection process can be arbitrarily set by the user via the operation unit 14. The generated display image data is stored in the storage unit 12.

  Specifically, the display image generation unit 34 includes a time projection processing unit 342 and an extraction processing unit 344. The time projection processing unit 342 performs time projection processing on data of a plurality of three-dimensional images to generate data of a single three-dimensional image (hereinafter referred to as a projected three-dimensional image). The cross section of the generated projected 3D image is the same as the cross section of the plurality of 3D images. The extraction processing unit 344 extracts a target area included in the projected three-dimensional image, and generates display image data related to the target area.

  The control unit 30 reads out a dedicated program stored in the storage unit 12, develops it on the memory of the control unit 30, and controls each unit of the image processing device 2, thereby executing a time projection process that limits a processing target. To do.

  Next, details of the time projection process that limits the processing target performed under the control of the control unit 30 will be described. FIG. 11 is a diagram illustrating a typical flow of the time projection processing in which the processing target is limited. It is assumed that the time projection process in FIG. 11 is a temporal maximum value projection process that is clinically useful. However, the time projection process in the second embodiment is not limited to this, and the minimum value projection process, the average value projection process, and the median value projection process can be performed in the same manner as the maximum value projection process.

  The control unit 30 waits for an instruction to start processing via the operation unit 14. When the user gives an instruction to start processing via the operation unit 14, the control unit 30 arranges the plurality of volume data sets VDs to VDe stored in the storage unit 12 in order of scan time (step SB1). .

  When the arrangement is completed in the order of the scan times, the control unit 30 causes the three-dimensional image generation unit 32 to perform a three-dimensional image generation process (step SB2). In the three-dimensional image generation processing, the three-dimensional image generation unit 32 performs three-dimensional image processing on each of the plurality of volume data sets VDs to VDe to generate data of the plurality of three-dimensional images Is to Ie. Assume that each three-dimensional image is composed of L × M pixels. The number of L and M may be any number.

  When the three-dimensional image data is generated, the control unit 30 writes the three-dimensional image Is data in the time projection area (step SB3). By writing, the same data as the data of the three-dimensional image Is is copied to the time projection area.

  When writing is performed, the control unit 30 determines whether or not Steps SB5 to SB7 have been performed on all the three-dimensional images VDi (s <i ≦ e) (Step SB4).

  If it is determined in step SB4 that all the three-dimensional images Ii are not subjected to steps SB5 to SB7 (step SB4: NO), the control unit 30 reads the three-dimensional image VDi from the storage unit 12 (step SB4). Typically, the three-dimensional images Ii are read one by one in order of scan time. The read three-dimensional image Ii is supplied by the control unit 30 to the time projection processing unit 342 of the projection display image generation unit 34. Steps SB5 to SB7 are repeated for each three-dimensional image.

  When the reading is performed, the control unit 30 causes the time projection processing unit 342 to perform a replacement process (step SB6). In the replacement process, the time projection processing unit 342 compares the pixel values of the pixels at the same coordinate j in the time projection area and the three-dimensional image Ii, and compares the larger pixel value with the pixel at the coordinate j in the time projection area. Replace with the pixel value of. Step SB6 and the next step SB7 are performed for each coordinate.

  When the replacement is performed, the control unit 30 causes the time density curve creating unit 18 to perform plot processing (step SB7). In the plot processing, the time density curve creating unit 18 plots the pixel value of the pixel at the coordinate j of the three-dimensional image Ii in the TDC memory in order to create the time density curve at the coordinate j.

  When the plotting is performed, the control unit 30 determines whether or not Steps SB6 and SB7 have been performed for all coordinates j (all coordinates of (0, 0) to (L, M)) of the time projection area. (Step SB8).

  If it is determined in step SB8 that steps SB6 and SB7 have not been performed for all coordinates j (step SB8: NO), the control unit 30 sets the coordinates j to be processed in steps SB6 and SB7 as the next coordinates. (Step SB9), the time projection processing unit 342 and the time density curve creation unit 18 are again made to perform steps SB6 and SB7, respectively.

  If it is determined in step SB8 that steps SB6 and SB7 have been performed for all coordinates j, control unit 30 proceeds to step SB4 and repeats steps SB5 to SB8 with different three-dimensional images Ii. By repeating step SB5 to step SB8 for all three-dimensional images, the time projection processing unit 342 generates projection three-dimensional image data, and the time density curve creating unit 18 generates time density curves for all coordinates j. Created.

  If it is determined in step SB4 that steps SB5 to SB8 have been performed for all three-dimensional images (step SB4: YES), control unit 30 proceeds to step SB10. In step SB10, the control unit 30 causes the region determination unit 20 to perform region determination processing (step SB10). In the region determination process, the region determination unit 20 determines a target region for time projection processing in the projection three-dimensional image according to the above-described method 1 or method 2 based on the created time density curve. The determined coordinate data of the target area is stored in the storage unit 12.

  When the target region is determined, the control unit 30 causes the extraction processing unit 344 to perform extraction processing (step SB11). In the extraction processing, the extraction processing unit 344 generates display image data related to the extracted target region by extracting the target region from the projection three-dimensional image.

  When the display image data is generated, the control unit 30 causes the display unit 24 to perform display processing (step SB12). In the display process, the display unit 24 displays the generated display image.

  When the display image is displayed, the control unit 30 ends the time projection process that limits the target area.

  As described above, the image processing apparatus 2 according to the second embodiment can generate display image data by executing time projection processing with a limited target area on a plurality of three-dimensional image data.

  Thus, the image processing apparatus 2 according to the second embodiment realizes reduction in labor and improvement in efficiency in blood vessel image diagnosis.

  Note that the present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. In addition, various inventions can be formed by appropriately combining a plurality of components disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, constituent elements over different embodiments may be appropriately combined.

The figure which shows the outline | summary of the time projection process limited to the object area | region based on 1st Embodiment of this invention. 1 is a diagram illustrating a configuration of an image processing apparatus according to a first embodiment. The figure which shows the typical flow of the time projection process limited to the object area | region performed under control of the control part of FIG. The figure which shows the typical example of the time concentration curve derived from a bone for demonstrating step SA9 of FIG. The figure which shows the typical example of the time concentration curve derived from the brain for demonstrating step SA9 of FIG. The figure which shows the typical example of the time concentration curve derived from the blood vessel for demonstrating step SA9 of FIG. The figure which shows the typical example of the time concentration curve derived from a border for demonstrating step SA9 of FIG. The figure for demonstrating the moving image display process of the blood flow by the display part of FIG. The figure which shows the outline | summary of the time projection process limited to the object area | region based on 2nd Embodiment of this invention. The figure which shows the structure of the image processing apparatus which concerns on 2nd Embodiment. The figure which shows the typical flow of the time projection process limited to the object area | region performed under control of the control part of FIG.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Image processing apparatus, 10 ... Control part, 12 ... Memory | storage part, 14 ... Operation part, 16 ... Projection volume data set generation part, 18 ... Time density curve preparation part, 20 ... Area determination part, 22 ... Display image generation part , 24 ... display section

Claims (1)

A storage unit for storing a plurality of volume data sets related to a plurality of scan times;
A first generator for performing a time projection process on the plurality of volume data sets to generate a single projection volume data set;
A specifying unit for specifying a voxel region in the projection volume data set indicating a specific pixel value change along the plurality of scan times;
A second generator for performing three-dimensional image processing on the projection volume data set to generate data of a single first image indicating the specified voxel region;
A display unit for displaying the first image;
An image processing apparatus comprising:
The second generation unit performs three-dimensional image processing on the plurality of volume data sets to generate a plurality of second image data indicating the voxel regions, respectively.
The display unit displays the plurality of second images on the first image so as to overlap each other in order of the scan time.
An image processing apparatus.

Images