Patent Publication Number: US-8989470-B2

Title: Image processing apparatus, program and image diagnostic apparatus for high-frequency enhancement processing

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of Japanese Patent Application No. 2011-040984 filed Feb. 26, 2011, which is hereby incorporated by reference in its entirety. 
     BACKGROUND OF THE INVENTION 
     The present invention relates to an image processing apparatus, a program and an image diagnostic apparatus which improve spatial resolution of an image. 
     Conventionally, in many X-ray CT (Computed Tomography) apparatuses, an arithmetic operation for overlay with a reconstruction function is performed on projection data acquired by imaging, and back projection processing is executed thereon to thereby reconstruct an X-ray CT image. 
     The quality of the X-ray CT image depends on the characteristic of the reconstruction function used in image reconstruction. Therefore, in each X-ray CT apparatus, a plurality of types of reconstruction functions respectively different in the quality of the reconstructed image are prepared and provided to a user. There are prepared, for example, a lung field function close to high spatial resolution so adjusted that a high-frequency component appears relatively strongly, a soft part function close to low noise so adjusted that a high-frequency component appears relatively weakly, a standard function having an intermediate property between these, etc. The user properly uses these reconstruction functions according to diagnostic purposes, sections to be observed and the like. See, for example, paragraphs [0021], [0029] and [0030] of Japanese Patent Application Laid-Open No. 2004-073432. 
     On the other hand, when an image is reconstructed using a reconstruction function, spatial resolution and noise level in the reconstructed image are in a trade off relationship with respect to each other. Therefore, when such a reconstruction function that the high-frequency component appears extremely strongly is used in an attempt to enhance the spatial resolution to the maximum, an increase in noise becomes sharp so that the image may result in an image that does not withstand a practical use. 
     With this situation, in regard to the previously-prepared reconstruction function, the balance between spatial resolution and a noise level has been adjusted within a range durable for practical use. Therefore, even in the case of the reconstruction function close to the highest spatial resolution, potential spatial resolution of projection data has not yet been drawn to a maximal degree. 
     On the other hand, a section (e.g., auditory ossicles or the like) having a very fine structure even within the sections of a subject has been desired at a higher spatial resolution. There has been room for further high spatial resolution. However, when using the reconstruction function adjusted such that an improvement in spatial resolution is pursued at random, and such that the high-frequency component appears strongly, noise is increased needlessly with respect to a region that does not require such a high spatial resolution (e.g., a soft tissue region), thus leading to an undesirable result. 
     With the foregoing in view, a process capable of making a further improvement in spatial resolution for the region without increasing noise needlessly is desired. 
     SUMMARY OF THE INVENTION 
     In a first aspect, an image processing apparatus is provided. The image processing apparatus includes an acquiring device which acquires a typical pixel value corresponding to a noted region in an image, a calculating device which calculates index values of variances in pixel values in the noted region or the noted region and an adjacent region thereof, a first enhancement degree determination device which determines an enhancement degree according to the acquired typical pixel value and each of the calculated index values, and an image processing device which performs high-frequency enhancement processing on the noted region, based on the enhancement degree determined by the first enhancement degree determination device. 
     In a second aspect the image processing apparatus according to the first aspect is provided, wherein the first enhancement degree determination device specifies an enhancement degree corresponding to each of the calculated index values, based on a first relation that indicates a relation between each of the index values of the variances and the enhancement degree and varies according to the typical pixel value corresponding to the noted region. 
     Incidentally, the first enhancement degree determination device determines the first relation according to a typical pixel value. It partly includes such a case that a plurality of different typical pixel values and the same relation are associated with each other. 
     In a third aspect, the image processing apparatus according to the second aspect is provided, wherein in the first relation, each of index values of variances included in a first range and a first enhancement degree are associated with each other, each of index values of variances included in a second range larger in index value than the first range and a second enhancement degree smaller than the first enhancement degree are associated with each other, and each of index values of variances included in a third range larger in index value than the second range and a third enhancement degree larger than the second enhancement degree are associated with each other. 
     In a fourth aspect, the image processing apparatus according to the third aspect is provided, wherein the second range is a range of index values of variances corresponding to the existence of an artifact. 
     In a fifth aspect, the image processing apparatus according to any one of the first to fourth aspects is provided, further including second enhancement determination device which determines an enhancement degree according to the acquired typical pixel value, wherein the image processing device performs high-frequency enhancement processing on the noted region, based on the enhancement degree determined by the second enhancement degree determination device. 
     In a sixth aspect, the image processing apparatus according to the fifth aspect is provided, wherein the second enhancement degree determination device specifies an enhancement degree corresponding to the acquired typical pixel value, based on a second relation indicative of a relation between a typical pixel value corresponding to the noted region and an enhancement degree. 
     In a seventh aspect, the image processing apparatus according to the sixth aspect is provided, wherein in the second relation, a typical pixel value included in a fourth range and a fourth enhancement degree are associated with each other, a typical pixel value included in a fifth range larger in pixel value than the fourth range and a fifth enhancement degree than the fourth enhancement degree are associated with each other, a typical pixel value included in a sixth range larger in pixel value than the fifth range and a sixth enhancement degree smaller than the fifth enhancement degree are associated with each other, and a typical pixel value included in a seventh range larger in pixel value than the sixth range and a seventh enhancement degree larger than the sixth enhancement degree are associated with each other. 
     In an eighth aspect, the image processing apparatus according to the seventh aspect is provided, wherein the fourth range is a range of pixel values corresponding to the existence of air, and the sixth range is a range of pixel values corresponding to the existence of a soft tissue. 
     In a ninth aspect, the image processing apparatus according to any one of the sixth to eighth aspects is provided, wherein the image is an X-ray CT image, and wherein the second enhancement degree determination device determines an enhancement degree, based on the second relation that varies according to a reconstruction function used in reconstruction of the X-ray CT image. 
     Incidentally, the second enhancement degree determination device determines the second relation according to a reconstruction function. It partly includes such a case that a plurality of different reconstruction functions and the same relation are associated with each other. 
     In a tenth aspect, the image processing apparatus according to any one of the first to ninth aspects is provided, further including third enhancement degree determination device which determines an enhancement degree in such a manner that a larger value is acquired when an edge is not detected by edge detection processing on the noted region or the noted region and an adjacent region thereof rather than when the edge is detected by the edge detection processing, wherein the image processing device performs high-frequency enhancement processing on the noted region, based on the enhancement degree determined by the third enhancement degree determination device. 
     In an eleventh aspect, the image processing apparatus according to the tenth aspect is provided, wherein the edge detection processing is a process for determining that the edge has been detected where the number of pixels, at which a difference between each of pixels values of pixels in regions adjacent to the noted region and a typical pixel value corresponding to the noted region is greater than or equal to a predetermined threshold value, of the pixels in the regions adjacent to the noted region, is greater than or equal to a predetermined number. 
     In a twelfth aspect, the image processing apparatus according to any one of the first to eleventh aspects is provided, wherein the image is an X-ray CT image, wherein the image processing apparatus further includes fourth enhancement degree determination device which determines an enhancement degree in such a manner that a large value is acquired as the distance from the center of reconstruction of the X-ray CT image to the noted region increases, and wherein the image processing device performs high-frequency enhancement processing on the noted region, based on the enhancement degree determined by the fourth enhancement degree determination device. 
     In a thirteenth aspect, the image processing apparatus according to any one of the fifth to twelfth aspects is provided, wherein the image processing device performs high-frequency enhancement processing on the noted region in accordance with enhancement degrees obtained by performing multiplication, addition or weighted addition on a plurality of the enhancement degrees determined. 
     In a fourteenth aspect, the image processing apparatus according to any one of the first to thirteenth aspects is provided, wherein the high-frequency enhancement processing is sharpening filter processing. 
     In a fifteenth aspect, the image processing apparatus according to any one of the first to fourteenth aspects is provided, wherein the typical pixel value corresponding to the noted region is a pixel value of a central pixel in the noted region, an average value of pixel values in the noted region or both the noted region and the adjacent region thereof, or a weighted average value thereof. 
     In a sixteenth aspect, the image processing apparatus according to any one of the first to fifteenth aspects is provided, wherein each of the index values of the variances is a variance or standard deviation of pixel values in the noted region or the noted region and its adjacent region. 
     In a seventeenth aspect, a program is provided. The program is for causing a computer to function as an acquiring device which acquires a typical pixel value corresponding to a noted region in an image, a calculating device which calculates index values of variances in pixel values in the noted region or the noted region and an adjacent region thereof, a first enhancement degree determination device which determines an enhancement degree according to the acquired typical pixel value and each of the calculated index values, and an image processing device which performs high-frequency enhancement processing on the noted region, based on the enhancement degree determined by the first enhancement degree determination device. 
     In an eighteenth aspect, an image diagnostic apparatus is provided. The image diagnostic apparatus is equipped with an acquiring device which acquires a typical pixel value corresponding to a noted region in an image, a calculating device which calculates index values of variances in pixel values in the noted region or the noted region and an adjacent region thereof, a first enhancement degree determination device which determines an enhancement degree according to the acquired typical pixel value and each of the calculated index values, and an image processing device which performs high-frequency enhancement processing on the noted region, based on the enhancement degree determined by the first enhancement degree determination device. 
     In a nineteenth aspect, the image diagnostic apparatus according to the eighteenth aspect is provided, wherein X-ray CT imaging is conducted to reconstruct an image. 
     According to the aspects described above, spatial resolution can be improved with respect to a region desirous of high spatial resolution without increasing noise needlessly. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a diagram schematically showing a configuration of an X-ray CT apparatus. 
         FIG. 2  is a diagram of a gantry as viewed from its side surface. 
         FIG. 3  is a functional block diagram of a portion related to adaptive high-frequency enhancement processing in the X-ray CT apparatus. 
         FIG. 4  is a flowchart of the adaptive high-frequency enhancement processing in the X-ray CT apparatus. 
         FIG. 5  is a diagram showing one example of a first relation indicative of a correlation between a variance index value and an enhancement coefficient. 
         FIG. 6  is a diagram illustrating one example of a second relation indicative of a correlation between a typical pixel value in a noted region and an enhancement coefficient. 
         FIG. 7  shows one example of edge detection processing. 
         FIG. 8  is a diagram showing one example of a correlation between the distance from an iso-center to a noted region and an enhancement coefficient. 
         FIG. 9  is a diagram illustrating a sample image taken when the adaptive high-frequency enhancement processing is applied to an X-ray CT image of auditory ossicles. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Exemplary embodiments will be explained herein. 
       FIG. 1  is a diagram schematically showing a configuration of an X-ray CT apparatus. 
     As shown in  FIG. 1 , the present X-ray CT apparatus is equipped with a gantry  2 , a photographing table  4  and an operation console  6 . The gantry  2  has an X-ray tube  20 . X-rays (not shown) emitted from the X-ray tube  20  are formed to be an X-ray beam such as a sectorial fan beam, a cone beam or the like by means of an aperture  22  and applied to an X-ray detector  24 . 
     The X-ray detector  24  has a plurality of X-ray detecting elements arranged on a two-dimensional basis as viewed in an extending direction (channel direction) of the sectorial X-ray beam and its thickness direction (row direction). 
     A data acquisition section  26  is connected to the X-ray detector  24 . The data acquisition section  26  acquires data detected by the individual X-ray detecting elements of the X-ray detector  24  as projection data. The application of the X-rays from the X-ray tube  20  is controlled by an X-ray controller  28 . Incidentally, the relationship of connection between the X-ray tube  20  and the X-ray controller  28  is omitted from the drawing. 
     Data about a tube voltage and current supplied to the X-ray tube  20  by the X-ray controller  28  are acquired by the data acquisition section  26 . Incidentally, the relationship of connection between the X-ray controller  28  and the data acquisition section  26  is omitted from the drawing. 
     The aperture  22  is controlled by an aperture controller  30 . Incidentally, the relationship of connection between the aperture  22  and the aperture controller  30  is omitted from the drawing. 
     A rotating section  34  of the gantry  2  is equipped with components from the X-ray tube  20  to the aperture controller  30 . The rotation of the rotating section  34  is controlled by a rotation controller  36 . Incidentally, the relationship of connection between the rotating section  34  and the rotation controller  36  is omitted from the drawing. 
     The photographing table  4  carries an unillustrated subject in an X-ray irradiation space of the gantry  2  and carries the same out of the X-ray irradiation space. 
     The operation console  6  has a central processing unit  60 . The central processing unit  60  is configured by, for example, a computer or the like. A control interface  62  is connected to the central processing unit  60 . The gantry  2  and the photographing table  4  are connected to the control interface  62 . The central processing unit  60  controls the gantry  2  and the photographing table  4  through the control interface  62 . 
     The data acquisition section  26 , the X-ray controller  28 , the aperture controller  30  and the rotation controller  36  in the gantry  2  are controlled through the control interface  62 . Incidentally, the individual connections between those parts and the control interface  62  are omitted from the drawing. 
     A data acquisition buffer  64  is connected to the central processing unit  60 . The data acquisition section  26  of the gantry  2  is connected to the data acquisition buffer  64 . Data acquired by the data acquisition section  26  are inputted to the central processing unit  60  through the data acquisition buffer  64 . 
     The central processing unit  60  performs a scan planning process of an actual scan according to the operations by an operator. Also the central processing unit  60  performs image reconstruction using projection data of a plurality of views acquired through the data acquisition buffer  64 . A three-dimensional image reconstruction process or the like by, for example, a filtered back projection method is used in the image reconstruction. The operator is able to select a reconstruction function, so-called kernel used in image reconstruction according to a region or section to be observed and purposes. As the reconstruction function, a standard function, a soft part region function, a high resolution function and so on have been prepared. 
     The central processing unit  60  also performs adaptive high-frequency enhancement processing to improve spatial resolution of an X-ray CT image which is a reconstructed image. 
     A storage device  66  is connected to the central processing unit  60 . The storage device  66  stores therein various data, reconstructed images and a program or the like for implementing the function of the present X-ray CT apparatus. 
     A display device  68  and an input device  70  are respectively connected to the central processing unit  60 . The display device  68  displays the reconstructed image and other information outputted from the central processing unit  60 . The input device  70  is operated by the operator and inputs various instructions, information and the like to the central processing unit  60 . The operator interactively operates the present X-ray CT apparatus by use of the display device  68  and the input device  70 . 
       FIG. 2  is a diagram of the gantry  2  as viewed from its side surface. As shown in  FIG. 2 , an X-ray radiated from the X-ray tube  20  is shaped to be a fan-shaped X-ray beam  400  through the aperture  22  and applied to the X-ray detector  24 . The subject  8  placed on the photographing table  4  with its body axis being allowed to intersect with the sectorial plane of such an X-ray beam  400 , is carried in its corresponding X-ray irradiation space. 
     The X-ray irradiation space is shaped in space lying inside the cylindrical structure of the gantry  2 . An image of the subject  8  sliced by the X-ray beam  400  is projected onto the X-ray detector  24 . The X-ray penetrated through the subject  8  is detected by the X-ray detector  24 . The thickness th of the X-ray beam  400  applied to the subject  8  is adjusted according to the degree of opening of the aperture  22 . 
     The X-ray tube  20 , the aperture  22  and the X-ray detector  24  are rotated about the body axis of the subject  8  while maintaining the mutual relationship between them. Projection data about plural views per scan, e.g., 1000 views or so are acquired. The acquisition of the projection data is performed by a system of the X-ray detector  2 , data acquisition section  26  and data acquisition buffer  64 . 
     The central processing unit  60  performs image reconstruction of a tomographic image, based on the projection data acquired by the data acquisition buffer  64 . 
     Incidentally, the direction of the body axis of the subject  8 , i.e., the direction of conveyance of the subject  8  on the photographing table  4  is assumed to be a z direction as shown in  FIG. 2  herein. Further, the vertical direction is assumed to be a y direction, and the horizontal direction perpendicular to the y and z directions is assumed to be an x direction. 
     Thus, the adaptive high-frequency enhancement processing of the X-ray CT image will now be explained. 
       FIG. 3  is a functional block diagram of a section related to the adaptive high-frequency enhancement processing of the X-ray CT image in the X-ray CT apparatus.  FIG. 4  is a flowchart of the adaptive high-frequency enhancement processing of the X-ray CT image. 
     As shown in  FIG. 3 , the present X-ray CT apparatus is equipped with an image acquisition unit  601 , a pixel value acquisition unit  602 , a variance index value calculating unit  603 , a first enhancement coefficient determination unit  604 , a second enhancement coefficient determination unit  605 , an edge detector  606 , a third enhancement coefficient determination unit  607 , a distance measurement unit  608 , a fourth enhancement coefficient determination unit  609 , an image processor  610  and a controller  611 . 
     The first enhancement coefficient determination unit  604  is equipped with a first relation determination part  6041  and a first coefficient specifying part  6042 . The second enhancement coefficient determination unit  605  is equipped with a second relation determination part  6051  and a second coefficient specifying part  6052 . The image processor  610  is equipped with an enhancement degree determination part  6101  and a high-frequency enhancement processing part  6102 . 
     Incidentally, the already-acquired projection data are assumed to have been stored in the storage device  66 . 
     At step S 1 , the image acquisition unit  601  acquires an X-ray CT image G which is a reconstructed image. Here, the image acquisition unit  601  reads projection data P from the storage device  66  and performs image reconstruction using a reconstruction function selected by a user, based on the read projection data P to thereby acquire the corresponding X-ray CT image. As the reconstruction function, there are considered a plurality of types of reconstruction functions different in balance between spatial resolution and a noise level in the reconstructed image. As the reconstruction function, there are mentioned, for example, a lung field function close to high spatial resolution, a soft part function close to a low noise level, a standard function having an intermediate property between these, etc. 
     At step S 2 , the controller  611  sets a noted region including one or plural pixels in the X-ray CT image G, and the pixel value acquisition unit  602  acquires a typical pixel value C corresponding to the noted region. 
     It is possible to roughly discriminate whether the noted region is any tissue of air, lung, mediastinal space/liver, bone/contrasted blood vessels, etc., based on the typical pixel value C corresponding to the noted region. 
     As the typical pixel value C corresponding to the noted region, there are considered, for example, a pixel value of a central pixel in the noted region, an average value of pixel values in the noted region or both the noted region and its adjacent region or a weighted average value thereof, etc. Herein, the noted region is assumed to be a region corresponding to one pixel. This will be called a noted pixel. The typical pixel value corresponding to the noted region is assumed to be the average value of pixel values at the noted pixel and eight adjacent pixels lying orthogonally through the length and breadth of the noted pixel. Thus, information about each pixel value related to a section indicated by the noted region can be obtained while suppressing the effect of noise. 
     At step S 3 , the variance index value calculating unit  603  calculates an index value (hereinafter called a variance index value V) indicative of the degree of variance in the pixel values at the noted region and its adjacent region. 
     It is possible to recognize the fineness of the structure of the noted region, its noise level, etc., based on the variance index value V. For example, it is possible to roughly grasp whether the noted region is any of (1) a soft part region of mediastinal space/liver or the like, (2) an artifact such as streak or the like and (3) so-called high-contrast region of lung/bone/contrasted blood vessels or the like. 
     As the variance index value V, there can be considered, for example, a variance or standard deviation of pixel values in the noted region or the noted region and its adjacent region, etc. Here, the variance index value V is assumed to be a standard deviation of pixel values at a predetermined matrix region centering on a noted pixel, for example, a region of 5×5 pixels. 
     At step S 4 , the first relation determination part  6041  determines a first relation T 1  indicative of a relationship between a variance index value V and an enhancement coefficient H 1 , based on the typical pixel value C acquired at step S 2 . Incidentally, details on the first relation T 1  and its determination method will be described later. 
     At step S 5 , the first coefficient specifying part  6042  specifies an enhancement coefficient H 1  corresponding to the variance index value V calculated at step S 3 , by referring to the first relation T 1  determined at step S 4 . 
     Here, the term enhancement coefficient is a coefficient used to determine or fix up the degree of enhancement of high-frequency enhancement processing performed on the noted region. The enhancement coefficient acts so as to relatively increase the degree of enhancement as the value thereof becomes large, and acts so as to relatively decrease the degree of enhancement as the value thereof becomes small. 
     Incidentally, as the method for determining the first relation T 1 , there is considered, for example, a method for dividing values each taken as the typical pixel value C corresponding to the noted region into a plurality of ranges, storing candidates for the first relation T 1  in correspondence with one another every range and specifying the first relation T 1  which is a candidate corresponding to the typical pixel value C acquired at step S 2 . For example, a predetermined function is prepared in which the typical pixel value C corresponding to the noted region is defined as a parameter. Then the typical pixel value C acquired at step S 2  may be input to the predetermined function so as to derive the first function T 1  therefrom. 
     One example of the first relation is shown in  FIG. 5 . 
     When the variance index value V is within a first range R 1  relatively low in the variance index value V in the first relation T 1  according to this example as shown in  FIG. 5 , there is a high possibility that the noted region will be on a structure near a flat. Therefore, an improvement in spatial resolution and noise suppression are balanced to share equally, so that the enhancement coefficient H 1  is brought to 0.5 or so (first enhancement coefficient) corresponding to an intermediate level. When the variance index value V is within a second range R 2  middle in the variance index value V, there is a high possibility that the noted region will be on a streak artifact. Therefore, the enhancement coefficient H 1  is lowered to near zero indicative of the minimum level (second enhancement coefficient) so as to prevent the artifact from being enhanced. When the variance index value V is within a third range R 3  relatively high in the variance index value V, there is a high possibility that the noted region will be on a fine structure. Therefore, the enhancement coefficient H 1  is raised to near 1 indicative of the maximum level (third enhancement coefficient) in such a manner that the structure can be grasped. 
     That is, the variance index value V included in the first range R 1  and the first enhancement coefficient are associated with each other. Also, the variance index value V included in the second range R 2  larger in value than the first range R 1 , and the second enhancement coefficient smaller than the first enhancement coefficient correspond to each other. Further, the variance index value V included in the third range R 3  larger in value than the second range R 2 , and the third enhancement coefficient larger than the second enhancement coefficient correspond to each other. 
     Incidentally, now consider a balance between spatial resolution required for each region of a reconstructed image and noise. 
     The balance between the spatial resolution required for each region of the reconstructed image and the noise differs depending on the type of section in each region even if variances in pixel values are the same degree. For example, the noise suppression is relatively given priority in the soft part region, whereas the high spatial resolution is relatively given priority in the bone region. 
     In the present example, the first relation T 1  is determined based on the typical pixel value C corresponding to the noted region. Therefore, the type of section in the noted region can be predicted a little from the typical pixel value C corresponding to the noted region. Such an enhancement coefficient H 1  that the balance between the spatial resolution and noise suitable for the noted region is obtained can be derived from the degree of variances in pixel values in the neighborhood of the noted region in the form suitable for the predicted section. 
     Thus, the balance between the spatial resolution and noise suitable for the noted region can meet a complicated and delicate request that occurs due to the combination of the type of section and the variances in pixel values. 
     At step S 6 , the second relation determination part  6051  determines a second relation T 2  indicative of the relationship between the typical pixel value C and enhancement coefficient H 2  corresponding to the noted region according to a reconstruction function used in the image reconstruction. 
     At step S 7 , the second coefficient specifying part  6052  specifies an enhancement coefficient H 2  corresponding to the typical pixel value C acquired at step S 2  by referring to the second relation T 2  determined at step S 6 . 
     Incidentally, as the method of determining the second relation T 2 , there can be considered, for example, a method of storing candidates for the second relation T 2  in correspondence with one another respectively every type of reconstruction function and specifying the second relation T 2  that is a candidate corresponding to a reconstruction function actually used in the image reconstruction of the X-ray CT image G. 
     One example of the second relation is shown in  FIG. 6 . 
     When the typical pixel value C corresponding to the noted region is within a fourth range R 4  smallest in the value in the second relation T 2  according to this example as shown in  FIG. 6 , there is a high possibility that the noted region will be air. Therefore, the enhancement coefficient H 2  is lowered to near 0 corresponding to the minimum level (fourth enhancement coefficient) so as to prevent noise from increasing. When the typical pixel value C corresponding to the noted region is within a fifth range R 5  small in the value next, there is a high possibility that the noted region will be a lung. Therefore, the enhancement coefficient H 2  is raised up to near  1  corresponding to the maximum level (fifth enhancement coefficient) in such a manner that micro points of calcification or the like can be grasped. When the typical pixel value C corresponding to the noted region is within a sixth range R 6  small in the value next, there is a high possibility that the noted region will be mediastinal space, liver or the like. Therefore, the enhancement coefficient H 2  is lowered to near 0 corresponding to the minimum level (sixth enhancement coefficient) so as to prevent noise from increasing. When the typical pixel value C corresponding to the noted region is within a seventh range R 7  small in the value next, there is a high possibility that the noted region will be bones, contrasted blood vessels or the like. Therefore, the enhancement coefficient H 2  is raised up to near 1 corresponding to the maximum level (seventh enhancement coefficient) in such a manner that a fine structure such as auditory ossicles, calcification in blood vessels or the like can be grasped. 
     That is, the pixel value included in the fourth range R 4  and the fourth enhancement coefficient correspond to each other. The pixel value included in the fifth range R 5  larger in pixel value than the fourth range R 4  and the fifth enhancement coefficient larger than the fourth enhancement coefficient are associated with each other. The pixel value included in the sixth range R 6  larger than the fifth range R 5  in pixel value, and the sixth enhancement coefficient smaller than the fifth enhancement coefficient correspond to each other. The pixel value included in the seventh range R 7  larger than the sixth range R 6  in pixel value, and the seventh enhancement coefficient larger than the sixth enhancement coefficient correspond to each other. 
     Incidentally, the states of the spatial resolution and noise in the reconstructed image differ greatly according to the reconstruction function used in the image reconstruction. Since the second relation T 2  is changed depending on the reconstruction function used in the image reconstruction in the present example, the second relation T 2  to be referred can be determined in consideration of the difference in the state therebetween. 
     At step S 8 , the edge detector  606  performs edge detection processing in the noted region and its adjacent region. 
     At step S 9 , the third enhancement coefficient determination unit  607  determines an enhancement coefficient H 3  in such a manner that its value becomes larger where no edge is detected rather than where the edge is detected by the edge detection processing. 
     It is thus possible to derive the enhancement coefficient H 3  capable of preventing the occurrence of overshoot or undershoot due to the excessive enhancement of an edge portion at which the pixel value changes suddenly. 
     One example of the edge detection processing is shown in  FIG. 7 . As the edge detection processing, there is considered as shown in  FIG. 7 , for example, a process for, when a change in pixel value in a predetermined direction is viewed in a predetermined matrix region centering on a noted pixel, e.g., a region of 5×5 pixels, determining an edge to have been detected if the difference in pixel value between adjacent pixels is greater than or equal to a predetermined threshold value. There is considered, for example, a process for determining an edge to have been detected when the number of pixels, at which the difference in pixel value with respect to the noted pixel is greater than or equal to the predetermined threshold value, of the pixels included in the predetermined matrix region centering on the noted pixel is greater than or equal to a predetermined number. 
     At step S 10 , the distance measurement unit  608  measures a distance D from the reconstruction center, i.e., iso-center in the reconstructed image to the noted region. 
     At step S 11 , the fourth enhancement coefficient determination unit  609  determines an enhancement coefficient H 4  in such a manner that its value becomes large as the distance D measured at step S 10  increases. 
     One example of the relationship between the distance D from the iso-center to the noted region and the enhancement coefficient H 4  is shown in  FIG. 8 . In this example, the enhancement coefficient H 4  is 0 in a range in which the distance D is from 0 cm to 20 cm. The enhancement coefficient H 4  increases gradually in a range in which the distance D is from 20 cm to 45 cm. The enhancement coefficient H 4  becomes 1 when the distance D is greater than 45 cm. 
     It is known that the spatial resolution becomes low with distance from the iso-center in the X-ray CT image corresponding to the reconstructed image. It is thus possible to derive an enhancement coefficient capable of suppressing a reduction in the spatial resolution at the peripheral portion of the reconstructed image. 
     At step S 12 , the enhancement degree determination part  6101  performs multiplication, addition or weighted addition or the like on all the determined enhancement coefficients H 1  through H 4  to thereby determine an enhancement degree HA. 
     At step S 13 , high-frequency enhancement processing is performed on the noted region, based on the enhancement degree HA determined at step S 12 . 
     As the high-frequency enhancement processing, there can be considered, for example, sharpening filter processing using a weighted coefficient matrix, which is known to date. 
     Thus, the high-frequency enhancement processing on which the effect of correcting the spatial resolution and noise held in each enhancement coefficient is reflected is performed on the noted region. 
     At step S 14 , the controller  613  determines whether or not a region to be set as the noted region lies elsewhere. If it exists elsewhere, the flowchart returns to step S 2 , where a new noted region is set and the processing is continued. If it does not exist elsewhere, the processing is terminated. 
       FIG. 9  shows a sample image taken when the adaptive high-frequency enhancement processing is applied to an X-ray CT image of auditory ossicles. The left image is an original image G, the central image is a processed image G′, and the right image is a difference image (G′-G) between the processed image and the original image. In the processed image G′, the enhancement of high-frequency components is sufficiently performed on a high contrast region for the bones so that high spatial resolution is obtained. It is however found that the enhancement of high-frequency components is hardly performed on a soft part region and a region having a relatively flat structure of a bone part and hence an increase in noise is suppressed. 
     According to the embodiments described herein, the enhancement degree of the high-frequency enhancement processing performed on the noted region can be changed according to the combined condition of both the pixel value related to the noted region and the degree of variance in the pixel value. 
     Therefore, the type of section in the noted region and the state of its structure can first be discriminated in pieces. For example, the fine discrimination of a fine structure of each of the soft part region and the bone/contrasted blood vessels, a structure relatively flat, a structure like an artifact, etc. can be performed on the noted region in addition to the discrimination of air, lungs and the like. 
     It is possible to perform the high-frequency enhancement processing on the noted region with the suitable enhancement degree corresponding to the result of discrimination. For example, when it is considered that the noted region is a bone region judging from each pixel value but has a relatively flat structure judging from the degree of variances in pixel values, it is possible to suppress an increase in noise without the enhancement of the high-frequency components. Further, for example, even when the degree of variances in pixel values in a region considered to be an artifact changes depending on the type of substance or section, it is also possible to accurately determine whether the noted region is an artifact region and suppress an increase in noise without the enhancement of each high-frequency component if it is found to be the artifact region. 
     As a result, it is possible to suppress an increase in unnecessary noise without the enhancement of each high-frequency component with respect to a region in which noise suppression should be given priority and, in the mean time, to improve spatial resolution while enhancing each high-frequency component with respect to a region really desirous of high spatial resolution. 
     The embodiments described herein enable a delicate correction that cannot be obtained by the conventional method. For example, even if an enhancement coefficient determined according to only a pixel value and an enhancement coefficient determined according to only a variance index value of a pixel value are combined together to generate a new enhancement coefficient, enhancement coefficients respectively determined in another aspect may repel each other. It is difficult to perform such a delicate correction as described above. 
     Incidentally, the present invention is not limited to the embodiments specifically described herein, but may be added and modified in various ways within the scope not departing from the gist thereof. 
     For example, the combination and order of the processes for determining the enhancement coefficient are not limited to the embodiments described herein. A process based on several aspects may be omitted, a process based on another aspect may be added, and the order may be changed. The concrete contents of the process for determining the enhancement coefficient are not limited to the embodiments described herein. 
     Although in the embodiments described herein, for example, the respective enhancement coefficients are integrated to determine one enhancement degree, and the high-frequency enhancement processing is performed based on the enhancement degree, the high-frequency enhancement processing based on the enhancement coefficients may sequentially be performed for every enhancement coefficient. 
     An image processing apparatus having a functional block related to the above image processing, a program for causing a computer to function as such an image processing apparatus, and another image diagnostic apparatus equipped with such an image processing apparatus are merely exemplary. The image diagnostic could include, for example, a PET-CT apparatus, an Angio-CT apparatus, radiation therapy equipment with a CT function, etc.