Patent Publication Number: US-11380027-B2

Title: Medical image processing apparatus and medical image processing method

Description:
CLAIM OF PRIORITY 
     The present application claims priority from Japanese Patent Application JP 2019-172532 filed on Sep. 24, 2019, the content of which are hereby incorporated by references into this application. 
     BACKGROUND OF THE INVENTION 
     The present invention relates to a medical image processing apparatus and a medical image processing method which are adapted to handle a medical image which is obtained by a medical imaging apparatus such as an X-ray CT (Computed Tomography) apparatus and so forth. 
     BACKGROUND ART 
     The X-ray CT apparatus which is one example of the medical imaging apparatus acquires projection data at a plurality of projection angles by irradiating a subject with X rays which are emitted from various angles around the subject, backprojects the projection data and thereby reconstructs a tomographic image of the subject. The reconstructed tomographic image is used for an image diagnosis of the subject as a medical image. In a case where metal material such as a metal plate which is used for bone fixation is included in the subject, metal-induced artifacts, that is, so-called metal artifacts, are generated in the medical image and hinder the image diagnosis. A technology of reducing the metal artifacts which hinder the image diagnosis is called MAR (Metal Artifact Reduction), and various methods which use this technology are developed. 
     It is disclosed in U.S. Unexamined Patent Application Publication No. 2011/0007956 that a metallic region which is extracted on an original tomographic image is sequentially projected thereby to specify the metallic region on original projection data, and the original projection data is corrected by interpolating a projection value of the specified metallic region by using a projection value of a nonmetallic region. The method disclosed in U.S. Unexamined Patent Application Publication No. 2011/0007956 is called projection space correction because the original projection data is corrected. 
     In addition, it is disclosed in Yiannis Kyriakou, Esther Meyer, Daniel Prell, and Marc Kache lriesz, “Empirical beam hardening correction (EBHC) for CT”, Med. Phys. 37 (10), October 2010, 5179 that a high-density part which is extracted on an original tomographic image is sequentially projected thereby to obtain projection data of the high-density part and a plurality of base images which are obtained by reconstructing a combination of the projection data of the high-density part with original projection data are linearly coupled with the original tomographic image. The method disclosed in “Empirical beam hardening correction (EBHC) for CT” is called image space correction because the original tomographic image is corrected. 
     SUMMARY OF THE INVENTION 
     However, the methods disclosed in U.S. Unexamined Patent Application Publication No. 2011/0007956 and “Empirical beam hardening correction (EBHC) for CT” have both merits and demerits, and the medical image which is suited for the image diagnosis is not necessarily obtained by the abovementioned methods. Specifically, since in the projection space correction, the metallic region which is specified on the original projection data is interpolated by using the projection value of another (the nonmetallic) region, there are cases where a detailed structure in the metallic region may be lost. In addition, in the image space correction, in a case where saturation of the projection data of the high-density part occurs, for example, in a case where a metal-induced X-ray attenuation amount is too large, the metal artifacts are not sufficiently reduced. 
     Accordingly, the present invention aims to provide a medical image processing apparatus and a medical image processing method making it possible to reduce the metal artifacts with no loss of the detailed structure in the metallic region. 
     In order to attain the abovementioned aim, according to one embodiment of the present invention, there is provided a medical image processing apparatus which reconstructs a tomographic image from projection data of a subject in which metal material is included and includes a projection space correction section which corrects the projection data and thereby generates corrected projection data, an image space correction section which corrects the tomographic image by using the corrected projection data, and a coefficient setting section which sets a projection space coefficient which is used in the projection space correction section and an image space coefficient which is used in the image space correction section. 
     According to another embodiment of the present invention, there is also provided a medical image processing method for reconstructing a tomographic image from projection data of a subject in which metal material is included, including a projection space correcting step of correcting the projection data and thereby generating corrected projection data, an image space correcting step of correcting the tomographic image by using the corrected projection data, and a coefficient setting step of setting a projection space coefficient which is used in the projection space correcting step and an image space coefficient which is used in the image space correcting step. 
     According to the present invention, it is possible to provide the medical image processing apparatus and the medical image processing method making it possible to reduce the metal artifacts with no loss of the detailed structure in the metallic region. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an overall configuration diagram illustrating one example of a medical image processing apparatus according to a first embodiment of the present invention; 
         FIG. 2  is an overall configuration diagram illustrating one example of an X-ray CT apparatus which is one example of a medical imaging apparatus; 
         FIG. 3  is a functional block diagram illustrating one example of the medical image processing apparatus; 
         FIG. 4  is a diagram illustrating one example of a flow of processing of a medical image processing method; 
         FIG. 5  is a diagram illustrating one example of a flow of a process in the coefficient setting step in the first embodiment of the present invention; 
         FIG. 6  is a diagram illustrating one example of a metal artifact; 
         FIG. 7  is a diagram illustrating one example of a flow of a process in the projection space correcting step; 
         FIG. 8  is a diagram illustrating one example of a flow of a process in the image space correcting step; 
         FIG. 9  is a diagram illustrating one example of a flow of a process in the coefficient setting step according to a second embodiment of the present invention; 
         FIG. 10  is a diagram illustrating one example of a flow of a process in the coefficient setting step according to a third embodiment of the present invention; and 
         FIG. 11  is a diagram illustrating another example of the flow of the process in the coefficient setting step according to the third embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     In the following, embodiments of a medical image processing apparatus and a medical image processing method according to the present invention will be described with reference to the appended drawings. Incidentally, in the following description and the appended drawings, the same numerals are assigned to the constitutional elements having the same functional configurations, and repetitive description thereof is omitted. 
     First Embodiment 
       FIG. 1  is a diagram illustrating one example of a hardware configuration of a medical image processing apparatus  1  according to the first embodiment of the present invention. The medical image processing apparatus  1  is configured such that a CPU (Central Processing Unit)  2 , a memory  3 , a storage device  4 , and a network adapter  5  are connected with one another via a system bus  6  so as to freely transmit and receive signals. In addition, the medical image processing apparatus  1  is connected with a medical imaging apparatus  10  and a medical image database  11  over a network  9  so as to freely transmit and receive signals and is also connected with a display device  7  and an input device  8 . Here, “to freely transmit and receive the signals” indicates a state of freely transmitting and receiving the signals electrically and optically mutually or from one to the other both in wired and wireless states. 
     The CPU  2  controls operations of respective constitutional elements. The CPU  2  loads a program and data which is necessary for execution of the program which are stored in the storage device  4  into the memory  3 , executes the loaded program, and performs various types of image processing on a medical image. The memory  3  memorizes interim progress of the program and arithmetic processing that the CPU  2  executes. The storage device  4  stores the program that the CPU  2  executes and the data which is necessary for execution of the program, and is specifically an HDD (Hard Disk Drive), an SSD (Solid State Drive, and so forth. The network adapter  5  is adapted to connect the medical image processing apparatus  1  to the network  9  such as a LAN (Local Area Network), a telephone line, the Internet, and so forth. Various types of data that the CPU  2  handles may be transmitted to and received from the outside of the medical image processing apparatus  1  over the network  9  such as the LAN. 
     The display device  7  displays a result of processing and so forth that the medical image processing apparatus  1  executes and is specifically a liquid crystal display and so forth. The input device  8  is an operation device through which an operator gives operation instructions to the medical image processing apparatus  1  and is specifically a keyboard, a mouse, a touch panel, and so forth. The mouse may be other pointing devices such as a trackpad and a trackball. 
     The medical imaging apparatus  10  is an X-ray CT (Computed Tomography) apparatus  100  which acquires, for example, projection data on a subject  210  and reconstructs a tomographic image from the projection data and will be described later by using  FIG. 2 . The medical image database  11  is a database system which stores the projection data, the tomographic image, and so forth which are acquired by the medical imaging apparatus  10 . 
     An overall configuration of the X-ray CT apparatus  100  which is one example of the medical imaging apparatus  10  will be described by using  FIG. 2 . Incidentally, in  FIG. 2 , it is supposed that a lateral direction is an X-axis, a longitudinal direction is a Y-axis, and a direction which is vertical to a paper surface is a Z-axis. The X-ray CT apparatus  100  includes a scanner  200  and an operation unit  250 . The scanner  200  has an X-ray tube  211 , a detector  212 , a collimator  213 , a drive section  214 , a central control section  215 , an X-ray control section  216 , a high voltage generation section  217 , a scanner control section  218 , a bed control section  219 , a collimator control section  221 , a preamplifier  222 , an A/D converter  223 , a bed  240 , and so forth. 
     The X-ray tube  211  irradiates the subject  210  who is laid down on the bed  240  with X rays. A high voltage that the high voltage generation section  217  generates is applied to the X-ray tube  211  and thereby the subject  210  is irradiated with the X rays which are emitted from the X-ray tube  211  in accordance with a control signal which is transmitted from the X-ray control section  216 . 
     The collimator  213  restricts a range which is irradiated with the X rays which are emitted from the X-ray tube  211 . The X-ray irradiation range is set in accordance with a control signal which is transmitted from the collimator control section  221 . 
     The detector  212  detects the X rays which transmit through the subject  210  and thereby measures a spatial distribution of the transmitted X-rays. The detector  212  is disposed so as to face the X-ray tube  211 , and many detection elements are two-dimensionally arrayed in a plane which faces the X-ray tube  211 . A signal which is measured by the detector  212  is amplified by the preamplifier  222  and then is converted into a digital signal by the A/D converter  223 . Then, various types of correction processing are performed on the digital signal, and thereby projection data is acquired. 
     The drive section  214  drives the X-ray tube  211  and the detector  212  so as to rotate around the subject  210  in accordance with a control signal which is transmitted from the scanner control section  218 . X-ray irradiation and detection are performed in association with rotation of the X-ray tube  211  and the detector  212 , and thereby the projection data which is collected from a plurality of projection angles is acquired. A data collection unit per projection angle is called view. In arrangement of the respective detection elements of the detector  212  which are two-dimensionally arrayed, a rotation direction of the detector  212  is called a channel and a direction which is orthogonal to the channel is called a column. The projection data is identified on the basis of the view, the channel, and the column. 
     The bed control section  219  controls an operation of the bed  240  so as to maintain the bed  240  in a stationary state and/or to move the bed  240  in the Z-axis direction at a constant velocity while the X-ray irradiation and detection are being performed. A scan which is performed in a state of maintaining the bed  240  in the stationary state is called an axial scan and a scan which is performed while moving the bed  240  is called a spiral scan respectively. 
     The central control section  215  controls the above-described operations of the scanner  200  in accordance with instructions from the operation unit  250 . Next, the operation unit  250  will be described. The operation unit  250  has a reconstruction processing section  251 , an image processing section  252 , a storage section  254 , a display section  256 , an input section  258 , and so forth. 
     The reconstruction processing section  251  reconstructs the tomographic image by backprojecting the projection data that the scanner  200  acquires. The image processing section  252  performs various types of image processing for making the tomographic image into an image which is suitable for a diagnose. The storage section  254  stores the projection data, the tomographic image, and the image which is obtained after execution of the image processing. The display section  256  displays the tomographic image and the image which is obtained after execution of the image processing. The input section  258  is used in a case where the operator sets scanning conditions (a tube voltage, a tube current, a scanning speed, and so forth) used when acquiring the projection data of the subject  210  and tomographic image reconstruction conditions (a reconstruction filter, an FOV (Field Of View) size, and so forth). 
     Incidentally, the operation unit  250  may be the medical image processing apparatus  1  which is illustrated in  FIG. 1 . In this case, the reconstruction processing section  251  and the image processing section  252  correspond to the CPU  2 , the storage section  254  corresponds to the storage device  4 , the display section  256  corresponds to the display device  7 , and the input section  258  corresponds to the input device  8 , respectively. 
     Essential parts of the medical image processing apparatus  1  according to the first embodiment will be described by using  FIG. 3 . Incidentally, the essential parts may be configured by either dedicated hardware or software which operates on the CPU  2 . In the following, a case where the essential parts according to the first embodiment are configured by the software will be described. 
     The medical image processing apparatus  1  according to the first embodiment includes a projection space correction section  301 , an image space correction section  302 , and a coefficient setting section  303  which operate on the CPU  2 . In addition, the tomographic image and the projection data which are generated by the X-ray CT apparatus  100  are stored in the storage device  4 . In the following, respective components will be described. 
     The projection space correction section  301  corrects the projection data of the subject  210  which includes metal material and thereby generates corrected projection data. Specifically, the corrected projection data is generated by using metal projection data which is obtained by sequentially projecting a metal image in which a metallic region is extracted, nonmetal projection data which is obtained by interpolating a projection value of the metallic region which is specified on the projection data by using a projection value of a nonmetallic region, a projection space coefficient to be described later, and so forth. 
     The image space correction section  302  corrects the tomographic image of the subject  210  by using the corrected projection data that the projection space correction section  301  generates. Specifically, the tomographic image of the subject  210  is corrected by using a base image which is reconstructed from the projection data of the subject  210  and base projection data which is generated by combining the nonmetal projection data with the metal projection data, the corrected projection data, an image space coefficient to be described later, and so forth. 
     The coefficient setting section  303  sets the projection space coefficient that the projection space correction section  301  uses and the image space coefficient that the image space correction section  302  uses. Specifically, the projection space coefficient and the image space coefficient are set by the coefficient setting section  303  on the basis of any of a feature value of the metal material which is included in the subject  210 , the scanning condition concerned used when acquiring the projection data of the subject  210 , and the reconstruction condition concerned used when reconstructing the tomographic image of the subject  210 . 
     One example of a flow of processing which is executed by the medical image processing apparatus  1  according to the first embodiment will be described by using  FIG. 4 . 
     (S 401 ) 
     The coefficient setting section  303  sets the projection space coefficient and the image space coefficient. The projection space coefficient and the image space coefficient are set on the basis of any of the feature value of the metal material which is included in the subject  210 , the scanning condition concerned which is used when acquiring the projection data of the subject  210 , and the reconstruction condition concerned which is used when reconstructing the tomographic image of the subject  210 . 
     One example of a flow of a process in S 401  will be described by using  FIG. 5 . In the first embodiment, the projection space coefficient and the image space coefficient are set on the basis of the feature value of the metal material which is included in the subject  210 . 
     (S 501 ) 
     The coefficient setting section  303  acquires projection data P org  of the subject  210  which includes the metal material. The projection data P org  is read out of the storage device  4  and/or transmitted from the outside via the network adapter  5 . 
     (S 502 ) 
     The coefficient setting section  303  reconstructs a tomographic image F org  from the projection data P org . A metal artifact is generated in the tomographic image F org  under the influence of the metal material. One example of the metal artifact is illustrated in  FIG. 6 .  FIG. 6  illustrates one example of a tomographic image which is obtained by scanning an abdominal phantom and in which a dark band is generated between tow metallic regions which are present in the liver, and streak artifacts which extend starting from the respective metallic regions are generated. 
     (S 503 ) 
     The coefficient setting section  303  extracts the metallic region from within the tomographic image F org  and thereby generates a metal image F mtl . Thresholding is used for extraction of the metallic region. In a case where, for example, 2000 HU (Hounsfield Unit) is set as a threshold value, a pixel having a pixel value which exceeds 2000 HU is extracted as the metallic region on the tomographic image F org . The threshold value used for the thresholding may be set to a larger value as a maximum pixel value of the tomographic image F org  becomes larger. A pixel value which corresponds to a soft tissue is subtracted from a pixel value of the extracted metallic region, a pixel value which corresponds to air, for example, −1000 HU is set as a threshold value of a pixel value of a region other than the metallic region, and thereby the metal image F mtl  is generated. It becomes possible to avoid excessive enlargement of a projection value of first order corrected projection data to be described later by subtracting the pixel value of the soft tissue from the pixel value of the metallic region. The coefficient setting section  303  may generate the metal projection data P mtl  by sequentially projecting the metal image F mtl . 
     (S 504 ) 
     The coefficient setting section  303  calculates the feature value of the metallic region by using the metal image F mtl . One of a maximum pixel value v mtl_max , an area v mtl_area , and roundness v mtl_shp  of the metallic region is included in the feature value of the metallic region. 
     The maximum pixel value v mtl_max  of the metallic region is obtained by extracting a maximum value from within the pixel values of the metal image F mtl . 
     The area v mtl_area  of the metallic region is obtained by counting the number of pixels in the metallic region and multiplying a per-pixel area by the counted number of the pixels. Incidentally, in a case where the plurality of metallic regions are present, a total area of the metallic regions is obtained by adding up the numbers of pixels which are counted in the respective metallic regions and multiplying the added-up number of pixels by the per-pixel area. 
     The roundness v mtl_shp  of the metallic region is obtained by dividing a minor axis of the metallic region by a major axis of the metallic region. The smaller a difference between the major axis and the minor axis is, the larger the roundness v mtl_shp  is, and the larger the difference between the major axis and the minor axis is, the smaller the roundness v mtl_shp  is. Incidentally, in a case where the plurality of metallic regions are present, the minor axis and the major axis are obtained by regarding the plurality of metallic regions as one metallic region. That is, also each distance between the respective metallic regions concerned is included, and then the minor axis and the major axis are obtained. 
     The roundness v mtl_shp  of the metallic region may also be obtained by using the metal projection data P mtl . In a case where the metal projection data P mtl  is used, the roundness v mtl_shp  is obtained by the following formula. 
     
       
         
           
             
               
                 
                   
                       
                   
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     Here, A min ( ) is an operator used for obtaining a minimum value, A max ( ) is an operator used for obtaining a maximum value, view is a view position, slice is a column position, and ch is a channel position. In addition, d(view, slice) is a channel-direction dispersion of the projection values of view, slice in the metal projection data P mtl , and g(view, slice) is a gravity center channel of the projection values of view, slice in the metal projection data P mtl . 
     The coefficient setting section  303  sets a projection space coefficient β raw  and an image space coefficient β img  on the basis of the feature value of the metallic region. The projection space coefficient β raw  is obtained by, for example, the following formula.
 
β raw =γ·(λ· v   mtl_max   +μ·v   mtl_area   +ξ·v   mtl_shp )  [Numerical Formula 2]
 
     In addition, the image space coefficient β img  is obtained by, for example, the following formula.
 
β img =ρ−β raw   [Numerical Formula 3]
 
     Here, γ is an operator-settable variable, λ, ρ, ξ, and ρ are positive constants. The variable γ is set by the operator through the input device  8 . The constants λ, μ, ξ, and ρ are empirically set in advance on the basis of a result of scanning of a phantom which includes the metal material whose shape and attenuation coefficient are already known. The projection space coefficient β raw  is transmitted to the projection space correction section  301  and the image space coefficient β img  is transmitted to the image space correction section  302 . 
     According to the numerical formula 2, the larger any of the maximum pixel value v mtl_max , the area v mtl_area , and the roundness v mtl_shp  which are the feature values of the metallic region is, the larger the projection space coefficient β raw  becomes. In addition, according to the numerical formula 3, the larger the projection space coefficient β raw  is, the smaller the image space coefficient β img  becomes. That is, the larger the feature value concerned of the metallic region is, the more a projection space correction ratio in which the original projection data is corrected is increased than an image space correction ratio in which the original tomographic image is corrected. In a case where the feature value concerned of the metallic region is large, it is possible to sufficiently reduce the metal artifacts which are not sufficiently reduced by the image space correction by increasing the projection space correction ratio. 
     Further, in a case where the image space coefficient βi mg  is uniquely determined, for example, in a case where the method disclosed in “Empirical beam hardening correction (EBHC) for CT” is used, the projection space coefficient β raw  may be set on the basis of the numerical formula 3. In addition, according to the numerical formula 2, it is possible for the operator to freely set the projection space coefficient β raw  while comparing images which are obtained before correction and after correction with each other by adjusting the variable γ. 
     Description will be made by returning to  FIG. 4 . 
     (S 402 ) 
     The projection space correction section  301  corrects the projection data P org  by using the projection space coefficient β raw . One example of a flow of a process in the step S 402  will be described by using  FIG. 7 . 
     (S 701 ) 
     The projection space correction section  301  generates nonmetal projection data P lin  in the following procedure. First, the projection space correction section  301  specifies the metallic region on the projection data P org  on the subject  210  by using metal projection data P mtl  which is generated by sequentially projecting the metal image F mtl . Next, the projection space correction section  301  replaces the projection value of the metallic region which is specified on the projection data P org  with a value which is obtained by interpolating the projection value by using projection values of nonmetallic regions which are adjacent to the metallic region. In short, the projection space correction section  301  obtains a mean value of the projection values of the two nonmetallic regions which are adjacent to the metallic region in the channel direction and replaces the projection value of the metallic region with the obtained mean value. In another example, the projection space correction section  301  replaces the projection value of the metallic region with a value which is obtained by linearly interpolating the projection value by using projection values of nonmetallic regions which are adjacent to the metallic region in the channel direction and the column direction. The nonmetal projection data P lin  in which the metallic region is not included is generated by such replacement using an interpolated value as described above. Not only the metallic region is not included in the nonmetal projection data P lin  but also artifact components which are generated under the influence of the metal material are reduced in the nonmetal projection data P lin . 
     (S 702 ) 
     The projection space correction section  301  generates first order corrected projection data P fst_c  by adding the nonmetal projection data P lin  and the metal projection data P mtl  together. Since the nonmetal projection data P lin  in which the metal artifact components are reduced and the metal projection data P mtl  which includes the projection value of the metallic region are added together, the first order corrected projection data P fst_c  becomes projection data in which the metal artifacts are reduced while including the projection value of the metallic region. Incidentally, since the pixel value of the soft tissue is subtracted from the pixel value of the metallic region in S 503 , the projection value of the metallic region on the first order corrected projection data P fst_c  does not reach an extremely large value. 
     (S 703 ) 
     The projection space correction section  301  generates error projection data P err  by subtracting the first order corrected projection data P fst_c  from the projection data P org  of the subject  210 . Since the first order corrected projection data P fst_c  in which the metal artifacts are reduced is subtracted from the original projection data P org , the error projection data P err  becomes projection data in which the metal artifact is contained as the main component. 
     (S 704 ) 
     The projection space correction section  301  corrects the projection data P org  by using the error projection data P err  and the projection space coefficient β raw  and thereby generates corrected projection data P corr . The corrected projection data P corr  is generated by, for example, the following formula.
 
 P   corr   =P   org −β raw   ·P   err   [Numerical Formula 4]
 
     Incidentally, correction of the projection data P org  is not limited to the correction using the numerical formula 4, for example, the first order corrected projection data P fst_c  which is generated in S 702  may be used in place of the corrected projection data P corr , and the projection data P org  may be corrected by a well-known method such as the method disclosed in “Empirical beam hardening correction (EBHC) for CT”. 
     Description will be made by retuning to  FIG. 4 . 
     (S 403 ) 
     The CPU  2  or the reconstruction processing section  251  reconstructs a tomographic image F raw_corr  from the corrected projection data P corr  which is generated in step S 402 . 
     (S 404 ) 
     The image space correction section  302  corrects the tomographic image F raw_corr  by using the projection space coefficient β img . One example of a flow of a process in step S 404  will be described by using  FIG. 8 . 
     (S 801 ) 
     The image space correction section  302  generates base projection data P base  which serves as the base of the metal artifact. The base projection data P base  is generated by, for example, the following formula as data which is subjected to series expansion by the nonmetal projection data P lin  and the metal projection data P mtl  or by the projection data P org  and the metal projection data P mtl .
 
 P   base   =P   lin   m   ·P   mtl   n  or
 
 P   base   =P   org   m   ·P   mtl   n [  Numerical Formula 5]
 
     Here, m and n are integers and a combination of m with n is set depending on a necessary correction accuracy and an allowable arithmetic operation time and, for example, (m, n)=(1, 1), (0, 2) is set. 
     (S 802 ) 
     The image space correction section  302  generates a base image F base  by using the base projection data P base . The base image F base  is reconstructed from the base projection data P base  and is generated in accordance with the number of pieces of the base projection data P base  which are generated in S 801 . That is, in a case where the number of pieces of the base projection data P base  is L, the number of the base images F base  is L. For example, in a case where (m, n)=(1, 1), (0, 2) is set, L=2. 
     (S 803 ) 
     The image space correction section  302  generates an error image F err  by subjecting the base images F base  to weighted addition. The error image F err  is generated by, for example, the following formula. 
     
       
         
           
             
               
                 
                   
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                       · 
                       
                         
                           F 
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     Here, w(1) is a first-item weighting coefficient and is empirically set in advance on the basis of the result of scanning of the phantom which includes the metal material whose shape and attenuation coefficient are already known and/or is calculated by a sequential solution. 
     (S 804 ) 
     The image space correction section  302  corrects the tomographic image F raw_corr  by using the error image F err  and the image space coefficient β img  and thereby generates a corrected image F img_corr . The corrected image F img_corr  is generated by, for example, the following formula.
 
 F   img_corr   =F   raw_corr −β img   ·F   err   [Numerical Formula 7]
 
     Incidentally, correction of the tomographic image F raw_corr  is not limited to the correction using the numerical formula 7 and the tomographic image F raw_corr  may be corrected by the well-known method such as the method disclosed in “Empirical beam hardening correction (EBHC) for CT”. 
     Since the projection space coefficient β raw  and the image space coefficient β img  are set on the basis of the feature value concerned of the metallic region along the flow of the above-described process, it is possible to reduce the metal artifacts with no loss of a detailed structure in the metallic region. 
     Second Embodiment 
     In the first embodiment, it is described that the projection space coefficient β raw  and the image space coefficient β img  are set on the basis of any one of the feature values of the metallic region. In the second embodiment, description will be made in regard to the point that the projection space coefficient β raw  and the image space coefficient β img  are set on the basis of a scanning condition, in particular, on the basis of a cone angle which is an opening angle of a projection line which runs in a body-axis direction of the subject  210 . Incidentally, since the second embodiment is different from the first embodiment only in the flow of the process in S 401  in  FIG. 4 , description about other points is omitted. 
     One example of a flow of a process of setting the projection space coefficient β raw  and the image space coefficient β img  in the second embodiment will be described by using  FIG. 9 . 
     (S 901 ) 
     The coefficient setting section  303  acquires the scanning condition. The scanning condition is read out of the storage device  4  and/or transmitted from the outside via the network adapter  5 . 
     (S 902 ) 
     The coefficient setting section  303  acquires the cone angle of each projection value of the projection data P org  on the basis of the scanning condition. The cone angle is the opening angle of the projection line which runs in the body axis direction of the subject  210  and is determined on the basis of a channel position and a column position of each projection value. 
     (S 903 ) 
     The coefficient setting section  303  sets the projection space coefficient β raw  and the image space coefficient β img  on the basis of the cone angle of each projection value. Specifically, the smaller the cone angle is, the larger the projection space coefficient β raw  is set and the smaller the image space coefficient β img  is set. In a case where the cone angle is large, since an error which would occur when generating the metal projection data P mtl  by sequentially projecting the metal image F mtl  in projection space correction becomes large, image deterioration caused by the projection space correction is suppressed by setting the projection space coefficient β raw  small. 
     Since the projection space coefficient β raw  and the image space coefficient β img  are set on the basis of the scanning condition, in particular, on the basis of the cone angle which is the opening angle of the projection line which runs in the body-axis direction of the subject  210  along the flow of the above-described process, it is possible to reduce the metal artifacts with no loss of the detailed structure in the metallic region. 
     Third Embodiment 
     In the first embodiment, it has been described that the projection space coefficient β raw  and the image space coefficient β img  are set on the basis of the feature value concerned of the metallic region. In the third embodiment, description will be made with regard to the point that the projection space coefficient β raw  and the image space coefficient β img  are set on the basis of the magnitude of body motion of the subject  210  when scanning the projection data P org . Incidentally, since the third embodiment is different from the first embodiment only in the flow of the process in S 401  in  FIG. 4 , the description about other points is omitted. 
     One example of a flow of a process of setting the projection space coefficient β raw  and the image space coefficient β img  in the third embodiment will be described by using  FIG. 10 . 
     (S 1001 ) 
     The coefficient setting section  303  acquires the scanning condition concerned or the reconstruction condition concerned. The scanning condition concerned or the reconstruction condition concerned is read out of the storage device  4  and/or is transmitted from the outside via the network adaptor  5 . 
     (S 1002 ) 
     The coefficient setting section  303  specifies a scanned region where the projection data P org  is scanned on the basis of the scanning condition concerned or the reconstruction condition concerned. Specifically, in a case where electrocardiogram-gated scanning or electrocardiogram-gated reconstruction is being performed or in a case where a reconstruction filter for the heart and lung fields is selected, it is specified that the scanned region is the heart or the chest. 
     (S 1003 ) 
     The coefficient setting section  303  sets the projection space coefficient β raw  and the image space coefficient β img  on the basis of the scanned region. Specifically, in a case where the scanned region is a region which is large in body motion just like the heart or the chest, the projection space coefficient β raw  is set small and the image space coefficient β img  is set large. In addition, in a case where the scanned region is a region which is small in body motion just like the head, the projection space coefficient β raw  is set large and the image space coefficient β img  is set small. In a case where the body motion is large, since the error which would occur when generating the metal projection data P mtl  by sequentially projecting the metal image F mtl  in the projection space correction becomes large, the image deterioration caused by the projection space correction is suppressed by setting the projection space coefficient β raw  small. 
     Since the projection space coefficient β raw  and the image space coefficient β img  are set on the basis of the magnitude of the body motion of the scanned region along the flow of the above-described process, it is possible to reduce the metal artifacts with no loss of the detailed structure in the metallic region. 
     Another example of the flow of the process of setting the projection space coefficient β raw  and the image space coefficient β img  in the third embodiment will be described by using  FIG. 11 . 
     (S 1101 ) 
     The coefficient setting section  303  acquires the projection data P org  of the subject  210  which includes the metal material. The projection data P org  is read out of the storage device  4  and/or is transmitted from the outside via the network adaptor  5 . 
     (S 1102 ) 
     The coefficient setting section  303  calculates a differential value between the projection data P org  and projection data which is opposed to the projection data P org , that is, counter projection data which is different from the projection data P org  in projection angle by 180 degrees. Since the counter projection data is obtained by scanning the region where the projection data P org  is scanned from an opposite direction, in a case where no body motion takes place, the differential value is reduced to zero and an absolute value of the differential value is increased as the body motion becomes large. 
     (S 1103 ) 
     The coefficient setting section  303  sets the projection space coefficient β raw  and the image space coefficient β img  on the basis of the absolute value of the differential value. Specifically, in a case where the absolute value of the differential value is large, the projection space coefficient β raw  is set large and the image space coefficient β img  is set small. In a case where the absolute value of the differential value which indicates the magnitude of the body motion is large, since the error which would occur when generating the metal projection data P mtl  by sequentially projecting the metal image F mtl  in the projection space correction becomes large, the image deterioration caused by the projection space correction is suppressed by setting the projection space coefficient β raw  small. 
     Since the projection space coefficient β raw  and the image space coefficient β img  are set on the basis of the magnitude of the body motion of the scanned region also along the flow of the above-described process, it is possible to reduce the metal artifacts with no loss of the detailed structure in the metallic region. 
     Incidentally, the medical image processing apparatus and the medical image processing method of the present invention are not limited to the above-described embodiments and may be embodied by modifying the constitutional elements within the range not deviating from the gist of the present invention. In addition, the plurality of the constitutional elements which are disclosed in the abovementioned embodiments may be mutually combined appropriately. For example, configurations of the first to third embodiments may be mutually combined so as to set the projection space coefficient β raw  and the image space coefficient βi mg  on the basis of the feature value(s) of the metallic region, the cone angle, and the magnitude of the body motion. Further, some constitutional elements may be deleted from all the constitutional elements described in the abovementioned embodiments. 
     REFERENCE SIGNS LIST 
       1 : medical image processing apparatus,  2 : CPU,  3 : memory,  4 : storage device,  5 : network adapter,  6 : system bus,  7 : display device,  8 : input device,  10 : medical imaging apparatus,  11 : medical image database,  100 : X-ray CT apparatus,  200 : scanner,  210 : subject,  211 : X-ray tube,  212 : detector,  213 : collimator,  214 : drive section,  215 : central control section,  216 : X-ray control section,  217 : high voltage generation section,  218 : scanner control section,  219 : bed control section,  221 : collimator control section,  222 : preamplifier,  223 : A/D converter,  240 : bed,  250 : operation unit,  251 : reconstruction processing section,  252 : image processing section,  254 : storage section,  256 : display section,  258 : input section,  301 : projection space correction section,  302 : image space correction section,  303 : coefficient setting section