JP5442530B2 - Image processing apparatus, image display apparatus, program, and X-ray CT apparatus - Google Patents

Description

The present invention relates to an image processing apparatus that processes an image based on projection data obtained by dual energy imaging, an image display apparatus that displays an image based on the projection data, and a program (program) therefor ), And X-ray CT (Computed) equipped with these devices
Tomography).

  Based on projection data (data) obtained by dual energy imaging using an X-ray CT apparatus, a monochromatic image corresponding to an image captured using monochromatic X-rays having any effective X-ray energy is obtained. A method for reconfiguration is known (see, for example, Patent Document 1, Abstract, Patent Document 2, FIGS. 4 to 5, etc.). According to this method, an image of desired effective X-ray energy can be obtained in a short time as much as necessary without additional exposure to the imaging target.

US2009 / 0052612A1 JP 2009-1553829 A

  Taking advantage of the features of the above method, for example, an image display apparatus capable of supporting image diagnosis as described below can be considered.

  First, projection data collected by dual energy imaging of an imaging target is received, a predetermined image is reconstructed based on the projection data, and displayed on a monitor. Next, the operator designates a predetermined image area of interest on the displayed predetermined image, and sets the image area as the area of interest. A monochrome image of the region of interest is determined for a plurality of effective X-ray energies. Then, the relationship between the value of the effective X-ray energy and the representative pixel value of the region of interest in the monochrome image of the effective X-ray energy, that is, the X-ray absorption characteristic with respect to the X-ray energy of the region of interest is imaged and displayed.

  Since the X-ray absorption characteristics of a substance vary depending on the type of the substance, the composition of the substance in the region of interest can be specified based on the X-ray absorption characteristics. Accordingly, in this image display device, the operator can know the X-ray absorption characteristics of a part of an image that is suspected to be a lesion such as a tumor on the displayed predetermined image. It is possible to determine whether or not the site is a true lesion.

  However, in such an image display device, when there are a plurality of image regions suspected to be lesions on the predetermined image, such image regions are designated as regions of interest one by one and X-ray absorption is performed. The characteristics must be confirmed. Therefore, it is particularly unsuitable for detection of multiple tumors and plaque analysis, and it may be possible to overlook the lesion.

  Under such circumstances, an image processing apparatus and an image display apparatus that can extract an image region corresponding to a desired substance, for example, a substance that is the same as or similar to a substance of a set region of interest, on a CT image to be imaged , And programs for them, and X-ray CT apparatuses equipped with these devices are desired.

  The first aspect of the invention is the first projection data collected by the dual energy imaging of the imaging target, and the second projection by the second X-ray having energy different from the first X-ray. X-rays having a desired effective X-ray energy are obtained by reconstructing means for reconstructing a predetermined image based on at least one of the projection data, and by a predetermined calculation based on the first and second projection data. A calculation unit that calculates a pixel value of a desired pixel in a monochrome image corresponding to an image obtained by imaging, and a plurality of effective X-ray energies calculated by the calculation unit for each image region in the predetermined image; The effective X-ray energy and the effective X-ray energy in the monochrome image based on the pixel value of the image area in the monochrome image of An acquisition unit that acquires a relationship between a representative pixel value of an image region, and a relationship acquired by the acquisition unit among the image regions is an effective X-ray energy and a monochromatic image of the effective X-ray energy. An image processing apparatus is provided that includes specifying means for specifying an image region similar to a relationship with a pixel value corresponding to a predetermined substance.

  The invention according to a second aspect provides the image processing apparatus according to the first aspect, wherein the plurality of effective X-ray energies are three or more effective X-ray energies.

  The third aspect of the invention is the first projection data collected by the dual energy imaging of the imaging object and the second projection data by the first X-ray and the second X-ray by the energy different from the first X-ray. X-rays having a desired effective X-ray energy are obtained by reconstructing means for reconstructing a predetermined image based on at least one of the projection data, and by a predetermined calculation based on the first and second projection data. A calculation unit that calculates a pixel value of a desired pixel in a monochrome image corresponding to an image obtained by shooting, a setting unit that sets a region of interest in the predetermined image, and the region of interest in the predetermined image , The effective X-ray energy based on the pixel value of the region of interest in the monochrome image of the plurality of effective X-ray energies calculated by the calculating means A first acquisition means for acquiring a relationship between a representative pixel value of the region of interest in the monochrome image of the effective X-ray energy and a predetermined value in the monochrome image of the effective X-ray energy and the effective X-ray energy; Storage means for storing a relationship with a pixel value corresponding to a substance for one or more substances, detection means for detecting a relation similar to the acquired relation among the stored relations, For each image region different from the region of interest in a predetermined image, the effective X-ray energy and the effective X-ray energy are calculated based on the pixel values of the image region in a plurality of effective X-ray energy monochrome images calculated by the calculating unit. Second acquisition means for acquiring a relationship with a representative pixel value of the image area in a monochrome image of X-ray energy; Of the image areas, a specifying means for specifying an image area whose relationship acquired by the second acquiring means is similar to the detected relationship, and the predetermined image in which the specified image area is emphasized are displayed. There is provided an image display device comprising display means for performing the above operation.

  The invention according to a fourth aspect provides the image display device according to the third aspect, wherein the plurality of effective X-ray energies are three or more effective X-ray energies.

  According to a fifth aspect of the invention, the detection means is configured to change a pixel value with respect to at least one effective X-ray energy segmented area in the relation acquired by the second acquisition means and the stored relation. The image display apparatus according to the third aspect or the fourth aspect of the invention detects the similar relationship based on the above.

  The invention according to a sixth aspect provides the image display device according to the fifth aspect, wherein the detecting means detects the similar relationship based on a change amount of a pixel value with respect to a plurality of effective X-ray energy divided regions. To do.

  The invention according to a seventh aspect provides the image display device according to the third to sixth aspects, wherein the display means colors and displays the specified image region.

  The invention according to an eighth aspect provides the image display device according to the seventh aspect, wherein the color to be colored is a color associated with the detected relationship.

  The invention according to a ninth aspect is the eighth to eighth aspects, wherein the one or more substances include iodine, calcium, fat, water, or a mixed substance containing at least one of these. An image display device according to any one of the above aspects is provided.

  The invention according to the tenth aspect is the first projection data collected by the dual energy imaging of the imaging target and the second projection by the second X-ray having energy different from the first X-ray. X-rays having a desired effective X-ray energy are obtained by reconstructing means for reconstructing a predetermined image based on at least one of the projection data, and by a predetermined calculation based on the first and second projection data. A calculation unit that calculates a pixel value of a desired pixel in a monochrome image corresponding to an image obtained by shooting, a setting unit that sets a region of interest in the predetermined image, and the region of interest in the predetermined image Based on the pixel values of the region of interest in the monochrome image having a plurality of effective X-ray energies calculated by the calculating means, A first obtaining means for obtaining a relationship between the pixel value of the region of interest in the monochrome image of effective X-ray energy, and each image region different from the region of interest in the predetermined image, Based on the pixel values of the image area in a plurality of effective X-ray energy monochrome images calculated by the calculating means, the effective X-ray energy and a representative of the image area in the effective X-ray energy monochrome image. A second acquisition unit that acquires a relationship with a pixel value; and an image region in which the relationship acquired by the second acquisition unit is similar to the relationship acquired by the first acquisition unit among the image regions There is provided an image display device comprising: a specifying unit for specifying the image; and a display unit for displaying the predetermined image in which the specified image region is emphasized. .

  The eleventh aspect of the invention provides the image display apparatus according to the tenth aspect, wherein the plurality of effective X-ray energies are three or more effective X-ray energies.

  According to a twelfth aspect of the present invention, in the pixel value for at least one effective X-ray energy segmented region in the relationship acquired by the first acquisition unit and the relationship acquired by the second acquisition unit The image display device according to the tenth aspect or the eleventh aspect is provided that specifies the similar image region based on a change amount of the image.

  The invention according to a thirteenth aspect is the image display apparatus according to the twelfth aspect, wherein the specifying unit specifies the similar image region based on a change amount of a pixel value with respect to a plurality of divided regions of effective X-ray energy. provide.

  The fourteenth aspect of the invention provides the image display device according to any one of the tenth to thirteenth aspects, wherein the display means colors and displays the specified image area.

  According to a fifteenth aspect of the present invention, the specified image area is determined in accordance with the substance density of the image area obtained by the display means based on the relationship acquired for the specified image area. The image display device according to the seventh aspect, the eighth aspect or the fourteenth aspect is provided.

  In a sixteenth aspect of the invention, the region of interest is a region of a plurality of pixels, and a representative pixel value of the region of interest is an average value or a weighted average value of the pixel values of the plurality of pixels. An image display device according to any one of the fifteenth aspects from a viewpoint is provided.

  According to a seventeenth aspect of the present invention, each of the image areas is a single pixel area, and the representative pixel value of the image area is a single pixel value corresponding to the image area. An image display apparatus according to any one of the sixteenth aspects is provided.

  According to an eighteenth aspect of the present invention, each of the image regions is a region of a plurality of pixels, and a representative pixel value of the image region is an average value or a weighted average value of pixel values of the plurality of pixels corresponding to the image region. An image display device according to any one of the third to sixteenth aspects is provided.

  The invention of the nineteenth aspect provides a program for causing a computer to function as a device according to any one of the first to eighteenth aspects.

  According to a twentieth aspect of the invention, there is provided an X-ray CT apparatus comprising: an imaging unit that performs the dual energy imaging; and the apparatus according to any one of the first to eighteenth aspects.

  In the invention of the above aspect, as the “predetermined image”, for example, a tube voltage image, a substance density image, a monochrome image, and the like can be considered. The “photographing target” includes a human body and an object.

  Moreover, the invention of the above viewpoint is not limited to medical use and can be applied to industrial use and the like.

  According to the invention of the above aspect, with the above configuration, for each image region in the predetermined image to be imaged, the relationship between the effective X-ray energy and the pixel value in the monochrome image of the effective X-ray energy is acquired, and An image area whose relationship is similar to the relationship related to a predetermined substance can be specified among the image areas, and is the same as or similar to a desired substance, for example, a substance of a set region of interest on the CT image to be imaged. An image region corresponding to the substance can be extracted.

It is a figure which shows the structure of the X-ray CT apparatus by 1st embodiment. It is a mechanism block (block) figure of the part regarding the image display of the X-ray CT apparatus of 1st embodiment. It is a figure which shows roughly the process of reconstructing a tube voltage image, a material density image, and a monochrome image in steps. It is a figure which shows an example of the reference image displayed. It is a figure which shows an example of the reference image in which the region of interest was set. It is a figure which shows notionally a spectral HU curve (spectralHU curve) acquisition process. It is a figure which shows an example of the spectral HU curve of a region of interest. It is a figure which shows an example of the spectral HU curve of each substance. It is a flowchart which shows the flow of a similar curve detection process. It is a figure which shows a similar curve detection process notionally. It is a figure which shows an example of the reference image by which the similar area | region where a spectral HU curve is similar to a region of interest was specified. It is a figure which shows an example of the reference image by which the region of interest and the similar region were colored and displayed. It is a flow figure showing the flow of processing in the X-ray CT apparatus of a first embodiment. It is a functional block diagram of the part regarding the image display of the X-ray CT apparatus of 2nd embodiment.

  Embodiments of the invention will be described below.

(First embodiment)
FIG. 1 is a diagram schematically showing the configuration of the X-ray CT apparatus of the first embodiment.

  The X-ray CT apparatus 100 includes an operation console 1, an imaging table (imaging means) 10, and a scanning gantry (imaging means) 20.

  The operation console 1 includes an input device 2 that receives input from an operator, a central processing unit 3 that performs control of various units for scanning a subject (imaging target) 40, various calculations, and the like, and a scanning gantry 20. The data acquisition buffer (buffer) 5 which collects the data acquired by (1), the monitor 6 which displays an image, and the memory | storage device 7 which memorize | stores a program, data, etc. are provided.

  The imaging table 10 includes a cradle 12 on which the subject 40 is placed and carried into and out of the opening B of the scanning gantry 20. The cradle 12 is moved up and down and horizontally moved by a motor built in the imaging table 10. Here, the body axis direction of the subject 40, that is, the horizontal linear movement direction of the cradle 12 is the z direction, the vertical direction is the y direction, and the horizontal direction perpendicular to the z direction and the y direction is the x direction.

  The scanning gantry 20 includes a rotating unit 15 and a support unit 16 that rotatably supports the rotating unit 15. The rotating unit 15 includes an X-ray tube 21, an X-ray controller 22 that controls the X-ray tube 21, and a collimator 23 that collimates the X-rays 81 generated from the X-ray tube 21. An X-ray detector 24 that detects X-rays 81 irradiated from the X-ray tube 21 and transmitted through the subject 40, and a data acquisition device (DAS;) that converts and collects the output of the X-ray detector 24 into projection data. Data Acquisition System) 25 and a rotating unit controller 26 for controlling the X-ray controller 22, the collimator 23, and the DAS 25 are mounted. The X-ray detector 24 is a multi-row detector in which, for example, 256 detector rows are arranged in the z direction. The support unit 16 includes a control controller 29 that communicates control signals and the like with the operation console 1 and the imaging table 10. The rotating part 15 and the support part 16 are electrically connected via a slip ring 30.

  FIG. 2 is a functional block diagram of a portion related to image display in the X-ray CT apparatus of the first embodiment.

  The X-ray CT apparatus 100 includes a dual energy imaging control unit 51 (imaging unit), an image reconstruction unit (reconstruction unit and calculation unit) 52, a display control unit (display unit) 53, and a region of interest setting unit (setting unit) 54. Spectral HU curve acquisition unit (first and second acquisition unit) 55, Spectral HU curve storage unit (storage unit) 56, similar curve detection unit (detection unit) 57, and similar region specification unit (specification unit) 58 I have.

  The dual energy imaging control unit 51 controls the imaging table 10 and the scanning gantry 20, performs dual energy imaging on the subject 40, and collects projection data. For example, scanning is performed while alternately switching the X-ray tube voltage between a relatively high first tube voltage HV and a relatively low second tube voltage LV in units of one view or several views. Collect projection data for the viewing angle. Alternatively, scanning is performed with the X-ray tube voltage set to the first tube voltage HV, projection data for a predetermined view angle is collected, the X-ray tube voltage is switched to the second tube voltage LV, and scanning is performed. Projection data for a predetermined view angle is collected. As a result, the first projection data PHV based on the X-ray having the first tube voltage HV and the second projection data PLV based on the X-ray having the second tube voltage LV are collected.

  In this example, the first and second tube voltages HV and LV are 140 [kV] and 80 [kV], respectively. Further, the predetermined view angle is set to the fan angle α [rad] or 2π [rad] of the π + X-ray beam.

  The image reconstruction unit 52 reconstructs a tube voltage image, a material density image, and a monochromatic image based on the first and second projection data PHV and PLV.

  The tube voltage image is a tomographic image obtained when X-ray CT imaging of the subject 40 is performed using X-rays when the X-ray tube voltage is a predetermined tube voltage. For example, projection data is filtered. It is obtained by back projection processing. The substance density image is a tomographic image representing the density distribution of a predetermined substance in the subject 40 and is obtained, for example, by performing weighted subtraction processing on two types of tube voltage images. A monochromatic image is an image corresponding to an image photographed by monochromatic X-rays having a predetermined effective X-ray energy, and is obtained, for example, by weighted addition processing of two types of substance density images.

  These images are reconstructed as images having a resolution of, for example, 256 × 256 pixels. Moreover, in this example, the tube voltage image by the 1st tube voltage HV and the tube voltage image by the 2nd tube voltage LV are reconstructed as a tube voltage image. Further, the water density image Gw and the iodine density image Gio are reconstructed as the material density image.

  An example of reconstruction processing by the image reconstruction unit 52 is shown below.

  FIG. 3 is a diagram schematically showing a process of reconstructing a tube voltage image, a material density image, and a monochrome image in a stepwise manner.

  As shown in FIG. 3, the image reconstruction unit 52 uses the first and second projection data PHV and PLV, and the first tube voltage image representing the subject 40 photographed with the first tube voltage HV. The GHV and the second tube voltage image GLV representing the subject 40 imaged by the second tube voltage LV are reconstructed. Specifically, first, predetermined pre-processing including logarithmic conversion, correction of radiation quality, correction of sensitivity of the X-ray detector, and the like is performed on the first and second projection data PHV and PLV. Next, a predetermined reconstruction function is superimposed on the preprocessed first and second projection data PHV and PLV. The first and second projection data PHV and PLV on which the reconstruction function is superimposed are respectively backprojected to obtain first and second tube voltage images GHV and GLV.

  Next, the image reconstructing unit 52 performs a weighted subtraction process on the first tube voltage image GHV and the second tube voltage image GLV so as to strongly express the density distribution of the first substance in the subject 40. A substance density image and a second substance density image that strongly represents the density distribution of the second substance in the subject 40 are obtained. Here, as an example, the first substance is water and the second substance is iodine, and a water density image Gw representing the density distribution of water and an iodine density image Gio representing the density distribution of iodine are obtained.

  The projection data of the subject or an image reconstructed based on the projection data can be approximately expressed by the density distributions of two different types of substances and their X-ray absorption coefficients. Based on this approximate model, first and second material density images can be obtained. That is, the first material is obtained by performing weighted subtraction processing on the first tube voltage image GHV and the second tube voltage image GLV so that the pixel value of the pixel corresponding to the water that is the first material becomes zero. As a second substance density image, an iodine density image Gio that strongly suppresses the density component of the water and suppresses the density distribution of iodine as the second substance. Similarly, the first tube voltage image GHV and the second tube voltage image GLV are subjected to weighted subtraction processing so that the pixel value of the pixel corresponding to iodine as the second substance becomes zero, thereby obtaining the second tube voltage image GHV. A component of iodine which is a substance is suppressed, and a water density image Gw which strongly represents the density distribution of water which is the first substance is obtained as the first substance density image.

  Note that the pixel values corresponding to the first and second substances in the first and second tube voltage images GHV and GLV, respectively, can be estimated from the imaging conditions of dual energy imaging. Therefore, the weight to be used for the weighted subtraction process can be specified from the ratio of these estimated pixel values.

  The water density image Gw and the iodine density image Gio can be obtained, for example, by performing a weighted subtraction process according to the following formula.

  Here, kw is a conversion coefficient for expressing the pixel value Gw (x, y) of the water density image in terms of water density [mg / ml], and kio is the pixel value Gio (x, y) of the iodine density image. Conversion coefficient for expressing density [mg / ml], rio is the dual energy ratio of iodine in the first tube voltage HV and the second tube voltage LV, rw is the first tube voltage HV and the second tube voltage It is the dual energy ratio of water in LV.

  In Equation 1 representing the weighted subtraction process for obtaining the water density image Gw, the weighting coefficient to be multiplied by the pixel value GLV (x, y) of the second tube voltage image is kw, and the pixel of the first tube voltage image The weighting factor by which the value GHV (x, y) is multiplied is kW · rio. Further, in Equation 2 representing the weighted subtraction process for obtaining the iodine density image Gio, the weight coefficient to be multiplied by the pixel value GLV (x, y) of the second tube voltage image is kio, and the first tube voltage image. The weighting coefficient by which the pixel value of GHV (x, y) is multiplied is kio · rw.

  The dual energy ratio rio is a pixel value (CT value) GCio, LV (x, y) corresponding to iodine on the image GCLV (x, y) obtained when the X-ray is taken with the second tube voltage LV. ) Is divided by the pixel value GCio, HV corresponding to iodine on the image GCHV (x, y) obtained when X-rays are taken with the first tube voltage HV (CT value ratio) It is. Further, the dual energy ratio rw is obtained by converting the pixel value GCw, LV (x, y) corresponding to the water on the image GCLV (x, y) to the pixel value GCw, LV corresponding to the water on the image GCHV (x, y). A value obtained by dividing by HV (x, y).

  Next, as shown in FIG. 3, the water density image Gw and the iodine density image Gio are subjected to weighted addition processing, and a monochrome image corresponding to an image photographed using monochromatic X-rays having a predetermined effective X-ray energy. Get Gm.

  The monochromatic image Gm can be obtained, for example, by performing a weighted addition process according to the following formula.

  Here, E1 is the effective X-ray energy, μw (E1) is the X-ray absorption coefficient of water with respect to the X-ray with the effective X-ray energy E1, and μio (E1) is the X-ray absorption of iodine with respect to the X-ray with the effective X-ray energy E1. The coefficient kc is a conversion coefficient for converting a pixel value into a CT value. As is well known, the CT value is a value indicating the degree of X-ray absorption of a substance, the CT value of air is represented by -1000 [HU], and the CT value of water is represented by 0 [HU].

  In Equation 5 representing the weighted addition process for obtaining the monochrome image Gm, the weighting coefficient to be multiplied to the water density image Gw is kc · μw (E1), and the weighting factor to be multiplied to the iodine density image Gio is kc · μio ( E1).

  By the way, in the above method, the first and second projection data are respectively subjected to image reconstruction processing to obtain two types of images, and these two types of images are subjected to weighted subtraction processing using different first and second weights. Thus, first and second substance density images are obtained. However, the first and second projection data are subjected to weighted subtraction with different first and second weights to obtain two types of projection data, and these two types of projection data are respectively subjected to image reconstruction processing, First and second material density images can also be obtained.

  Further, the weighted subtraction process and the weighted addition process are not limited to the linear linear weighted subtraction process and the linear linear weighted addition process, and a high-order linear weighted subtraction process, a high-order linear weighted addition process, and the like can also be used.

  The image reconstruction unit 52 can reconstruct a monochromatic image having a desired effective X-ray energy by adjusting the weighting in the weighted addition process of the first and second material density images. In addition, the image reconstruction unit 52 performs weighted addition processing with a predetermined weight, for example, the pixel value of a desired pixel in the first substance density image and the pixel value of the same pixel in the second substance density image, Only the pixel value of a desired pixel in a monochrome image having a desired effective X-ray energy can be calculated.

  For details of the reconstruction process of the monochrome image Gm, refer to, for example, US Patent Document US2009 / 0052612A1.

  The display control unit 53 controls the monitor 6 to display a predetermined image reconstructed by the image reconstruction unit 52, that is, a tube voltage image, a material density image, or a monochrome image as a predetermined reference image Gr. In this example, a monochrome image having a predetermined effective X-ray energy is displayed as the reference image Gr. FIG. 4 is a diagram illustrating an example of the displayed reference image Gr.

  The region-of-interest setting unit 54 sets the region of interest ROI on the reference image Gr displayed on the monitor 6 according to the operation of the operator. The region of interest ROI can be a circular shape, a rectangular shape, or the like, but in this example, it is a circular shape. FIG. 5 is a diagram illustrating an example of the reference image Gr in which the region of interest ROI is set.

  The spectral HU curve acquisition unit 55 acquires the spectral HU curve CROI of the region of interest ROI set by the region of interest setting unit 54. A spectral HU curve is a graph showing the relationship between the value of effective X-ray energy and a representative pixel value (CT value) of a predetermined substance or a predetermined image area in a monochrome image of the effective X-ray energy. It is. Note that the acquisition of the spectral HU curve does not require obtaining an actual curve, but includes acquiring information that can identify the curve.

  An example of a spectral HU curve acquisition process by the spectral HU curve acquisition unit 55 is shown below.

  FIG. 6 is a diagram conceptually showing the spectral HU curve acquisition process.

  First, by using the image reconstruction unit 52, a portion corresponding to the region of interest ROI of the water density image Gw and a portion corresponding to the region of interest ROI of the iodine density image Gio are weighted and added by a predetermined weight, A monochrome image Gm, ROI, E1 of the region of interest ROI with the effective X-ray energy E1 is generated.

  Next, representative pixel values gROI, E1 in the monochrome image Gm, ROI, E1 of the generated region of interest ROI are calculated. As this representative pixel value, an average value, an intermediate value, a median value, and a weighted average value obtained by changing the weight according to the pixel position can be considered. In the example, an average value is calculated as the representative pixel value.

  Next, the image reconstruction unit 52 is used to change the weighting used in the above-described weighted addition processing to generate monochrome images Gm, ROI, E2 of the region of interest ROI having the effective X-ray energy E2. A representative pixel value gROI, E2 in the monochrome image Gm, ROI, E2 of the generated region of interest ROI is calculated.

  By repeating such processing, a representative monochromatic image Gm, ROI, E1, Gm, ROI, E2,..., Gm, ROI, En for each region of interest ROI of each effective X-ray energy. Pixel values gROI, E1, gROI, E2,..., GROI, En are calculated.

  Thereby, the relationship between the effective X-ray energy and the representative pixel value in the monochrome image of the region of interest ROI of the effective X-ray energy can be obtained. That is, it is possible to obtain a relationship that can grasp how the pixel value in the monochrome image changes with respect to a certain change in the effective X-ray energy value. A graph representing this relationship is a spectral HU curve CROI of the region of interest ROI.

  The spectral HU curve can be obtained more accurately as the number (type) n of effective X-ray energies is larger, that is, as the above “representative pixel value” is calculated for more effective X-ray energies. Therefore, the “representative pixel value” may be calculated for effective X-ray energies of usually 3 or more, preferably 5 or more, and more preferably 10 or more. Of course, this is not a story limited to the spectral HU curve CROI of the region of interest ROI, but is common in obtaining all the spectral HU curves.

  FIG. 7 is a diagram illustrating an example of a spectral HU curve of a region of interest. The horizontal axis represents the effective X-ray energy E [keV] of the monochrome image in the region of interest ROI, and the vertical axis represents the representative pixel value gROI, E [HU] in the monochrome image of the region of interest ROI.

  In this example, as shown in FIG. 7, a representative pixel value gROI, E is obtained in steps of 5 [keV] for effective X-ray energy in the range of 40 [keV] to 140 [keV], and each point is plotted. (Plot) to obtain a spectral HU curve CROI of the region of interest ROI.

  The spectral HU curve acquisition unit 55 also obtains spectral HU curves CR1, CR2,..., CRm of the image regions R1, R2,..., Rm other than the region of interest ROI in the reference image Gr. Perform the same process as in the case to obtain. Each image region R1, R2,..., Rm is a region of a plurality of pixels such as 2 × 2 pixels (single pixel region in the reference image Gr ′ with reduced resolution), and the representative pixel value of the region is The average value or the weighted average value of the pixel values of a plurality of pixels in the region can also be used. However, in this example, these image regions are single pixel regions in the reference image Gr, and a representative pixel value in the region is a single pixel value of the region itself.

  The spectral HU curve storage unit 56 stores a plurality of spectral HU curves of the substance for main substances included in the subject. The spectral HU curve of a substance is a curve that represents the relationship between effective X-ray energy and pixel values corresponding to the substance in a monochrome image of the effective X-ray energy. As main substances contained in the subject, for example, iodine (contrast medium), calcium (bone), fat, blood, water, a mixed substance containing at least one of these can be considered.

  In addition, calcium and fat are divided in stages from high density to low density. As the mixed substance, for example, a mixed substance of blood and iodine, a mixed substance of fat and calcium, and the like can be considered. As for the mixed substance of blood and iodine, for example, blood having a contrast medium concentration of 1% to blood having a contrast medium concentration of 10% is divided stepwise in increments of 1%.

  The spectral HU curve storage unit 56 also stores the color assigned according to the type of the substance in association with the spectral HU curve of the substance. For example, green is assigned to iodine, red is assigned to calcium, yellow is assigned to fat, and blue is assigned to water. Although the details will be described later, the assigned color is used when the image area on the reference image Gr specified by the similar area specifying unit 58 is colored and displayed.

FIG. 8 is a diagram showing an example of a spectral HU curve of each substance. In this figure, Cio + b1 is blood with a contrast medium concentration of 1%, Cio + b5 is blood with a contrast medium concentration of 5%, Cio + b10 is blood with a contrast medium concentration of 10%, Cca1 is low concentration of calcium, Cca2 is a medium concentration of calcium, Cca3
Is a high concentration calcium, Cfat1 is a low concentration fat, Cfat2 is a medium concentration fat, Cfat3 is a high concentration fat, and Cw is a water curve.

  As shown in FIG. 8, since the shape and absolute value of the spectral HU curve of each substance differ depending on the type and density of the substance, the substance in the image region where the curve is obtained from the shape and absolute value of the spectral HU curve. Type and density can be specified.

  The similar curve detection unit 57 detects a curve whose shape is similar to the spectral HU curve CROI of the region of interest ROI among the spectral HU curves of each substance stored in the spectral HU curve storage unit 56. An example of the similar curve detection process by the similar curve detection unit 57 is shown below.

  FIG. 9 is a flowchart showing the flow of the similar curve detection process. FIG. 10 is a diagram conceptually showing this similar curve detection process.

  In step T1, as shown in FIG. 10, the spectral HU curve CROI of the region of interest ROI is converted to a first effective X-ray energy width ΔE1, for example, 20 to 50 [keV] in the axial direction of the effective X-ray energy. Divided into a plurality of regions Q11, Q12,..., Q1n by width. FIG. 10 shows an example in which ΔE1 = 20 [keV] and effective X-ray energy E = 40 to 140 [keV] is divided into five.

  In step T2, with respect to the spectral HU curve CROI of the region of interest ROI, the change amount ΔgROI, Q11, ΔgROI, Q12,..., ΔgROI, Q1n of the pixel value with respect to the first effective X-ray energy width ΔE1 for each divided region. Ask for.

  In step T3, a predetermined spectral HU curve CB is selected as a comparison target of the spectral HU curve CROI of the region of interest ROI from the spectral HU curves of each substance stored in the spectral HU curve storage unit 56.

  In Step T4, as in the case of the region of interest ROI, the spectral HU curve CB to be compared is divided into a plurality of regions Q11, Q12,... With a first effective X-ray energy width ΔE1 in the axial direction of the effective X-ray energy. Divide into Q1n.

  In step T5, the change amount ΔgB, Q11, ΔgB, Q12,..., ΔgB, Q1n of the pixel value with respect to the first effective X-ray energy width ΔE1 is determined for each spectral region for the spectral HU curve CB of the substance B. Ask.

  In step T6, for each segmented area, a deviation amount is obtained from the amount of change in the pixel values of the corresponding segmented areas, and the similarity of the spectral HU curve is determined based on these deviation amounts.

  For example, the ratio rQ11 of the variation ΔgROI, Q11 to the variation ΔgB, Q11, the ratio rQ12 of the variation ΔgROI, Q12 to the variation ΔgB, Q12,..., The ratio rQ1n of ΔgROI, Q1n to the variation ΔgB, Q1n Calculate. If the ratios rQ11, rQ12,..., RQ1n are all within a predetermined range close to 1, for example, within a range of 0.9 to 1.1, the spectral HU curve CB selected as the comparison target. Is determined to be a curve similar to the spectral HU curve CROI of the region of interest ROI, and the detection process ends. The predetermined range may be adjusted according to the operation of the operator.

  On the other hand, if any one of the ratios rQ11, rQ12,..., RQ1n is outside the predetermined range, the spectral HU curve CB to be compared is not a curve similar to the spectral HU curve CROI of the region of interest ROI. Determine and proceed to step T7.

  In step T7, it is determined whether or not the selected spectral HU curve is the last curve to be compared. If it is the last curve, the process proceeds to step T8. If it is not the last curve, the process returns to step T3, and another spectral HU curve that has not been compared yet is selected as a comparison target of the spectral HU curve CROI of the region of interest ROI. Fix and continue the detection process.

  In step T8, as shown in FIG. 10, the spectral HU curve CROI of the region of interest ROI is set to a second effective X-ray energy width ΔE2, which is smaller than the first effective X-ray energy width ΔE1, for example, 5 to 10 [keV]. Divided into a plurality of regions Q21, Q22,..., Q2n by width. FIG. 10 shows an example when ΔE2 = 10 [keV].

  In step T9, with respect to the spectral HU curve CROI of the region of interest ROI, the change amount ΔgROI, Q21, ΔgROI, Q22,..., ΔgROI, Q2n of the pixel value with respect to the second effective X-ray energy width ΔE2 for each divided region. Ask for.

  In Step T10, a predetermined spectral HU curve CB is selected as a comparison target of the spectral HU curve CROI of the region of interest ROI from among the spectral HU curves stored in the spectral HU curve storage unit 56.

  In step T11, as in the region of interest ROI, the spectral HU curve CB to be compared is divided into a plurality of regions Q21, Q22,... With a second effective X-ray energy width ΔE2 in the axial direction of the effective X-ray energy. Divide into Q2n.

  In step T12, the change amount ΔgB, Q21, ΔgB, Q22,..., ΔgB, Q2n of the pixel value with respect to the second effective X-ray energy width ΔE2 for each divided region is obtained for the spectral HU curve CB to be compared. Ask.

  In step T13, for each segmented area, a deviation amount is obtained from the amount of change in the pixel values of the corresponding segmented areas, and the similarity determination of the spectral HU curve is performed based on these deviation amounts.

  For example, the ratio rQ21 of the variation ΔgROI, Q21 to the variation ΔgB, Q21, the ratio rQ22 of the variation ΔgROI, Q22 to the variation ΔgB, Q22,..., And the ratio rQ2n of ΔgROI, Q2n to the variation ΔgB, Q2n Calculate. If the ratios rQ21, rQ22,..., RQ2n are all within a predetermined range close to 1, for example, within a range of 0.9 to 1.1, the spectral HU curve CB to be compared is represented as a region of interest. It is determined that the curve is similar to the ROI spectral HU curve CROI, and the detection process is terminated. At this time, the predetermined range may be further expanded, for example, a range of 0.85 to 1.15 may be relaxed. The predetermined range can be adjusted according to the operation of the operator, and further can be adjusted for each divided region.

  On the other hand, if any one of the ratios rQ21, rQ22,..., RQ2n is outside the predetermined range, the spectral HU curve CB to be compared is not a curve similar to the spectral HU curve CROI of the region of interest ROI. Determine and proceed to step T14.

  In step T14, it is determined whether or not the selected spectral HU curve is the last curve to be compared. If it is the last curve, the detection process is terminated. If it is not the last curve, the process returns to step T10, and the effective X-ray energy width to be classified is set as the second effective X-ray energy width ΔE2, and then the spectral of the region of interest ROI. As a comparison target of the HU curve CROI, another spectral HU curve that has not been compared is selected again, and the detection process is continued.

  In this way, by switching the effective X-ray energy width ΔE that divides the spectral HU curve stepwise from large to small, the time required for detection processing can be efficiently reduced. The substance contained in the subject can be specified fairly limited if the type of the subject is known. Therefore, it is considered that the spectral HU curve CROI of the region of interest ROI is generally similar to the spectral HU curve of any substance stored in the spectral HU curve storage unit 56 with a relatively high degree of similarity. Therefore, first, a relatively rough similarity determination with a small amount of calculation is performed so as not to spend time on the detection process. And even if a detection omission occurs due to the rough similarity determination, the detection omission is prevented by a relatively fine similarity determination thereafter.

  Incidentally, the similarity determination of the spectral HU curve can be performed based on the amount of change in pixel value for at least one effective X-ray energy segmented region, but is performed based on the amount of change in pixel value for one segmented region. Therefore, the determination accuracy is improved by performing the change based on the amount of change in the pixel value with respect to the plurality of divided regions. Therefore, normally, it is performed based on the amount of change in pixel values for a plurality of segmented regions, preferably three or more segmented regions, more preferably five or more segmented regions.

  If a curve similar to the spectral HU curve CROI of the region of interest ROI is not detected even after performing such detection processing, this spectral HU curve CROI is registered as a spectral HU curve of a new substance. And stored in the spectral HU curve storage unit 56. Also, a new color is assigned and stored in association with this spectral HU curve CROI. The spectral HU curve CROI itself is treated as the detected spectral HU curve Cd.

  Note that the change amounts ΔgB, Q11, ΔgB, Q12,..., ΔgB, Q1n of the spectral HU curves CB to be compared are first calculated for the respective effective X-ray energy widths ΔE1, ΔE2,. They may be obtained and stored in advance in the spectral HU curve storage unit 56. Thereby, the time required for the detection process can be further shortened.

  Further, in this example, when all the shift amounts of the change amount of the pixel value with respect to the predetermined effective X-ray energy width in each divided region are within the predetermined range, the spectral HU curve CB to be compared is the spectral of the region of interest ROI. It is determined that the curve is similar to the HU curve CROI. However, for example, when one or more predetermined parts of the shift amounts of the change amounts are all within a predetermined range, the spectral HU curve CB to be compared is similar to the spectral HU curve CROI of the region of interest ROI. You may determine that it is a curve. The predetermined part may be a deviation amount in a segmented region on the side where the effective X-ray energy is relatively low, in which the characteristic of the curve shape is likely to appear.

  In this example, the similarity determination of the spectral HU curve is performed based on the shift amount of the change amount of the pixel value with respect to the predetermined effective X-ray energy width in each divided region. You may carry out based on a value.

  The similar region specifying unit 58 uses the spectral HU curve acquired by the spectral HU curve acquisition unit 55 among the image regions R1, R2,..., Rm other than the region of interest ROI in the reference image Gr. A region similar to the spectral HU curve Cd detected by 57 is specified. At this time, if there is a spectral HU curve of the same substance series as the detected spectral HU curve Cd, that is, if there is a spectral HU curve having the same kind of substance and a different concentration, the region similar to that curve is also included. Identify. The similarity determination is performed by the same process as the similarity determination by the similar curve detection unit 57.

  For example, one image area is selected from the image areas R1, R2,..., Rm, and a spectral HU curve CRi in the selected image area Ri is acquired. One spectral HU curve is selected from the detected spectral HU curve Cd and the spectral HU curve of the same substance series as the spectral HU curve Cdi to be compared. The spectral HU curve CRi in the image region Ri and the spectral HU curve Cdi to be compared are divided into a plurality of regions with a predetermined effective X-ray energy width ΔE in the axial direction of the effective X-ray energy. For each segmented area, a deviation amount is obtained between the pixel value change amounts of the same segmented area, and the similarity determination of the spectral HU curve is performed based on these deviation amounts. Here, when it is determined that the two curves are not similar to each other, the similar similarity determination is performed by changing the spectral HU curve to be compared. Such similarity determination processing is sequentially performed for each of the image regions R1, R2,.

  An image region in which the acquired spectral HU curve is determined to be similar to the spectral HU curve detected by the similar curve detection unit 57 or the spectral HU curve of the same substance series has similar energy characteristics to the region of interest ROI. Identified as a similar region. At this time, the material density of the similar region is specified from the spectral HU curve determined to be similar.

  FIG. 11 is a diagram illustrating an example of a reference image Gr in which a similar region RR whose spectral HU curve is similar to the region of interest ROI is specified.

  When the similar region is specified by the similar region specifying unit 58, the display control unit 53 displays the reference image Gr in which the similar region is emphasized. There are various methods of highlighting, such as displaying a predetermined pattern or texture such as shading on a similar area in a semi-transparent manner and overlaying it, or highlighting the outline of a similar area with a bold line. In this example, however, the similar region is displayed in a semi-transparent color with the color stored in association with the spectral HU curve Cd detected by the similar curve detection unit 57. At this time, the color density is changed according to the material density of the similar region. For example, when the material density is high, the color is darkened, and when the material density is low, the color is lightened.

  In this example, such colored display is similarly performed on the region of interest ROI.

  FIG. 12 is a diagram illustrating an example of the reference image Gr in which the region of interest ROI and the similar region RR are displayed in color.

  Hereafter, the flow of processing in the X-ray CT apparatus of the first embodiment will be described.

  FIG. 13 is a flowchart showing the flow of processing in the X-ray CT apparatus of the first embodiment. In this figure, “SHU curve” is an abbreviation for spectral HU curve.

  In step S1, the dual energy imaging control unit 51 controls the imaging table 10 and the scanning gantry 20 to perform dual energy imaging, and collects first and second projection data PHV and PLV.

  In step S2, the image reconstruction unit 52 reconstructs the first and second tube voltage images GHV and GLV based on the first and second projection data PHV and PLV collected in step S1. Further, the water density image Gw and the iodine density image Gio are reconstructed by subjecting the first and second tube voltage images GHV and GLV to weighted subtraction with two different weights.

  In step S3, the image reconstruction unit 52 performs a weighted addition process on the water density image Gw and iodine density image Gio reconstructed in step S2 with a predetermined weighting to obtain a monochromatic image Gm having a predetermined effective X-ray energy. Reconfigure.

  In step S4, the display control unit 53 displays the monochrome image Gm reconstructed in step S3 on the monitor 6 as a reference image Gr.

  In step S5, the region-of-interest setting unit 54 sets a region of interest ROI on the reference image Gr displayed on the monitor 6 according to the operation of the operator.

  In step S6, the spectral HU curve acquisition unit 55 uses the image reconstruction unit 52 to obtain a plurality of effective X-ray energy monochrome images for the region of interest ROI, and acquires the spectral HU curve CROI of the region of interest ROI.

  In step S7, the similar curve detection unit 57 detects a spectral HU curve similar to the spectral HU curve CROI of the region of interest ROI among the spectral HU curves of each substance stored in the spectral HU curve storage unit 56.

  In step S8, the similar curve detection unit 57 determines whether a similar spectral HU curve is detected. If not detected, the process proceeds to step S9. If detected, the process proceeds to step S10.

  In step S9, the similar curve detection unit 57 registers the substance corresponding to the region of interest ROI as a new substance. That is, the spectral HU curve CROI of the region of interest ROI is stored in the spectral HU curve storage unit 56 as a new spectral HU curve, and a new color is assigned to the substance corresponding to the region of interest ROI and is associated with this curve. To remember.

  In step S10, the display control unit 53 displays the color stored in association with the similar spectral HU curve detected in step S7 or the new spectral HU curve registered in step S9, and the region of interest ROI and similar. The color used for coloring the region, that is, the mapping color MC is determined.

  In step S11, the display control unit 53 specifies the material density of the region of interest ROI from the similar spectral HU curve detected in step S7. When a new spectral HU curve is registered in step S9, it is assumed that the new spectral HU curve is a standard material density curve, and the material density of the region of interest ROI is set to a standard predetermined value. It is specified as the material density.

  In step S12, the display control unit 53 colors the region of interest ROI in the reference image Gr translucently with the mapping color MC determined in step S10. At this time, coloring is performed with a density corresponding to the material density of the region of interest ROI specified in step S11.

  In step S13, the spectral HU curve acquisition unit 55 selects one of the image regions R1, R2,..., Rm other than the region of interest ROI that has not yet generated or acquired a spectral HU curve.

  In step S14, the spectral HU curve acquisition unit 55 generates and acquires a spectral HU curve of the selected image region (hereinafter referred to as a selection region).

  In step S15, the similar area specifying unit 58 determines whether or not the spectral HU curve of the selected area acquired in step S14 is similar to the above-described similar or new spectral HU curve. If they are similar, the process proceeds to step S16, and if they are not similar, the process proceeds to step S18.

  In step S <b> 16, the display control unit 53 specifies the substance concentration in the selected region from the magnitude of the pixel value in the spectral HU curve of the selected region.

  In step S17, the display control unit 53 colors the selected region in the reference image Gr translucently with the mapping color MC as a similar region to the region of interest ROI. At this time, it is colored with a density corresponding to the material density of the selected region.

  In step S18, the spectral HU curve acquisition unit 55 determines whether or not the current selection area is the last image area. If it is the last, the process ends. If it is not the last, the process returns to step S14 to continue the process.

  As described above, according to the first embodiment, on the reference image Gr, the region of interest ROI and the spectral HU curve, that is, the image region having an X-ray absorption characteristic similar to the region of interest ROI are displayed in the same color (layer display). An image region corresponding to the same or similar substance as the region of interest ROI can be extracted.

  In addition, since the color to be colored, that is, the mapping color MC is determined according to the type of the substance, the type of the substance can be recognized from the color.

  Further, since the image area to be colored is colored with a density corresponding to the material density of the image area, the material density can be recognized by the color density.

  If a curve similar to the spectral HU curve CROI of the region of interest ROI cannot be detected from the spectral HU curves of each material stored in the spectral HU curve storage unit 56, the material corresponding to the region of interest ROI Is registered as a new substance, and its spectral HU curve CROI is newly stored. Therefore, if the image area of the spectral HU curve similar to that of the new substance is set as the region of interest ROI from the next time onward, it can be recognized as a registered substance and has a kind of learning function. Can be made.

(Second embodiment)
FIG. 14 is a functional block diagram of a portion related to image display of the X-ray CT apparatus of the second embodiment.

  The X-ray CT apparatus 100a of the second embodiment has a configuration in which the spectral HU curve storage unit 56 and the similar curve detection unit 57 are omitted based on the first embodiment.

  In the first embodiment, a curve similar to the spectral HU curve CROI of the region of interest ROI is detected from the spectral HU curves of each substance stored in advance, and among the image regions other than the region of interest ROI, the spectral HU curve is detected. An image area whose curve is similar to the detected curve is identified and highlighted.

  On the other hand, in the second embodiment, among the image regions R1, R2,..., Rm other than the region of interest ROI, an image region whose acquired spectral HU curve is similar to the spectral HU curve CROI of the region of interest ROI is specified. And highlight it. The rest is the same as in the first embodiment.

  As mentioned above, although embodiment of invention was described, embodiment of invention is not limited to said embodiment, A various deformation | transformation and addition are possible in the range which does not deviate from the meaning of invention.

  For example, in the above-described embodiment, the similarity determination of the spectral HU curve is performed based on the pixel value at a predetermined effective X-ray energy and another predetermined effective X-ray energy in each of two spectral HU curves to be compared. One or a plurality of pixel value ratios (CT value ratios) may be obtained, and the ratio may be calculated based on the amount of deviation of the corresponding ratios. Alternatively, the spectral HU curves may be fitted to each other to obtain a variance or standard deviation of pixel values in the curves, and may be performed based on the magnitude of the variance or standard deviation.

  Further, for example, in the above embodiment, the material density of the similar region may be specified from the size of the pixel value in the spectral HU curve of the region. Spectral HU curves have the same material type and slightly different densities, but the curves are similar in shape, and the pixel values in the curve are relative to the amount of the material density. Shift to. Therefore, it is possible to obtain the material density from the size of the pixel value in the spectral HU curve.

  Further, for example, in the above embodiment, the display control unit 53 may display the spectral HU curve CROI of the region of interest ROI or the detected similar spectral HU curve on the display screen of the reference image Gr.

  Further, for example, the above embodiment is an X-ray CT apparatus including an imaging unit including the imaging table 10, the scanning gantry 20, the dual energy imaging control unit 51, and the like. An image processing apparatus and an image display apparatus that are not present are examples of embodiments of the invention. A program for causing a computer to function as such an image processing apparatus or an image display apparatus is also an example of an embodiment of the invention.

DESCRIPTION OF SYMBOLS 1 Operation console 2 Input device 3 Central processing unit 5 Data collection buffer 6 Monitor 7 Storage device 10 Imaging table (imaging means)
12 Cradle 15 Rotating part 16 Supporting part 20 Scanning gantry (imaging means)
21 X-ray tube 22 X-ray tube controller 23 Collimator 24 X-ray detector 25 Data collection device 26 Rotating part controller 29 Control controller 30 Slip ring 40 Subject (imaging target)
51 Dual energy imaging control unit (imaging means)
52 Image reconstruction unit (reconstruction means and calculation means)
53 Display control unit (display means)
54 Region-of-interest setting part (setting means)
55 Spectral HU curve acquisition unit (first and second acquisition means)
56 Spectral HU curve storage (storage)
57 Similar curve detector (detection means)
58 Similar region identification part (identification means)
81 X-ray 100 X-ray CT system

Claims (20)

At least one of the first projection data by the first X-ray and the second projection data by the second X-ray having energy different from that of the first X-ray collected by the dual energy imaging of the imaging target. Reconstructing means for reconstructing a predetermined image based on;
A pixel value of a desired pixel in a monochrome image corresponding to an image obtained by imaging using X-rays having a desired effective X-ray energy is calculated by predetermined calculation based on the first and second projection data. A calculation means;
For each image region in the predetermined image, the effective X-ray energy and the effective X-ray energy monotonous are calculated based on the pixel values of the image region in a plurality of effective X-ray energy monochrome images calculated by the calculating unit. An acquisition means for acquiring a relationship with a representative pixel value of the image region in a chromatic image;
Among the image regions, an image region in which the relationship acquired by the acquisition unit is similar to the relationship between the effective X-ray energy and the pixel value corresponding to a predetermined substance in the monochrome image of the effective X-ray energy is specified. An image processing apparatus comprising: a specifying unit that performs the processing. The image processing apparatus according to claim 1, wherein the plurality of effective X-ray energies is three or more effective X-ray energies. At least one of the first projection data by the first X-ray and the second projection data by the second X-ray having energy different from that of the first X-ray collected by the dual energy imaging of the imaging target. Reconstructing means for reconstructing a predetermined image based on;
A pixel value of a desired pixel in a monochrome image corresponding to an image obtained by imaging using X-rays having a desired effective X-ray energy is calculated by predetermined calculation based on the first and second projection data. A calculation means;
Setting means for setting a region of interest in the predetermined image;
For the region of interest in the predetermined image, the effective X-ray energy and the monotonic of the effective X-ray energy are calculated based on the pixel values of the region of interest in a plurality of effective X-ray energy monochrome images calculated by the calculating unit. First acquisition means for acquiring a relationship with a representative pixel value of the region of interest in a chromatic image;
Storage means for storing a relationship between effective X-ray energy and a pixel value corresponding to a predetermined substance in a monochrome image of the effective X-ray energy for one or more substances;
Detecting means for detecting a relationship similar to the acquired relationship among the stored relationships;
For each image region different from the region of interest in the predetermined image, based on pixel values of the image region in a plurality of effective X-ray energy monochrome images calculated by the calculation means, the effective X-ray energy and the Second acquisition means for acquiring a relationship with a representative pixel value of the image region in a monochrome image of effective X-ray energy;
A specifying means for specifying an image area in which the relationship acquired by the second acquisition means is similar to the detected relationship among the image areas;
An image display device comprising: display means for displaying the predetermined image in which the specified image region is emphasized.   The image display apparatus according to claim 3, wherein the plurality of effective X-ray energies is three or more effective X-ray energies.   The detection unit obtains the similar relationship based on a change amount of a pixel value with respect to at least one effective X-ray energy segmented region in the relationship acquired by the second acquisition unit and the stored relationship. The image display device according to claim 3 or claim 4 for detection.   The image display apparatus according to claim 5, wherein the detection unit detects the similar relationship based on a change amount of a pixel value with respect to a plurality of divided regions of effective X-ray energy.   The image display device according to claim 3, wherein the display unit displays the specified image region in a colored manner.   The image display device according to claim 7, wherein the color to be colored is a color associated with the detected relationship.   The image display device according to claim 3, wherein the one or more substances include iodine, calcium, fat, water, or a mixed substance containing at least one of these. At least one of the first projection data by the first X-ray and the second projection data by the second X-ray having energy different from that of the first X-ray collected by the dual energy imaging of the imaging target. Reconstructing means for reconstructing a predetermined image based on;
A pixel value of a desired pixel in a monochrome image corresponding to an image obtained by imaging using X-rays having a desired effective X-ray energy is calculated by predetermined calculation based on the first and second projection data. A calculation means;
Setting means for setting a region of interest in the predetermined image;
For the region of interest in the predetermined image, the effective X-ray energy and the monotonic of the effective X-ray energy are calculated based on the pixel values of the region of interest in a plurality of effective X-ray energy monochrome images calculated by the calculating unit. First acquisition means for acquiring a relationship with a representative pixel value of the region of interest in a chromatic image;
For each image region different from the region of interest in the predetermined image, based on pixel values of the image region in a plurality of effective X-ray energy monochrome images calculated by the calculation means, the effective X-ray energy and the Second acquisition means for acquiring a relationship with a representative pixel value of the image region in a monochrome image of effective X-ray energy;
A specifying unit for specifying an image region in which the relationship acquired by the second acquisition unit is similar to the relationship acquired by the first acquisition unit among the image regions;
An image display device comprising: display means for displaying the predetermined image in which the specified image region is emphasized.   The image display apparatus according to claim 10, wherein the plurality of effective X-ray energies is three or more effective X-ray energies.   The specifying means is based on a change amount of a pixel value with respect to at least one effective X-ray energy segmented area in the relationship acquired by the first acquiring means and the relationship acquired by the second acquiring means. The image display device according to claim 10 or 11, wherein a similar image region is specified.   The image display device according to claim 12, wherein the specifying unit specifies the similar image region based on a change amount of a pixel value with respect to a plurality of divided regions of effective X-ray energy.   The image display device according to claim 10, wherein the display unit displays the specified image region in a colored manner.   The display means determines a color intensity for coloring the specified image area in accordance with the substance density of the image area obtained based on the relationship acquired for the specified image area. The image display device according to claim 7, claim 8 or claim 14 to be changed. The region of interest is a multi-pixel region;
The image display device according to any one of claims 3 to 15, wherein the representative pixel value of the region of interest is an average value or a weighted average value of the pixel values of the plurality of pixels. Each image area is a single pixel area;
The image display device according to any one of claims 3 to 16, wherein the representative pixel value of the image region is a pixel value of a single pixel corresponding to the image region. Each of the image areas is a multi-pixel area,
The image display device according to any one of claims 3 to 16, wherein the representative pixel value of the image region is an average value or a weighted average value of a plurality of pixel values corresponding to the image region.   The program for functioning a computer as an apparatus as described in any one of Claims 1-18.   An X-ray CT apparatus comprising: an imaging unit that performs the dual energy imaging; and the apparatus according to any one of claims 1 to 18.

Images