JP2010213760A - Image processing device, and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To assure proper image diagnosis using a map image. <P>SOLUTION: As map image generating section 38a generates a map image, a least square sum image generating section 38b generates a least square sum image based on a least square sum as total sum of output error. A clustering image generating section 38c generates a clustering image by clustering a range over a predetermined pixel value by means of the least square sum image. A warning range extracting section 38d extracts a warning range based on cluster area. A system control section 39 controls to display a superposed image of the warning range with the map image generated by a superposed image generating section 38e. In a case where the warning range is designated, the system control section 39 displays TDC of the warning range formed by a TDC forming section 38f, and in a case where an operator referring to the TDC designates the warning range as a non-analysis range, the system control section 39 sets a map image corresponding to the non-analysis range not to be displayed. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an image processing apparatus and an image processing program.

  Conventionally, a perfusion image is generated by an X-ray CT apparatus, an MRI apparatus, or the like, and blood flow in capillaries of a predetermined tissue (for example, brain tissue of the head, liver tissue of the abdomen, pancreatic tissue, etc.). Analysis of dynamics is being conducted.

  For example, an X-ray CT apparatus having a function of generating a perfusion image shows a change in CT value over time from an X-ray CT image obtained by photographing a head of a subject administered with a nonionic iodine contrast agent in time series. calculate. Then, the X-ray CT apparatus calculates CBP, CBV, and MTT, which are indexes (indexes) that quantitatively represent blood flow dynamics passing through capillaries in the brain tissue from the change in the calculated CT value over time. A map image mapped to is generated as a perfusion image.

  CBP is the blood flow per unit volume and unit time in the capillary, CBV is the blood flow per unit volume in the capillary, and MTT is the blood average of the capillary. It is the transit time. A doctor refers to a map image in which CBP, CBV, and MTT are mapped to diagnose a cerebral infarction and determine a treatment policy.

  Here, as a representative example of a method for generating a map image, there is a map image generation method based on an iterative least square method.

  In the iterative least square method, a transition from a CT value concentration change curve (TDC: Time density curve) in an artery (input artery), which is an input source of blood flow to the capillary in the tissue, shifts to TDC in the capillary in the tissue. The transition factor for is determined.

  That is, in the iterative least square method, when the TDC of the input artery is input, the ideal transition coefficient for outputting the TDC of the capillary in the tissue is repeated until the sum of output errors is minimized. Executed. Then, CBP, CBV, and MTT of intracapillary capillaries are calculated from the TDC of the input artery using an analysis model based on the transition coefficient that minimizes the sum of output errors. In the iterative least square method, the least square sum (Err), which is the sum of output errors, is calculated as an index, and a map image in which Err is mapped on the tissue to be diagnosed is also generated.

  In the iterative least square method, when there are a plurality of input arteries such as brain tissue, a map image is generated by selecting an input artery having the smallest Err as a dominant blood vessel in each capillary blood vessel.

  Here, as a specific example using the iterative least square method, a box-MTF method (box-Modulation Transfer Functional) which approximates a transfer function for transferring from the TDC of the input artery to the TDC of the capillary in the tissue by a rectangular function. Method) is known (see, for example, Patent Documents 1 and 2).

JP 2003-116843 A JP 2003-190148 A

  By the way, the above-described conventional technique has a problem that image diagnosis using a perfusion image may not be performed properly.

  For example, in the conventional technique described above, when there are a plurality of input arteries, the input artery having the smallest mathematically calculated least square sum is selected as the dominant blood vessel, but the input artery having a smaller least square sum is not necessarily selected. It is not necessarily a physiologically relevant dominant blood vessel, and the accuracy of the perfusion image may not be guaranteed.

  In the above-described conventional technique, the transfer coefficient is determined from the TDC in the artery. However, the delay of the contrast start time, the body motion of the subject at the time of imaging, the lesion of the subject (for example, the subject is in the circulatory system) If the TDC in the artery is not appropriate due to the influence of the above disease, it is difficult to guarantee the accuracy of the perfusion image.

  Accordingly, the present invention has been made to solve the above-described problems of the prior art, and provides an image processing apparatus and an image processing program capable of assuring appropriate image diagnosis using a perfusion image. For the purpose.

  In order to solve the above-described problems and achieve the object, the present invention according to claim 1 is generated from a plurality of medical images obtained by photographing a predetermined tissue of a subject administered with a contrast agent in time series. An image processing apparatus that performs image processing on a perfusion image representing blood flow dynamics in capillaries of a predetermined tissue, the contrast agent concentration in an artery of the predetermined tissue measured in the plurality of medical images The perfusion is performed by determining a transition coefficient based on a least square method for outputting a temporal change in contrast agent concentration in capillaries of the predetermined tissue measured in the plurality of medical images from a temporal change When an image is generated, the least square sum image in which the least square sum that is the sum of output errors based on the determined transition coefficient is arranged as the pixel value of the pixel at the same position of the perfusion image is generated. Extracted by a square sum image generating means, a region extracting means for extracting a region of a pixel having a predetermined pixel value or more in the least square sum image generated by the least square sum image generating means, and the region extracting means. And a display control means for controlling the superimposed image to be displayed on a predetermined display unit after aligning the region with the perfusion image.

  The invention according to claim 6 represents blood flow dynamics in capillaries of the predetermined tissue generated from a plurality of medical images taken in time series of the predetermined tissue of the subject to which the contrast medium is administered. An image processing program for causing a computer to execute an image processing method for performing image processing on a perfusion image, which is based on a temporal change in contrast agent concentration in an artery of the predetermined tissue measured by the plurality of medical images. The perfusion image is generated by determining a transition coefficient based on the least-squares method for outputting the temporal change of the contrast agent concentration in the capillary of the predetermined tissue measured in a plurality of medical images. In this case, a least square sum image is generated in which the least square sum that is the sum of output errors based on the determined transfer coefficient is arranged as the pixel value of the pixel at the same position of the perfusion image. Extracted by a least square sum image generation procedure, a region extraction procedure for extracting a region of pixels that are equal to or greater than a predetermined pixel value in the least square sum image generated by the least square sum image generation procedure, and the region extraction procedure The computer is caused to execute a display control procedure for performing control so that the superimposed image superimposed on the perfusion image after the aligned region is aligned with the perfusion image is displayed on a predetermined display unit.

  According to the invention of claim 1 or 6, it is possible to ensure appropriate image diagnosis using the perfusion image.

FIG. 1 is a diagram for explaining the configuration of the X-ray CT apparatus in the present embodiment. FIG. 2 is a diagram for explaining the configuration of the image processing unit in the present embodiment. FIG. 3 is a diagram for explaining the least squares sum image generation unit. FIG. 4 is a diagram for explaining the clustering image generation unit. FIG. 5 is a diagram for explaining the warning area extraction unit. FIG. 6 is a diagram for explaining the superimposed image generation unit. FIG. 7 is a diagram for explaining the TDC creation unit and the system control unit. FIG. 8 is a diagram for explaining a modification of the system control unit. FIG. 9 is a flowchart for explaining the superimposed image display processing of the X-ray CT apparatus in the present embodiment. FIG. 10 is a flowchart for explaining map image non-display processing of the X-ray CT apparatus in the present embodiment.

  Exemplary embodiments of an image processing apparatus and an image processing program according to the present invention will be described below in detail with reference to the accompanying drawings. Hereinafter, a case where the image processing apparatus according to the present invention is incorporated in an X-ray CT apparatus will be described as an example.

  First, main terms used in this embodiment will be described. The “map image” used in the present embodiment is a “perfusion image” representing blood flow dynamics in a capillary vessel. Specifically, the “map image” is an X-ray CT image obtained by photographing a head or abdomen of a subject administered with a contrast agent (for example, a nonionic iodine contrast agent) in time series. This is an image obtained by mapping “CBP”, “CBV”, and “MTT” calculated on the basis of a change in density of CT values over time on an imaged tissue.

  In addition, “CBP”, “CBV”, and “MTT” are indices (indexes) that quantitatively represent blood flow dynamics passing through capillaries in a tissue. Specifically, “CBP” , “CBV” refers to the blood flow per unit volume in the capillary and “MTT” refers to the blood in the capillary. It is the average transit time.

  The “repetitive least squares method” is a representative example of a method of generating a “map image”. In the “repeated least squares method”, an artery (input artery) that is a source of blood flow to the capillary in the tissue A transition coefficient for shifting to the TDC in the intracapillary capillary is calculated from the density change curve (TDC: Time density curve) of the CT value, and a “map image” is generated.

  Specifically, in the “iterative least squares method”, when the TDC of the input artery is input, the ideal transition coefficient for outputting the TDC of the capillary in the tissue has the minimum output error. It is executed repeatedly. In the “iterative least squares method”, the CBP, CBV, and MTT of the capillary in the tissue are calculated from the TDC of the input artery by the analysis model based on the transition coefficient that minimizes the sum of the output errors. An “image” is generated.

  In the “iterative least square method”, the least square sum (Err), which is the sum of output errors based on the determined transition coefficient, is calculated as an index, and a map image in which Err is mapped on the tissue to be diagnosed is also generated. Is done.

  Next, the configuration of the X-ray CT apparatus in the present embodiment will be described with reference to FIG. FIG. 1 is a diagram for explaining the configuration of the X-ray CT apparatus in the present embodiment. As shown in FIG. 1, the X-ray CT apparatus according to the present embodiment includes a gantry device 10, a bed device 20, and a console device 30.

  The gantry device 10 is a device that collects projection data by irradiating the subject P with X-rays, and includes a high voltage generator 11, an X-ray tube 12, an X-ray detector 13, a data collector 14, The rotating frame 15 and the gantry driving unit 16 are included.

  The rotating frame 15 supports the X-ray tube 12 and the X-ray detector 13 so as to face each other with the subject P interposed therebetween, and is a circle that rotates at high speed in a circular orbit around the subject P by the gantry driving unit 16. An annular frame.

  The X-ray tube 12 is a vacuum tube that irradiates the subject P with an X-ray beam with a high voltage supplied by the high voltage generator 11.

  The X-ray detector 13 is an apparatus that detects X-ray intensity distribution data indicating the intensity distribution of the X-rays irradiated from the X-ray tube 12 and transmitted through the subject P. For example, the X-ray detector 13 is, for example, in the channel direction (Y-axis shown in FIG. A plurality of detection element arrays which are X-ray detection elements arrayed in the direction) are arrayed along the body axis direction of the subject P (Z-axis direction shown in FIG. 1).

  The data acquisition unit 14 is a data acquisition system (DAS), and performs projection processing and A / D conversion processing on the X-ray intensity distribution data detected by the X-ray detector 13 to generate projection data. The generated projection data is transmitted to the console device 30 described later.

  The high voltage generator 11 is a device that supplies a high voltage to the X-ray tube 12 under the control of a scan controller 33 described later.

  The gantry driving unit 16 rotates the rotating frame 15 under the control of the scan control unit 33 described later, so that the X-ray tube 12 and the X-ray detector 13 are in a circular orbit around the subject P. Turn with.

  The couch device 20 is a device on which the subject P is placed, and includes a couchtop 22 and a couch driving device 21. The top plate 22 is a plate on which the subject P is placed, and the couch driving device 21 moves the top plate 22 in the Z-axis direction under the control of the scan control unit 33 to be described later. P is moved into the rotating frame 15.

  The console device 30 receives the operation of the X-ray CT apparatus by the operator, reconstructs an X-ray CT image representing the internal form of the subject P from the projection data collected by the gantry device 10, and is reconstructed. An apparatus that performs image processing on an X-ray CT image, and includes an input device 31, a display device 32, a scan control unit 33, a preprocessing unit 34, a projection data storage unit 35, and an image reconstruction unit 36. , An image storage unit 37, an image processing unit 38, and a system control unit 39.

  The input device 31 includes a mouse and a keyboard used by the operator of the X-ray CT apparatus for inputting various instructions and various settings, and receives instructions and setting information received from the operator (for example, a doctor who performs image diagnosis). And transferred to the system control unit 39.

  For example, the input device 31 sets various parameters for a generation method when generating a map image from an abdominal X-ray CT image of a subject P to which a contrast agent is administered, and various types when image processing is performed on the generated map image. Parameter settings and the like are received from the operator and transferred to the system control unit 39.

  The display device 32 is a monitor that is referred to by the operator, and displays an X-ray CT image, a map image, or the like to the operator under the control of the system control unit 39 or from the operator via the input device 31. A GUI (Graphical User Interface) for receiving various settings is displayed.

  The preprocessing unit 34 performs correction processing such as logarithmic conversion processing, offset correction, sensitivity correction, and beam hardening correction on the projection data generated by the data collection unit 14.

  The projection data storage unit 35 stores the projection data corrected by the preprocessing unit 34.

  The image reconstruction unit 36 reconstructs an X-ray CT image by performing back projection processing on the corrected projection data stored in the projection data storage unit 35. Thereby, the image reconstruction unit 36 reconstructs, for example, an X-ray CT image obtained by imaging the abdominal organ (for example, pancreas) of the subject P administered with the contrast agent in time series.

  The image storage unit 37 stores the X-ray CT image reconstructed by the image reconstruction unit 36.

  The image processing unit 38 is a processing unit that reads the X-ray CT image reconstructed by the image reconstruction unit 36 from the image storage unit 37 and performs image processing. Specifically, the image processing unit 38 in the present embodiment generates a map image by an iterative least square method from an X-ray CT image obtained by photographing the pancreas and the like of the subject P to which the contrast medium is administered in time series. To do.

  For example, the image processing unit 38 according to the present embodiment uses a box function that approximates a transfer function, which is a transition coefficient for transition from the TDC of the input artery to the TDC of the intracapillary capillary, as a repetitive least square method using a rectangular function. A map image is generated by the box-Modulation Transfer Functional Method.

  Note that the present invention can be applied to cases other than the box-MTF method in which a map image is generated using an iterative least square method.

  Here, the image storage unit 37 also stores an image (for example, a map image) processed by the image processing unit 38.

  The scan control unit 33 controls the operations of the high voltage generation unit 11, the gantry driving unit 16, the data collection unit 14, and the bed driving device 21 under the system control unit 39. Specifically, the scan control unit 33 controls the gantry driving unit 16 and the high voltage generation unit 11 under the system control unit 39 to rotate the rotating frame 15 during imaging of the subject P. X-rays are emitted from the X-ray tube 12.

  Further, the scan control unit 33 controls the amplification processing and A / D conversion processing of the data collection unit 14 under the system control unit 39. In addition, the scan control unit 33 moves the top 22 by controlling the bed driving device 21 during imaging of the subject P under the system control unit 39.

  The system control unit 39 controls the operations of the gantry device 10, the couch device 20, and the console device 30 based on various setting parameters input by the operator via the input device 31 and preset parameters, Performs overall control of the X-ray CT apparatus. Specifically, the system control unit 39 collects projection data from the gantry device 10 by controlling the scan control unit 33. The system control unit 39 controls the entire image processing in the console device 30 by controlling the preprocessing unit 34, the image reconstruction unit 36, and the image processing unit 38. In addition, the system control unit 39 controls the display device 32 to display various images stored in the image storage unit 37.

  Here, when displaying the generated map image on the display device 32, the X-ray CT apparatus according to the present embodiment performs appropriate image diagnosis using the map image by the function of the image processing unit 38 described in detail below. The main feature is that it is possible to guarantee this. Hereinafter, the main features will be described with reference to FIGS.

  2 is a diagram for explaining the configuration of the image processing unit in the present embodiment, FIG. 3 is a diagram for explaining the configuration of the least square sum image generation unit, and FIG. 4 is a clustering diagram. FIG. 5 is a diagram for explaining the warning area extracting unit, FIG. 6 is a diagram for explaining the superimposed image generating unit, and FIG. 7 is a diagram for explaining the image generating unit. FIG. 8 is a diagram for explaining a TDC creation unit and a system control unit, and FIG. 8 is a diagram for explaining a modification of the system control unit.

  As shown in FIG. 2, the image processing unit 38 in this embodiment includes a map image generation unit 38a, a least square sum image generation unit 38b, a clustering image generation unit 38c, a warning area extraction unit 38d, and a superimposed image generation. A unit 38e and a TDC creation unit 38f.

  The map image generation unit 38a generates a map image by the box-MTF method. Specifically, the map image generation unit 38a determines a transfer function (transition coefficient) from the plurality of X-ray CT images along the time series stored in the image storage unit 37 by the box-MTF method, and the determined transfer function A map image is generated by mapping each index of CBP, CBV, and MTT from (transition coefficient). The map image generation unit 38a may generate three types of map images in which CBP, CBV, and MTT are mapped, or a map image in which an index (for example, CBP) designated by the operator is mapped. It may be the case of generating only.

  The least squares sum image generation unit 38b repeats the least squares sum (Err), which is the sum of output errors based on the transition coefficients determined repeatedly by the least squares method when generating the map image, for the pixels at the same position in the map image. A least square sum image mapped as a pixel value is generated. For example, as shown in FIG. 3, the least square sum image generation unit 38 b sets a pixel value such that the luminance value of a pixel having a larger minimum square sum is higher, and generates a least square sum image.

  Returning to FIG. 2, the clustering image generation unit 38 c generates a clustering image obtained by extracting, as a cluster, regions of pixels having a predetermined pixel value or more in the least square sum image generated by the least square sum image generation unit 38 b.

  Specifically, the clustering image generation unit 38c sets a pixel value of a pixel that is equal to or greater than a predetermined pixel value in the least square sum image to “1”, for example, and sets a pixel value of a pixel that is less than the predetermined pixel value to, for example, A binarization process of “0” is performed. Then, the clustering image generation unit 38c performs expansion processing and reduction processing on the binarized image, thereby removing noise (hole filling and branch removal) in the binarized image. Thereby, the clustering image generation unit 38c generates, for example, a clustering image in which pixel regions having a predetermined pixel value or more are extracted as clusters, as shown in FIG.

  Returning to FIG. 2, the warning area extraction unit 38 d uses, as a warning area, a cluster that satisfies a predetermined condition among the clusters extracted as areas of a predetermined pixel value or more in the clustered image generated by the clustering image generation unit 38 c. Extract. For example, as illustrated in FIG. 5, the warning area extraction unit 38d calculates the areas of each of the six clusters of the clustered image, and labels the clusters as “clusters (1) to (6)” in descending order of the calculated areas. . Then, the warning area extraction unit 38d selects the upper three “clusters (1) to (3)” based on the parameters set by the operator as shown in FIG. ) To (3) ".

  The parameter set for extracting the warning area from the operator may be a “threshold for area”. In this case, the warning area extraction unit 38d extracts a cluster whose area is equal to or greater than the threshold as a warning area.

  In the present embodiment, the case where the warning area extraction unit 38d extracts the warning area based on the area of the cluster has been described. However, the conditions for extracting the warning area can be arbitrarily set by the operator. is there. For example, the condition for extracting the warning area may be a threshold for the average value of the pixel values of the least square sum image corresponding to each cluster.

  Returning to FIG. 2, the superimposed image generation unit 38e generates a superimposed image after aligning the warning region extracted by the warning region extraction unit 38d with the map image generated by the map image generation unit 38a. For example, as shown in FIG. 6, the superimposed image generation unit 38e masks the warning area extracted by the warning area extraction unit 38d with “shaded”, and then generates a superimposed image superimposed on the map image.

  The superimposed image generation unit 38e stores the generated superimposed image in the image storage unit 37, and the system control unit 39 reads the superimposed image from the image storage unit 37 and displays the superimposed image on the display device 32. To control.

  In the present embodiment, a case has been described in which a superimposed image in which a warning area extracted by the warning area extraction unit 38d is superimposed on a map image is displayed. However, the present invention is not limited to this, and clustering image generation is performed. There may be a case where all the clusters of the clustered image generated by the unit 38c are “shaded” as a warning area, a superimposed image superimposed on the map image is generated, and the generated superimposed image is displayed.

  Returning to FIG. 2, when the operator who refers to the superimposed image displayed on the display device 32 by the control of the system control unit 39 specifies one of the warning areas via the input device 31, A TDC in the region of interest is created, and the created TDC is stored in the image storage unit 37.

  For example, assume that the operator designates the warning area (2) via the input device 31, as shown in FIG. When the warning area (2) is designated, the TDC creating unit 38f warns a plurality of X-ray CT images along the time series used when the map image is generated as shown in FIG. 7B. An average value of CT values in the region (2) is calculated, and a TDC in which the calculated average value is plotted along a time series is created.

  The system control unit 39 controls the display device 32 to read the TDC of the region of interest created by the TDC creation unit 38 f from the image storage unit 37. Thereby, the TDC in the warning area (2) shown in FIG. 7B is referred to by the operator.

  Here, it is assumed that the operator refers to the TDC shape of the warning area (2) shown in FIG. 7B and determines that the analysis is inappropriate because the TDC shape is inappropriate. In this case, the operator designates the warning area (2) as the non-analysis area via the input device 31.

  When the warning area (2) is designated as the non-analysis area, the system control unit 39 controls to display a superimposed image from which the area of the map image at the same coordinates as the warning area (2) is removed. To do. Specifically, as shown in FIG. 7C, the system control unit 39 makes the warning area (2) black so that the map image of the warning area (2) is not displayed. Control.

  In the present embodiment, the case where the TDC creation unit 38f creates the TDC of the warning area has been described. However, the present invention is not limited to this, and the TDC creation unit 38f can be set to any arbitrary specified by the operator. It may be a case where a TDC of a region of interest is created. That is, the operator who refers to the TDC of the region of interest specified outside the warning region determines whether the region of interest is a non-analysis region, and the system control unit 39 determines that the region is not an analysis region. Control to hide the map image of the region of interest.

  Further, in this embodiment, the case where the non-analysis target area is specified with reference to the TDC of the area specified by the operator has been described. However, the present invention is not limited to this, for example, as shown in FIG. It may be a case where the non-analysis target area is designated by the operator who refers to the superimposed image in which the warning area is displayed with shading. For example, as shown in FIG. 8, when the warning area (1) having the largest area is designated as the non-analysis area by the operator, the system control unit 39 determines the warning area (1) determined as the non-analysis area. ) Is controlled so as not to be displayed.

  Subsequently, a processing flow of the X-ray CT apparatus in the present embodiment will be described with reference to FIGS. 9 and 10. FIG. 9 is a flowchart for explaining the superimposed image display process of the X-ray CT apparatus in this embodiment, and FIG. 10 is a flowchart for explaining the map image non-display process of the X-ray CT apparatus in this embodiment. It is.

  As shown in FIG. 9, the least square sum image generation unit 38b of the X-ray CT apparatus according to the present embodiment shows a predetermined tissue of the subject P to which the contrast medium is administered by the map image generation unit 38a in time series. When a map image is generated from a plurality of captured X-ray CT images based on the iterative least squares method (Yes in step S101), a least square sum that is the sum of output errors due to the transition coefficients determined by the iterative least squares method is obtained. A mapped least square sum image is generated (step S102).

  Then, the clustering image generation unit 38c performs a binarization process, a dilation process, and a reduction process on the least square sum image, thereby generating a clustered image in which regions where the least square sum is equal to or greater than a predetermined pixel value are extracted as clusters. (Step S103).

  After that, the warning area extraction unit 38d extracts a warning area based on the cluster area extracted from the clustering image (step S104), and the superimposed image generation unit 38e superimposes the warning area and the map image. (A superimposed image in which the warning area is masked with “shaded”) is generated (step S105).

  Subsequently, the system control unit 39 performs control so that the generated superimposed image is displayed on the display device 32 (step S106), and the process ends.

  Here, as illustrated in FIG. 10, when a warning area is designated via the input device 31 by the operator who refers to the superimposed image (Yes in step S201), the TDC creation unit 38f displays the warning area of the designated warning area. A TDC is created (step S202). Specifically, the TDC creation unit 38f calculates the average value of the CT values in the designated warning area of the plurality of X-ray CT images along the time series used when generating the map image, and calculates the calculated average Create a TDC that plots the values over time.

  Then, the system control unit 39 controls to display the TDC of the warning area designated by the operator on the display device 32 (step S203), and the warning area is designated as the non-analysis area by the operator referring to the TDC. It is determined whether or not it has been done (step S204).

  Here, when the warning area is not designated as the non-analysis area by the operator who refers to the TDC (No in step S204), the system control unit 39 ends the process.

  On the other hand, when the warning area is designated as the non-analysis area by the operator who refers to the TDC (Yes in step S204), the system control unit 39 creates a map image corresponding to the warning area designated as the non-analysis area. Control is performed so that the area is not displayed (step S205), and the process is terminated.

  As described above, in the present embodiment, the map image generation unit 38a repeatedly performs the least square method from a plurality of X-ray CT images obtained by imaging a predetermined tissue of the subject P to which the contrast agent is administered in time series. When the map image is generated based on the map, the least square sum image generation unit 38b generates a least square sum image in which the least square sum that is the sum of the output errors based on the transition coefficients determined by the iterative least square method is mapped. . Then, the clustering image generation unit 38c performs a binarization process, a dilation process, and a reduction process on the least square sum image, thereby generating a clustered image in which an area in which the least square sum is a predetermined pixel value or more is extracted as a cluster. The warning area extraction unit 38d extracts a warning area based on the cluster area extracted from the clustering image, and the system control unit 39 superimposes the warning area generated by the superimposed image generation unit 38e and the map image. Control is performed so that the image is displayed on the display device 32.

  Therefore, a doctor who is an operator can determine whether or not the map image in the warning area is generated by a physiologically appropriate dominant blood vessel by referring to the warning area. As described above, It is possible to ensure appropriate image diagnosis using the map image.

  In this embodiment, when a warning area is designated via the input device 31 by the operator who refers to the superimposed image, the TDC creation unit 38f creates a TDC for the designated warning area, and the system control unit 39 controls to display on the display device 32 the TDC of the warning area designated by the operator. When the warning area is designated as the non-analysis area by the operator who refers to the TDC, the system control unit 39 selects a map image area corresponding to the warning area designated as the non-analysis area. Control to hide.

  Therefore, the doctor who is an operator can refer to the shape of the TDC of the designated warning area, and if the referenced TDC is not appropriate, the doctor can remove the warning area from the map image as the outside of the image diagnosis target. It is possible to further ensure appropriate image diagnosis using the.

  In the above-described embodiment, a case has been described in which a map image generated by an iterative least-squares method is processed from an X-ray CT image captured by an X-ray CT apparatus as a medical image, but the present invention is not limited thereto. The map image generated by the repetitive least squares method from the MRI image photographed by the MRI apparatus as a medical image may be processed.

  For example, the MRI apparatus uses a pulse sequence that emphasizes longitudinal relaxation (T1) and susceptibility effect (T2 *) for a predetermined tissue of a subject administered with a contrast agent such as Gd-DTPA (Gadolinium-diethylenetriaminepentaacetic acid). The used dynamic scan is performed, and a map image is repeatedly generated by the least square method from the temporal change in contrast agent concentration in a plurality of MRI images along the time series obtained by the dynamic scan. Then, the MRI apparatus generates a least square sum image and executes image processing in the same manner as in the above-described embodiment. Thereby, it is possible to ensure appropriate image diagnosis using the map image generated from the MRI image.

  In the above-described embodiment, the case where the image processing unit 38 is incorporated in the X-ray CT apparatus has been described. However, the present invention is not limited to this, and for example, connected to the X-ray CT apparatus via a network. An image processing apparatus that has incorporated the function of the image processing unit 38 into an image processing apparatus that has received the X-ray CT image reconstructed by the X-ray CT apparatus generates a least square sum image, and The image processing may be executed in the same manner as in the embodiment. In the present invention, a map image is generated in an X-ray CT apparatus, and the image processing apparatus that has received the map image generated by the X-ray CT apparatus generates a least-squares sum image and is similar to the above-described embodiment. Alternatively, image processing may be executed.

  Each component of each illustrated device is functionally conceptual and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution / integration of each device is not limited to the illustrated one. For example, all or a part of the map image generation unit 38a and the least square sum image generation unit 38b are integrated with various loads. It can be configured to be functionally or physically distributed / integrated in arbitrary units according to the usage situation or the like. Further, all or any part of each processing function performed in each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware by wired logic.

  As described above, the image processing apparatus and the image processing program according to the present invention are provided in the predetermined tissue generated from a plurality of medical images obtained by photographing a predetermined tissue of a subject to which a contrast agent is administered in time series. It is useful when image processing is performed on perfusion images (map images) representing blood flow dynamics in capillaries of blood vessels, and in particular, appropriate image diagnosis using perfusion images (map images) can be guaranteed. Suitable for becoming.

DESCRIPTION OF SYMBOLS 10 Stand apparatus 11 High voltage generation part 12 X-ray tube 13 X-ray detector 14 Data collection part 20 Bed apparatus 21 Bed drive apparatus 22 Top plate 30 Console apparatus 31 Input apparatus 32 Display apparatus 33 Scan control part 34 Pre-processing part 35 Projection Data storage unit 36 Image reconstruction unit 37 Image storage unit 38 Image processing unit 38a Map image generation unit 38b Least square sum image generation unit 38c Clustering image generation unit 38d Warning area extraction unit 38e Superimposition image generation unit 38f TDC generation unit 39 System control Part

Claims (6)

An image for performing image processing on a perfusion image representing blood flow dynamics in capillaries of a predetermined tissue generated from a plurality of medical images taken in time series of a predetermined tissue of a subject administered with a contrast agent A processing device comprising:
Change over time in contrast agent concentration in capillaries of the predetermined tissue measured in the plurality of medical images from change over time in arteries of the predetermined tissue measured in the plurality of medical images When the perfusion image is generated by determining a transition coefficient for outputting the perturbation image based on the least square method, a least square sum that is a sum of output errors due to the determined transition coefficient is calculated as the perfusion image. A least square sum image generating means for generating a least square sum image arranged as a pixel value of pixels at the same position of
In the least square sum image generated by the least square sum image generation means, an area extraction means for extracting an area of a pixel that is a predetermined pixel value or more;
Display control means for controlling to display a superimposed image superimposed on the perfusion image after aligning the area extracted by the area extraction means on a predetermined display unit;
An image processing apparatus comprising:   The display control means displays a superimposed image superimposed on the perfusion image after aligning only the area satisfying a predetermined condition among the areas extracted by the area extracting means on the predetermined display unit. The image processing apparatus according to claim 1, wherein the image processing apparatus is controlled.   When the operator who refers to the superimposed image displayed on the predetermined display unit specifies a non-analysis region via a predetermined input unit, the display control unit corresponds to the specified non-analysis region The image processing apparatus according to claim 1, wherein a control is performed so that the superimposed image from which the region of the perfusion image is removed is displayed on the predetermined display unit. When the operator who refers to the superimposed image displayed on the predetermined display unit by the control of the display control unit specifies a region of interest through a predetermined input unit, the plurality of images used for generating the perfusion image Further comprising a creation means for creating contrast agent concentration change information depicting a state of a change in contrast agent concentration over time in the region of interest of the medical image of
3. The image according to claim 1, wherein the display control unit performs control so that contrast medium concentration change information in the region of interest created by the creating unit is displayed on the predetermined display unit. 4. Processing equipment.   When the operator who refers to the contrast agent concentration change information in the region of interest displayed on the predetermined display unit designates the region of interest as the non-analysis region, the display control unit excludes the designated analysis target 5. The image processing apparatus according to claim 4, wherein control is performed so that a superimposed image from which the region of the perfusion image corresponding to the region is removed is displayed on the predetermined display unit. An image for performing image processing on a perfusion image representing blood flow dynamics in capillaries of a predetermined tissue generated from a plurality of medical images taken in time series of a predetermined tissue of a subject administered with a contrast agent An image processing program for causing a computer to execute a processing method,
Change over time in contrast agent concentration in capillaries of the predetermined tissue measured in the plurality of medical images from change over time in arteries of the predetermined tissue measured in the plurality of medical images When the perfusion image is generated by determining a transition coefficient for outputting the perturbation image based on the least square method, a least square sum that is a sum of output errors due to the determined transition coefficient is calculated as the perfusion image. A least square sum image generation procedure for generating a least square sum image arranged as a pixel value of pixels at the same position of
In the least square sum image generated by the least square sum image generation procedure, a region extraction procedure for extracting a region of pixels that are equal to or greater than a predetermined pixel value;
A display control procedure for controlling to display a superimposed image superimposed on the perfusion image after aligning the region extracted by the region extraction procedure;
An image processing program for causing a computer to execute.

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