JP2015093001A - Medical x-ray measuring apparatus and detection value row processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To increase the number of effective pixels belonging to a target tissue in a medical X-ray measuring apparatus such as a bone density measuring apparatus.SOLUTION: A detection value row is comprised of a plurality of L detection values (low energy X-ray detection value) and a plurality of H detection values (high energy X-ray detection value) which are alternately arranged in an X direction. A plurality of adjacent detection value pairs are set in the detection value row, and the presence or absence of a boundary 132 is determined in each adjacent detection value pair. Concretely, when a tissue class determination result based on one detection value does not coincide with a tissue class determination result based on the other detection value row (code 134 reference), a boundary 144 is determined. A pixel row is set in the detection value row on the basis of the position of the boundary 144. Concretely, either a first pixel row pattern or a second pixel row pattern is selected ((F) reference) so as to increase the number of effective pixels more in the inside of a target tissue.

Description

  The present invention relates to a medical X-ray measurement apparatus, and more particularly to setting of a pixel row for a detection value row.

  As medical X-ray measurement apparatuses, an X-ray tissue diagnosis apparatus, an X-ray imaging apparatus, an X-ray CT apparatus, and the like are known. In the following, a bone density measuring apparatus, which is a kind of X-ray tissue diagnostic apparatus, will be described and described.

  A bone density measuring device is generally a device that measures and calculates bone density of bone in a subject based on a dual energy X-ray absorption method (DEXA method) (see Patent Literature 1 and Patent Literature 2). In the bone density measuring apparatus, for example, a pencil beam-shaped X-ray is mechanically two-dimensionally scanned, and X-rays transmitted through the subject are detected in parallel therewith. More specifically, low-energy X-rays and high-energy X-rays are alternately irradiated while performing beam scanning, whereby low-energy X-ray detection values (hereinafter referred to as “L detection values”) alternately arranged in the mechanical scanning direction. And a high energy X-ray detection value (hereinafter referred to as “H detection value”).

  In the conventional bone density measuring apparatus, a two-dimensional pixel array is fixedly set with respect to a two-dimensional detection value array composed of a plurality of L detection values and a plurality of H detection values. That is, the irradiation sequence is constant regardless of the position and shape of the target bone. Each pixel constituting the pixel array includes an L detection value acquired first and an H detection value acquired later, or an H detection value acquired first and an L detection value acquired later. The bone density (the amount of bone mineral per unit area) is calculated for each pixel based on the L detection value and the H detection value constituting the pixel. Conventionally, some bone density measuring apparatuses irradiate a fan beam having a two-dimensional extent or a cone beam having a three-dimensional extent.

Japanese Patent No. 4980862 JP2012-192118A

  In the conventional bone density measuring apparatus, as described above, each pixel is configured by the L detection value (or H detection value) acquired earlier and the H detection value (or L detection value) acquired later. . Strictly speaking, the acquired coordinates of the two detection values do not coincide with each other in each pixel. Although depending on the mechanical scanning speed and the energy switching period, there is a difference of, for example, 1 cm between these coordinates. Therefore, when the boundary between the bone and the soft tissue is included in the pixel, there is a possibility that the bone density calculated for the pixel or the tissue type determined based on the bone density is not an accurate value. In order to avoid the problem, if pixels near the boundary (contour) in the bone region are uniformly excluded from the calculation target, the bone density calculation range becomes small. That is, the number of effective pixels that can be used for measurement is reduced. Since bones of small animals such as mice and rats are very small, when setting the calculation range for it, there is a request to make the calculation range as large as possible, but the above-mentioned uniform exclusion results in contrary to such a request. It invites.

  Conventional bone density measuring devices generally have a function of automatically determining the outline of a bone region, that is, the boundary between bone and soft tissue based on a bone density image or a bone density distribution. However, the determination is based on the minimum unit of pixels. Therefore, it is required to increase the resolution of boundary determination. In medical X-ray measurement apparatuses other than bone density measurement apparatuses, it is required to increase the resolution of boundary determination.

  Note that Patent Document 2 discloses a bone density measuring device capable of displaying information corresponding to L detection values and H detection values obtained in pixel units (see FIGS. 2 and 3 of the same document). ). However, this document does not disclose boundary determination in units of detection values or half pixels. In addition, there is no description about adaptively setting a pixel column or a pixel array according to the boundary.

  An object of the present invention is to make it possible to adaptively set a pixel column (a plurality of calculation detection value pairs) for a detection value column in a medical X-ray measurement apparatus. Alternatively, the number of effective pixels belonging to the target tissue can be increased.

  The medical X-ray measurement apparatus according to the present invention scans an X-ray beam that passes through a subject while switching X-ray energy, thereby detecting a plurality of low-energy X-ray detection values arranged alternately in the beam scanning direction, and An acquisition means for acquiring a detection value sequence comprising a plurality of high-energy X-ray detection values; and for the detection value sequence, selected from a pixel column pattern group including a first pixel column pattern and a second pixel column pattern Setting means for setting the pixel column pattern, and calculation means for calculating a calculation value based on a detection value pair constituting the pixel for each pixel in the pixel column to which the specific pixel column pattern is applied, The detection value pair constituting each pixel in the first pixel column pattern is a low energy detection value that exists first in the beam scanning direction and a high energy detection that exists immediately after that. The detection value pair that constitutes each pixel in the second pixel column pattern is composed of a high energy detection value that exists first in the beam scanning direction and a low energy detection value that exists immediately thereafter. It is a feature. Preferably, the first pixel column pattern and the second pixel column pattern are shifted by half a pixel in the beam scanning direction.

  According to the above configuration, the detection value sequence is acquired by scanning the subject with the X-ray beam. The X beam is preferably a fan beam. A pencil beam or cone beam may be scanned. The detection value row is composed of a plurality of low energy X-ray detection values and a plurality of high energy X-ray detection values that are alternately arranged in the beam scanning direction. Conventionally, detection value pairs (pixels) for calculating bone density and the like are fixedly set for the detection value sequence. However, according to the above configuration, detection value pairs (pixels) are adaptively set. Is possible. That is, according to the situation, any pixel column pattern can be selected from a plurality of pixel column patterns including the first pixel column pattern and the second pixel column pattern. For example, it is desirable to select a pixel column pattern so that more effective pixels belong to the target tissue. In any case, according to the subsequent pixel column pattern setting, problems caused by the uniform pixel column pattern setting can be solved or reduced. The pixel column pattern group may be configured by two of the first pixel column pattern and the second pixel column pattern, but may further be configured to include a third pixel column pattern and the like. For example, the third pixel column pattern may be a pattern having a double resolution obtained by combining the first pixel column pattern and the second pixel column pattern.

  Each detection value may be a value indicating detection intensity, a value indicating attenuation, or the like. The calculated value is preferably a bone density, but may be a value indicating fat mass or the like. Note that a one-dimensional image is formed by applying the first pixel pattern to the detection value sequence, and another one-dimensional image is formed simultaneously by applying the second pixel pattern to the same detection value sequence. You may comprise and compare and evaluate both.

  Preferably, the setting unit selects a pixel column pattern to be applied to the detection value column based on the contour of the target tissue. The outline (boundary) of the tissue of interest is specified by analyzing the detection value sequence, for example. The outline of the tissue of interest may be specified based on another image. It is also possible to manually specify the contour. If the contour of the target tissue is specified, more pixels can be set in the target tissue based on the contour. When the boundary is determined based on the detection value sequence, the tissue type may be determined not in units of pixels but in units of detection values, and when the change of the tissue type is specified, it may be determined that the boundary is the boundary. According to this method, the determination resolution can be doubled as compared with the case where the boundary determination is performed in units of pixels.

  Preferably, a plurality of adjacent detection value pairs are set for the detection value sequence, and a determination unit that determines the presence or absence of the contour of the tissue of interest for each adjacent detection value pair, the determination unit includes the adjacent detection value First determination means for determining a tissue type based on a low energy X-ray detection value in a pair, second determination means for determining a tissue type based on a high energy X-ray detection value in the adjacent detection value pair, and the adjacent Comprehensive determination means for determining the presence or absence of the contour of the tissue of interest based on the determination result of the first determination means and the determination result of the second determination means for the detected value pair. Desirably, the determination result of the first determination means and the determination result of the second determination means are matched, and the presence of the boundary is specified by the mismatch between the two.

  Preferably, the acquisition unit is disposed on one side of the subject, and is disposed on the other side of the subject, and an X-ray generation unit that generates an X-ray fan beam that is scanned in the X direction and spreads in the Y direction. And an X-ray detection unit that detects an X-ray fan beam that has passed through the subject, and forms a two-dimensional detection value array comprising a plurality of detection value sequences arranged in the Y direction by scanning the X-ray fan beam. The setting means individually selects a pixel column pattern to be applied to each detection value column. According to this configuration, since the pixel pattern can be selected in units of detection columns, the number of effective pixels belonging to the target pixel can be increased.

  Preferably, the calculation means includes a calculation unit that generates a two-dimensional calculation value array corresponding to the two-dimensional detection value array, and a pixel array that constitutes a display image by performing interpolation processing on the two-dimensional calculation value array. An interpolation processing unit to be generated. Preferably, the target tissue is a bone, and the calculated value is a bone density.

  A pixel column processing method according to the present invention is a method of processing a detection value sequence acquired by scanning an X-ray beam that passes through a subject while switching X-ray energy, and the detection value sequence includes a beam A plurality of low energy X-ray detection values and a plurality of high energy X-ray detection values arranged alternately in the scanning direction. The method includes a first pixel column pattern and a second pixel column with respect to the detection value column. A setting step of setting a pixel column pattern selected from a pixel column pattern group including a pattern, and a detection value pair that configures the pixel for each pixel in the pixel column to which the specific pixel column pattern is applied A detection value pair that constitutes each pixel in the first pixel column pattern is a low energy detection value that exists first in the beam scanning direction. The detection value pair that comprises each of the pixels in the second pixel column pattern is a high energy detection value that exists first in the beam scanning direction and a low energy that exists immediately thereafter. It consists of an energy detection value. This method can be realized as a function of a program. In this case, the program is installed in the information processing apparatus via a storage medium or a network.

  According to the present invention, in a medical X-ray measurement apparatus, it is possible to flexibly set a pixel row (a detection value pair for calculation) according to a situation. Alternatively, the number of pixels belonging to the target tissue can be increased.

It is a figure which shows the 1st example of a bone density measuring apparatus. It is a figure which shows the two-dimensional pixel array set with respect to the two-dimensional detection value array. It is a figure for demonstrating the mechanical scanning of a fan beam. It is a figure for demonstrating the mechanical scanning of a pencil beam. It is a figure which shows the 1st example of the boundary determination method. It is a figure which shows the determination conditions in the boundary determination method shown in FIG. It is a figure which shows the 2nd example of the boundary determination method. It is a figure which shows the determination conditions in the boundary determination method shown in FIG. It is a figure which shows the 1st example of a pixel row setting. It is a figure which shows the 2nd example of pixel column setting. It is a figure which shows the 3rd example of pixel row setting. It is a figure which shows the 4th example of pixel row setting. It is a figure which shows the two-dimensional pixel array as a comparative example. It is a figure which shows the two-dimensional pixel array set adaptively according to the boundary. It is a figure for demonstrating the interpolation process and resampling process with respect to a two-dimensional pixel array. It is a figure for demonstrating the setting of the pixel array based on the back side boundary. It is a figure for demonstrating the setting of the pixel array based on the front boundary and the rear boundary. It is a figure which shows the 2nd example of a bone density measuring apparatus. It is a figure for demonstrating a pre scan. It is a figure which shows the 1st example of a setting of the two-dimensional pixel array based on a prescan result. It is a figure which shows the 2nd example of a setting of the two-dimensional pixel array based on a prescan result. It is a figure which shows the 3rd example of a setting of the two-dimensional pixel array based on a prescan result. It is a figure which shows the 4th example of a setting of the two-dimensional pixel array based on a prescan result. It is a figure which shows the specific example of a filter. It is a figure for demonstrating this scan. It is a figure which shows an example of a period variable type irradiation sequence. It is a figure which shows the 3rd example of a bone density measuring apparatus. It is a figure which shows the structural example of a pre-processing part. It is a figure for demonstrating pre-processing conditions. It is a figure which shows the two-dimensional pixel array as a comparative example. It is a figure which shows the two-dimensional pixel array to which the replacement process was performed. It is a figure which shows the 1st example of a replacement process. It is a figure which shows the 2nd example of a replacement process. It is a figure which shows the 3rd example of a replacement process. It is a figure which shows the bone density image which has 2 times the resolution.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described with reference to the drawings.

(1) First example of bone density measuring device (device configuration, boundary determination, and post-setting of pixel array)
FIG. 1 shows a conceptual diagram of a first example of a bone density measuring apparatus. The bone density measuring device is a medical X-ray measuring device that forms a bone density image by irradiating a subject with X-rays. Bone density is generally the amount of bone mineral per unit area. In this embodiment, the bone density is measured and calculated based on the DEXA method.

  In FIG. 1, the bone density measuring device is roughly composed of a measuring unit 10 and an arithmetic control unit 12. The measurement unit 10 is installed in an X-ray management area, for example. The arithmetic control unit 12 is constituted by an information processing device, for example.

  First, the measurement unit 10 will be described. As shown in FIG. 1, the subject 16 is placed on the top plate 14 </ b> A of the imaging table 14. The subject 16 has a bone 16A to be measured. The bone 16A is, for example, a lumbar vertebra or a femur. The measurement unit 10 has a lower part 18 and an upper part 20. The lower part 18 will be described. A generator 24 is provided below the top plate 14A so as to be horizontally movable. The generator 24 has an X-ray generation tube 26 that generates X-rays. In the example shown in FIG. 1, a filter unit 28 is provided on the upper side of the generator 24. A shutter unit may be provided together with the filter unit 28. A voltage is supplied from the high voltage source 30 to the X-ray generation tube 26. Specifically, a low voltage and a high voltage are alternately applied to the X-ray generation tube 26 at a timing according to the control signal 31. Thereby, low energy X-rays and high energy X-rays are alternately generated in the X-ray generation tube 26. A fan beam 32 as a two-dimensional beam is formed in the configuration example shown in FIG. 1 by the action of the collimator and filter unit 28 not shown. The fan beam 32 is a beam that spreads from below to above, that is, a planar beam. The filter unit 28 includes a filter plate that is rotationally driven, and the filter plate includes a low energy X-ray filter member and a high energy X-ray filter member. Depending on the type of X-ray, an appropriate filter corresponding to the type is inserted on the X-ray passing path. The filter unit 28 is controlled by a control unit 44 described later.

  The lower part 18 has a scanning mechanism 22. The operation is controlled by the control unit 44. In the present embodiment, both the lower movable body including the generator 24 and the upper movable body including the detector 34 described later are mechanically scanned in the X direction, that is, the direction perpendicular to the paper surface in FIG. Such mechanical scanning is performed by the scanning mechanism 22. By scanning the fan beam 32 in the X direction, a pyramid-shaped irradiation region is formed. Incidentally, the Y direction is the fan beam spreading direction, the Z direction is the X-ray irradiation direction, and more specifically, the fan beam center line is directed. X-ray generation may be performed at the top and X-ray detection may be performed at the bottom.

  The upper part 20 has a detector 34. The detector 34 has a plurality of detection cells (sensors) provided along the spreading direction of the fan beam 32, that is, the Y direction. Each detection cell individually detects X-rays. For example, about 500 detection cells are arranged one-dimensionally. Accordingly, a detection value sequence including a plurality of detection values arranged in the Y direction, that is, the fan beam spreading direction is acquired by them. By sequentially irradiating X-rays at each position in the X direction, a detection value string is obtained at each position in the X direction. However, since low energy X-rays and high energy X-rays are alternately irradiated as described above, a low energy X-ray detection value sequence (L detection value sequence) and a high energy X-ray detection value sequence (H detection value sequence). Are acquired alternately.

  As the fan beam 32 is mechanically scanned in the X direction, the detector 34 is mechanically scanned in the X direction. It is also possible to use a pencil beam instead of the fan beam. In this case, the pencil beam is two-dimensionally zigzag scanned. Further, a narrow fan beam may be two-dimensionally zigzag scanned. Further, a cone beam can be used.

  In the configuration example shown in FIG. 1, the imaging table 14 and the lower part 18 are configured separately from each other. However, they may be integrated.

  Next, the container calculation control unit 12 will be described. As described above, the arithmetic control unit 12 is constituted by an information processing apparatus, for example, a personal computer. The arithmetic control unit 12 controls the measurement unit 10 and processes data acquired by the measurement unit 10. Each process executed by the arithmetic control unit 12 is realized as a software function in the configuration example shown in FIG. In FIG. 1, each process is shown as a block.

  The data memory 36 stores a plurality of detection value strings. These constitute a two-dimensional detection value array. The two-dimensional detection value array is composed of a plurality of L detection value sequences and a plurality of H detection value sequences arranged alternately along the X direction. If the view is changed by 90 degrees, a plurality of detection value strings arranged in the Y direction can be considered in the two-dimensional detection value array. In this case, each detection value string is composed of a plurality of detection values arranged in the X direction, specifically, a plurality of L detection values and a plurality of H detection values arranged alternately in the X direction. is there. A plurality of pixels are defined for such a detection value sequence. The detection value column and the pixel column will be described in detail later.

  The boundary determination unit 38 is a module that determines a boundary based on the two-dimensional detection value array. The pixel array setting unit 42 is a module that defines or sets a two-dimensional pixel array for the two-dimensional detection value array based on the determination result of the boundary determination unit 38, that is, based on the determined boundary. The operations of the boundary determination unit 38 and the pixel array setting unit 42 will be described in detail later.

  The bone density calculation unit 40 is a module that calculates the bone density for each pixel constituting the two-dimensional pixel array set by the pixel array setting unit 42, specifically, for each effective pixel belonging to the bone region. is there. In that case, a pair of detection values (L detection value and H detection value) constituting each pixel are referred to. In the present embodiment, the bone density is calculated according to the DEXA method as described above. In order to realize the method, the bone density calculation uses a measurement result separately measured in a state where the subject is not inserted on the X-ray beam path. That is, prior to measurement on the subject, the X-ray intensity in a state where the subject is not attenuated is measured. This can be regarded as the incident X-ray intensity when the subject is inserted.

  In the configuration example shown in FIG. 1, the boundary determination is executed based on the two-dimensional detection value array as described above. In this case, each detection value is an output value of each detection cell. However, the boundary determination may be executed based on the attenuation amount (attenuation value), or may be executed based on other data corresponding to them.

The bone density is calculated as a value proportional to R _L −α · R _H. Here, R _L = ln (I _OL / I _L ), R _H = ln (I _OH / I _H ), and α = _RL / _RH . However, each value is as follows. α is a coefficient measured in the soft tissue region (other than the bone region).
I _OL : Incident intensity of low energy X-ray
I _OH : Incident intensity of high energy X-ray
I _L : Intensity of low energy X-rays (detected value in the area where bone and soft tissue exist)
I _H : Intensity of high energy X-rays (detected value in the area where bone and soft tissue exist)

L detected values and H detected values described above are, for example, I _L and I _H. However, values corresponding to them, for example, R _L and R _H can also be used.

  In FIG. 1, a control unit 44 is a module that executes control of bone density measurement. Further, the control unit 44 has a function of calculating an average bone density within a calculation range (region of interest). Incidentally, the calculation range is set by the bone density calculation unit 40 or the control unit 44. The input unit 46 is operated by the examiner. The display unit 48 is a display for displaying a bone density image and the like.

  FIG. 2 shows a two-dimensional pixel array 62 set for the two-dimensional detection value array 50. First, the two-dimensional detection value array 50 will be described. The two-dimensional detection value array 50 includes a plurality of detection value strings 52 and 54 arranged in the X direction. Each detection value sequence 52 includes a plurality of L detection values 56 arranged in the Y direction. Each detection value sequence 54 includes a plurality of H detection values 58 arranged in the Y direction. That is, the L detection value sequence 52 and the H detection value sequence 54 are alternately obtained by scanning the fan beam in the X direction while repeatedly performing the irradiation with the low energy X-ray and the irradiation with the high energy X-ray. As a result, a two-dimensional detection value array 50 is configured.

  From another viewpoint, the two-dimensional detection value array is constituted by a plurality of detection value strings 60 arranged in the Y direction. In that case, each detection value row 60 is composed of a plurality of L detection values and a plurality of H detection values arranged alternately in the X direction. With respect to such a two-dimensional detection value array 50, according to the bone density measuring apparatus shown in FIG. 1, the pixel row 64 is adaptively applied to each detection value row 60 in accordance with the position of the boundary included therein. Can be set. That is, as will be described later, for each detection column 60, it is possible to select a pixel column pattern that matches the position of the boundary from the first pixel column pattern and the second pixel column pattern.

  Each pixel column 64 includes a plurality of pixels 63 arranged in the X direction. Each pixel 63 includes an L detection value and an H detection value. That is, it consists of detected value pairs. However, there are two types of pairs. That is, an LH pair consisting of an L detection value existing in the positive direction in the X direction and an H detection value existing immediately thereafter, and an H detection value existing in the positive direction in the X direction and immediately thereafter There is an HL pair consisting of L detection values existing in. The first pixel column pattern is composed of a plurality of closely connected LH pairs. The second pixel column pattern is composed of closely connected HL pairs. According to the configuration example illustrated in FIG. 1, the first pixel column pattern or the second pixel column pattern can be selected for each pixel column 60 according to the position of the boundary. The specific contents will be described in detail later, but if a pixel column pattern is adaptively selected for each pixel column 60, an optimal two-dimensional detection value array 50 can be configured according to the shape of the target bone. It is.

  Incidentally, in the present embodiment, the output value of the detection cell is used in the boundary determination. However, as described above, the boundary determination may be performed based on the attenuation amount or the like. In the example illustrated in FIG. 2, the pixel column pattern is selected for each single pixel column 60, but the pixel column pattern may be selected in units of a plurality of pixel columns. In any case, by applying a method of selecting a pixel column pattern, the number of effective pixels to be subjected to bone density calculation can be increased more than before, or the accuracy and reproducibility of measurement can be improved than before. Is possible.

  FIG. 3 conceptually shows the mechanical scanning of the fan beam. Reference numeral 34 denotes a detector, which is composed of a plurality of detection cells 34a arranged in the Y direction. When such a detector 34 is mechanically scanned in the X direction across the target bone 66, a rectangular scan area 65 is constructed.

  FIG. 4 shows a mechanical scan of the pencil beam. Reference numeral 68 schematically represents a pencil beam. Such a pencil beam 68 is scanned two-dimensionally with respect to the target bone 70. Reference numeral 72 represents a zigzag scan path in that case. The zigzag scan path 72 includes a path part 72-1 corresponding to a positive scan in the X direction, a path part 72-2 corresponding to a positive scan in the Y direction, and a path part 72 corresponding to a negative scan in the X direction. -3 and a path portion 72-4 corresponding to a positive scan in the Y direction. However, in the configuration of FIG. 4, for example, the X direction corresponds to the main scanning direction, and the Y direction corresponds to the sub scanning direction. However, the zigzag scan path 72 may be rotated 90 degrees.

  Next, the boundary determination method will be described with reference to FIGS.

  FIG. 5 shows a first example of boundary determination. In FIG. 5, the direction from left to right corresponds to the positive direction of the X direction. (A) shows a first pixel column pattern as one selection candidate, and (B) shows a second pixel column pattern as another selection candidate. (C) shows a detection value sequence composed of a plurality of detection values arranged along the X direction. Specifically, it includes a plurality of L detection values 56 and a plurality of H detection values 58 arranged alternately. . (D) represents the determination of the boundary in units of adjacent detection value pairs. As shown in (D), a plurality of detection value pairs are set in a multiplexed manner in the detection value sequence with a half-overlapping relationship with each other. The boundary determination condition will be described later with reference to FIG.

  In the example illustrated in FIG. 5, the determination result of the tissue type based on the L detection value 56 and the determination result of the tissue type based on the H detection value 58 are matched with each other, and “no boundary” is determined when they match. If they do not match, it is determined that there is a boundary.

  Specifically, in the determination block indicated by reference numeral 74, it is determined that there is no boundary, and in the determination block indicated by reference numeral 76, it is determined that there is a boundary 78. Conventionally, the boundary is determined in units of pixels. However, in the method illustrated in FIG. 5, it is possible to determine the boundaries in units of detection values as a result. That is, it is possible to determine the presence / absence of a boundary with a resolution twice that of the prior art. When it is determined that there is a boundary (reference numeral 78), the subsequent determination process may be omitted. Of course, a subsequent determination process may be executed to determine the next boundary.

  When it is determined that there is a boundary (reference numeral 78), various processes can be realized based on the determination. For example, after identifying a bone region based on the determined boundary (reference numeral 80), image processing and measurement may be performed on the recognized bone area (reference numeral 82). Alternatively, a pixel row for bone density calculation may be set based on the determined boundary (reference numeral 84). A bone density may be calculated for each pixel in accordance with such a pixel row, and a bone density image may be constructed based on the calculated bone density (reference numeral 86). As described above, according to the configuration example illustrated in FIG. 5, an optimal pixel column pattern can be selected from the two pixel column patterns based on the determined boundary position. The two pixel column patterns have a relationship shifted by half a pixel in the X direction. By selecting the pixel column pattern, the number of effective pixels belonging to the bone region can be increased.

  FIG. 6 illustrates determination conditions in the boundary determination method illustrated in FIG. Reference numeral 88 indicates a determination result based on the L detection value, and reference numeral 90 indicates a determination result based on the H detection value. Reference numeral 92 indicates a comprehensive determination result. As indicated by reference numerals 94 and 96, when the two individual determination results match each other, the two individual determination results are employed as they are in the comprehensive determination. On the other hand, when the two individual determination results do not match, the boundary is determined as indicated by reference numeral 98. That is, it is determined that there is a boundary.

  A second example of boundary determination will be described with reference to FIGS. In FIG. 7, (A) shows a first pixel column pattern as one selection candidate, and (B) shows a second pixel column pattern as another selection candidate. (C) shows a detection value string. (D) schematically shows a boundary determination method.

  Prior to the boundary determination, the bone density is calculated based on the adjacent detection value pairs 56 and 58 (reference numeral 88). In this case, a value corresponding to bone density is calculated for soft tissue. In the block denoted by reference numeral 90, the tissue type is determined based on the individual detection values 56 and 58 constituting the adjacent detection value pair. Further, the tissue type is determined based on the bone density. The organization type is finally determined by matching the three individual determination results with each other. The determination conditions will be described later with reference to FIG. In the example illustrated in FIG. 7, any type of soft tissue, bone, and boundary is determined based on three individual determination results. When the boundary is determined, the bone region is identified based on the position where the boundary is determined (reference numeral 98), and image processing or the like is performed on the bone area (reference numeral 100).

  FIG. 8 shows determination conditions in the boundary determination method shown in FIG. Reference numeral 102 indicates a determination result based on the L detection value, reference numeral 104 indicates a determination result based on the H detection value, and reference numeral 106 indicates a determination result based on the bone density. Further, reference numeral 108 indicates a comprehensive determination result. As indicated by reference numeral 110, when all of the three individual determination results 102, 104, and 106 are bones, bone is determined in the comprehensive determination indicated by reference numeral 108. On the other hand, in other cases, it is determined that the tissue is other than bone, that is, soft tissue (see reference numeral 112). Of course, various variations are possible, for example, when the three individual determination results all indicate soft tissue, the soft tissue is comprehensively determined, and otherwise, whether the authenticity is unknown is determined. It is desirable to determine the determination conditions according to the purpose of bone density calculation and the required accuracy.

  As described above, by determining the boundary based on a plurality of detection value pairs set in a multiplexed manner, the resolution is doubled compared to the determination of the boundary based on a plurality of pixels set with a non-overlapping relationship. It is possible to realize.

(2) Description of Pixel Array Setting Example Next, a two-dimensional pixel array setting method will be described with reference to FIGS. 9 to 17. FIG. 9 to FIG. 12 show setting examples of pixel columns according to the boundary positions. First, the first example will be described with reference to FIG.

  In FIG. 9, (A) shows the section signal. In FIG. 9, the horizontal direction corresponds to the X direction. In the section signal, the symbol “L” represents a low energy X-ray irradiation period, and the symbol “H” represents a high energy X-ray irradiation period. (B) represents the organization type, that is, the contents of the organization existing in the X direction. Here, a real boundary 110 exists between the soft tissue and the bone. The actual boundary 110 coincides with a point (falling point) at which the H section is switched to the L section.

  (C) shows an array of L detection values. They are compared to a threshold 112 for discriminating between soft tissue and bone. If the L detection value is larger than the threshold 112, it is determined as soft tissue, and if it is smaller, it is determined as bone. (D) shows an array of H detection values. They are compared to a threshold 114. Soft tissue is determined for an H detection value larger than the threshold value 114, and bone is determined for an H detection value smaller than that.

  A plurality of detected value pairs are defined as evaluation objects along the X direction. Focusing on the detection value pair 116 among them, soft tissue is determined for the H detection value 118 that exists first (upstream) in the positive direction in the X direction, while it exists immediately after (on the downstream side). Bone is determined for the L detection value 120. As a result, the two individual determination results are inconsistent, and the presence of a boundary between the two detection values is determined. This is shown in (E). That is, there are shown individual determination results, and a boundary (intersection boundary) 126 is determined as a point where the soft tissue 122 is determined first and then the bone 124 is switched from there. Then, as shown in (F), according to the position of the boundary 126, one of the pixel column patterns is selected and set.

  Specifically, a specific pixel column pattern is selected from the first pixel column pattern and the second pixel column pattern so that the effective pixels belonging to the bone region are as many as possible. In the example shown in FIG. 9, as shown in (F), the first pixel column pattern composed of a plurality of LH pairs is selected. In the example shown in FIG. 9, if the second pixel column pattern composed of a plurality of HL pairs is selected, the actual boundary 110 is caused to exist at a position exactly in the middle of the specific pixel. On the other hand, in the example shown in FIG. 9, since the first pixel column pattern is set based on the position of the actual boundary 110, the number of effective pixels can be increased.

  When the first pixel column pattern is set, as shown in (G), the bone density is calculated for each pixel constituting the pixel column. In soft tissue, a calculated value corresponding to the bone density value is obtained, but it is ignored in calculating the average bone density. Reference numeral 128 denotes a threshold value for discriminating the tissue type, and a bone is determined only for a value exceeding the threshold value. However, in the example shown in FIG. 9, since comprehensive determination can be performed based on individual detection values, it is not always necessary to determine the tissue type based on bone density. Incidentally, the arrangement of the L detection values and the arrangement of the H detection values shown in FIG. 9 and the like are illustrative examples.

  FIG. 10 shows a second example. In addition, the same code | symbol is attached | subjected to the structure similar to the structure shown in FIG. 9, and the description is abbreviate | omitted. In the example shown in FIG. 10, as represented by (B), the actual boundary 130 between the soft tissue and the bone enters the L period slightly from the falling point. In such a case, paying attention to the detection value sequence indicated by (C) and (D), particularly focusing on the detection value pair 132, soft tissue is determined for the H detection value 134, and for the L detection value 136. The bone has been determined. As a result, as shown by (E), the boundary (inter-section boundary) 142 is determined at the position corresponding to the falling point. That is, the soft tissue 138 is determined on the upstream side, and the bone 140 is determined on the downstream side. As a result, as shown in (F), as in the first example shown in FIG. 9, the first pixel column pattern is selected and set. However, when attention is paid to the pixel n in the bone density column shown in (G), the bone density is slightly lower than the bone density for the pixel n shown in FIG. Depending on the magnitude of the descending, exceptional processing may be applied.

  FIG. 11 shows a third example. In FIG. 11, the same components as those shown in FIG. 9 are denoted by the same reference numerals, and the description thereof is omitted. In this third example, as shown in (B), the actual boundary 132 exists in the second half of the L section (a point away from the falling point and close to the next rising point). In the detection value sequence indicated by (C) and (D), focusing on the detection value pair 134, soft tissue is determined for the L detection value indicated by reference numeral 136, and for the H detection value indicated by reference numeral 138. The bone has been determined. That is, the two individual determination results are inconsistent with each other, whereby the boundary is determined as a result of the comprehensive determination. In this case, as shown in (E), the boundary 144 is determined at a point that coincides with the rising point in the section signal (see (A)). Before that, the soft tissue 140 is determined, and after that, the bone 142 is determined. In comparison with the first example and the second example shown in FIG. 9 and FIG. 10, the position of the boundary 144 finally determined as a result of the position of the actual boundary 132 being shifted in the positive direction of the X direction is the detected value. It is shifted by one, that is, half pixel.

  FIG. 12 shows a fourth example. Also in FIG. 12, the same components as those shown in FIG. 9 and the like are denoted by the same reference numerals, and the description thereof is omitted. In the fourth example, a boundary 146 exists at the position of the rising point as shown in FIG. In the detection value sequence shown in (C) and (D), focusing on the detection value pair 148, soft tissue is determined for the L detection value 150, and bone is determined for the H detection value 152. That is, there is a mismatch between the two individual determination results, and as a result, the boundary 160 is determined. The determined boundary 160 coincides with the rising point in (A).

  As described above, according to the above method, a boundary can be detected in units of half pixels, and a pixel pattern can be appropriately set based on the boundary. For example, it is possible to set more measurement pixels (effective pixels) in a specific bone that is a tissue of interest. In particular, when the measurement target is small, the measurement accuracy can be improved.

  FIG. 13 shows a two-dimensional pixel array 164 as a comparative example. The two-dimensional pixel array 164 is set for the two-dimensional detection value array 50. As described above, the two-dimensional detection value array 50 includes a plurality of detection value strings arranged in the X direction. They consist of a plurality of L detection value sequences 52 and a plurality of H detection value sequences 54. From another viewpoint of the two-dimensional detection value array 50, the two-dimensional detection value array 50 is an aggregate of 60 of a plurality of detection value sequences arranged in the Y direction. It consists of a plurality of L detection values and a plurality of H detection values arranged alternately in the X direction. Incidentally, reference numeral 34 represents a detector.

  Conventionally, the two-dimensional pixel array 164 is uniformly set for the two-dimensional detection value array 50 as described above. Regardless of the position and shape of the boundary 162, if individual pixels are set uniformly, the number of effective pixels 168 cannot be increased. Incidentally, reference numeral 166 indicates an invalid image, that is, a pixel that is not recognized as a pixel in the bone region.

  In the above situation, it is possible to set a two-dimensional pixel array 166 as shown in FIG. 14 by applying the above-described adaptive selection method of pixel patterns. In FIG. 14, the same components as those shown in FIG. 13 are denoted by the same reference numerals. The two-dimensional pixel array 166 includes a plurality of detection value strings 170 and 172 arranged in the Y direction. Here, the pixel column 170 is a pixel column having a first pixel column pattern, and the pixel column 172 is a pixel column having a second pixel pattern. The first pixel pattern is an aggregate of a plurality of LH pairs, and the second pixel pattern is an aggregate of a plurality of HL pairs. For each pixel column at each position in the Y direction, an appropriate pixel column pattern is selected from the two pixel column patterns according to the position of the boundary 162 in the X direction. Thereby, the number of effective pixels 168 in the bone region can be increased. Thereby, the accuracy of measurement can be increased.

  FIG. 15 shows interpolation processing and resampling processing. (A) shows the two-dimensional pixel array 166 after pattern setting. When direct measurement or direct image processing based on this is difficult, it is desirable to apply interpolation processing and resampling processing as indicated by reference numeral 174 to the two-dimensional pixel array 166. Such a processing result is a two-dimensional pixel array 176 shown in FIG. It is an array with regularity in both directions.

  FIG. 16 shows the setting of the two-dimensional pixel array 180 based on the rear boundary 178. Each block to which hatching indicated by reference numeral 182 indicates effective pixels belonging to the bone region. At each position in the Y direction, an appropriate pixel column pattern is selected according to the position of the rear boundary 178 in the X direction. That is, the pixel pattern is selected so that the number of effective pixels belonging to the bone region is increased. Note that, as shown in FIG. 17, the two-dimensional pixel array 186 may be determined so that the effective pixels are larger in the two front and rear boundaries 182 and 184.

(3) Second example of bone density measuring apparatus (explanation regarding pre-scan, boundary determination, adaptive setting of irradiation sequence, and pre-setting of pixel array)
FIG. 18 shows a second example of the bone density measuring device. In addition, the same code | symbol is attached | subjected to the structure similar to the structure demonstrated in the 1st example shown in FIG. 1, and the description is abbreviate | omitted.

  In the second example shown in FIG. 18, the bone density measuring device is roughly composed of a measuring unit 188 and an arithmetic control unit 190. The measurement unit 188 has a lower part 192 and an upper part 194. The lower part 192 has a generator 196. Generator 196 includes an x-ray generator tube 198. A filter unit 200 is provided above the generator 196. It is desirable to provide a shutter unit together with the filter unit 200. In the second example, a pencil beam 203 is generated. The pencil beam 203 is mechanically scanned in the X and Y directions. A mechanism for this is the scanning mechanism 22.

  The upper part 194 has a detector 202 that is scanned two-dimensionally. It receives the pencil beam 203. The scanning mechanism 22 mechanically scans the upper movable body including the detector 202 together with the lower movable body.

  In the two-dimensional data memory 36, a two-dimensional detection value array acquired by executing a main scan described later is stored. In this second example, a pre-scan is executed prior to the main scan. Prescan data that is the scan result is sent to the boundary determination unit 204. This pre-scan data also constitutes a two-dimensional detection value array. The boundary determination unit 204 determines the boundary between the soft tissue and the bone based on the prescan data. The determination result is output to the control unit 206.

  The control unit 206 has a function of controlling the pre-scan and a function of controlling the main scan. These functions are shown as a pre-scan control unit 208 and a main scan control unit 210 in FIG.

  In the configuration example shown in FIG. 18, when pre-scanning is performed, low-energy X-rays are used, and the entire object is scanned two-dimensionally with a pencil beam. Thereby, a two-dimensional detection value array is acquired as pre-scan data. By analyzing the pre-scan data, the contour or boundary of the bone is determined in advance, and the execution condition for the main scan is determined based on the determined position. That is, the main scanning condition is determined so that as many effective pixels as possible belong to the bone region. This will be described in detail later.

  When the main scan is executed according to the main scan conditions determined as described above, a two-dimensional detection value array including a plurality of L detection values and a plurality of H detection values is stored in the two-dimensional data memory 36. It will be. Therefore, the bone density calculation unit 40 calculates the bone based on the detection value pair constituting the pixel for each pixel constituting the two-dimensional pixel array that has already been set, specifically, for each pixel in the bone region. Calculate the density.

  In the second example shown in FIG. 18, unlike the first example, the boundary is determined by pre-scanning, and based on this, the main scanning condition, that is, the irradiation sequence or the two-dimensional pixel array is adaptively set. This will be specifically described below.

  FIG. 19 shows an example of prescan. Reference numeral 212 denotes a scan area, which is the maximum area where the pencil beam can be scanned. In pre-scanning, the scan path 216 is adaptively determined according to the shape of the contour 214A of the target bone 214. More specifically, first, as indicated by reference numeral 216-1, the pencil beam is scanned to the positive side in the X direction, and in the scanning process, the position of the boundary (contour) 214A is determined using an edge detection method. Identified. When the boundary 214A is detected, the pencil beam is moved to the X direction negative side as indicated by reference numeral 216-2. In that case, the movement is performed by a predetermined distance. Thereafter, as indicated by reference numeral 216-3, the pencil beam is moved to the Y direction positive side by a predetermined distance. From that point, as indicated by reference numeral 216-4, the pencil beam is moved again toward the positive side in the X direction. In the scanning process, edge detection is performed in parallel, and the position of the boundary 214A of the target bone 214 is specified. When a series of partial scans as described above are repeated, a scan path 216 as shown in FIG. 19 is formed as a result.

  As shown in FIG. 4, when the zigzag scan path is uniformly set over the entire scan area, it takes a long time to specify the boundary 214A. However, according to the method shown in FIG. Since the scan range can be narrowed accordingly, the advantage that the pre-scan time can be shortened can be obtained. However, when specifying the contours on both sides of the target bone 214 or when specifying the contour of a bone having a complicated shape, the boundary of the entire target bone is specified by the zigzag scan as shown in FIG. It may be.

  When the boundary is specified as described above, a pixel column is determined at each position in the Y direction according to the position of the boundary in the X direction. In that case, the entire pixel column is adjusted so that the pixel column is optimized within the bone region. A pixel column setting method will be described below using a specific example.

  FIG. 20 shows a first setting example. Reference numeral 218 indicates soft tissue, and reference numeral 220 indicates bone. A boundary 222 exists between them. Reference numeral 228 indicates the above-described two-dimensional detection value array, and reference numeral 230 indicates a two-dimensional pixel array.

  As shown in FIG. 20, in defining the pixel column along the X direction at each position in the Y direction, as many effective pixels as possible are set inside the boundary 222, that is, within the bone region. A pixel column is set. Reference numeral 224 indicates scanning in the X direction positive side in the main scan, and reference numeral 226 indicates scanning in the X direction negative side in the main scan. In any case, the pixel column is defined with reference to the boundary 222. In FIG. 20, all four pixel columns on the upper surface of the paper are configured by the first pixel column pattern, and all three pixel columns on the lower surface of the paper are configured by the second pixel column pattern. In the first example shown in FIG. 20, the alignment of the L section and the H section is the same among a plurality of pixel columns arranged in the Y direction. According to the first setting example, it is possible to obtain an advantage that the irradiation sequence at each position in the Y direction can be considerably simplified in the main scan.

  FIG. 21 shows a second setting example. In addition, the same code | symbol is attached | subjected to the structure similar to the structure shown in FIG. 20, and the description is abbreviate | omitted. This also applies to FIGS. 22 and 23 described later.

  In FIG. 21, a two-dimensional pixel array 234 is set for the two-dimensional detection value array 232. The two-dimensional pixel array 234 includes a plurality of pixel columns arranged in the Y direction. In the second setting example, the upper four pixel columns are all configured by the first pixel column pattern, and the lower three pixel columns are also configured by the first pixel column pattern. That is, at each position in the Y direction, when setting the L section and the H section in the bone region based on the boundary 222, the L section is first set on the right side (X direction positive side) of the boundary 222. The irradiation sequence is determined so that However, at each position in the Y direction, the section pitch is uniform at least within the bone region. When such a second setting example is employed, the pixel column pattern selection method is not necessarily required. In that respect, irradiation control can be simplified.

  FIG. 22 shows a third setting example. A two-dimensional pixel array 238 is set for the two-dimensional detection value array 236. In the third setting example, the irradiation sequence is finely adjusted according to the position of the boundary 222 at each position in the Y direction, that is, when viewed along the Y direction, a plurality of pixel columns are not aligned in the X direction. It has become. In other words, each irradiation sequence, that is, each pixel column is set in advance so that the first pixel of the effective pixel column is close to the boundary 222 at each position in the Y direction. Such fine control can be realized by detecting the boundary 222 in advance based on the execution result of the pre-scan.

  FIG. 23 shows a fourth setting example. A two-dimensional pixel example 244 is set for the two-dimensional detection value array 242. In the fourth setting example, the two-dimensional pixel array 244 is set based on the two boundaries 222 and 240. Specifically, for the X-direction positive scan indicated by 224, the pixel column is set with reference to the boundary 222, and for the scan 226 on the opposite X-direction negative side, the boundary 240 is set as the reference. As shown in FIG.

  In the above setting examples, particularly the setting examples shown in FIGS. 22 and 23, the irradiation sequence is dynamically variably set in accordance with the position of the boundary when scanning in the X direction. In particular, the scanning speed and the irradiation period (section length) are variably set as necessary. This will be described later with reference to FIG.

  FIG. 24 shows a filter plate 246 provided in the filter unit. In order to adjust the irradiation sequence based on the boundary, it is desirable to rotate the filter plate at a low speed. In the example shown in FIG. 24, the filter plate 246 includes nine low energy X-ray filter members 248 and nine high energy X-ray filter members 250. These two types of filter members 248 and 250 are alternately arranged along the circumferential direction. If a large number of filter plates are provided in this manner, the rotational speed of the filter plate can be lowered, and the rotational speed can be easily adjusted. Although a circular filter plate is shown in FIG. 24, a drum-shaped filter plate may be provided.

  FIG. 25 shows an example of a scan path in the main scan. A target bone 255 exists in the scan area 254. When the contours on both sides of the target bone 255 are specified by the pre-scan, the main scan path may be set based on the contour. One example is indicated by reference numeral 258. Reference numeral 256 represents a pencil beam.

  The scan path 258 has a path portion 258-1 corresponding to a scan to the positive side in the X direction. The path portion 258-1 starts from a position descending from the X-direction negative boundary to the X-direction negative side by a predetermined distance, and ends at a position separated by a predetermined distance from the X-direction positive boundary to the X-direction positive side. It is what. The pencil beam is scanned over a predetermined distance from the end point of the path portion 258-1 to the positive side in the Y direction. This is represented by the path portion 258-2. Thereafter, the pencil beam is moved to the X direction negative side. Even in that case, the start point and the end point of the scan are determined based on the boundaries on both sides of the target bone 255 in the X direction. Reference numeral 258-4 represents a path portion in a scan to the Y-direction positive side following the path portion 258-3. A series of processes as described above are repeatedly executed so as to cover the entire target bone 255. According to such setting of the main scan path, it is possible to shorten the main scan time. However, in order to properly set a pixel row in the target bone, if a certain run-up period is necessary on the near side of the target bone, a margin may be set on both sides of the target bone for such a run-up period. .

  FIG. 26 shows an irradiation sequence in the main scan. This defines an X-direction scan that is performed at a specific position in the Y direction. Reference numeral 260 represents a cross section of the target bone. The width is represented by W1. W2 indicates the main scan range in the X direction. The range W2 can be different at each position in the Y direction. Incidentally, W3 represents the maximum width of the scan area.

  (A) represents the operation of the shutter unit. The shutter unit is provided as necessary. When the shutter is in the closed state, X-rays are shielded on the near side of the subject, and the exposure of the subject is reduced. When the shutter is in the open state, X-rays pass through the subject. (B) represents a scan 262 toward the positive side in the positive direction. The irradiation sequence in that case is denoted by reference numeral 264. (C) shows a scan 272 to the X direction negative side. The irradiation sequence in that case is represented by reference numeral 274.

  As shown in (B), in this example, the boundary 282 on one side (the left side in the figure) of the target bone 260 is the reference, and the head section in the effective pixel row, that is, the reference section R1 is appropriately set. The irradiation sequence 264 is determined so that the reference section R1 is set at a position close to the boundary 262 within the bone region. Specifically, the irradiation sequence includes a run-up portion 266, an effective portion 268, and an overrun portion 270. The run-up portion corresponds to the front run-up section, the effective portion 268 corresponds to the measurement section, and the overrun portion 270 corresponds to the back-side overrun section. In the run-up portion 266, by controlling the scanning mechanism, the filter unit, etc., specifically, by controlling the number of pulses of the stepping motor that is the driving source, a stable and appropriate irradiation sequence within the bone region Can be realized.

  Also in the scan 272 in the reverse direction shown in (C), the scanning speed, the filter rotation speed, and the like are adjusted in the run-up portion 276 so that a stable irradiation sequence is formed in the effective portion 278. Also in this example, an overrun portion 280 is provided after the effective portion 278. In the scan 272, the irradiation sequence in the effective portion 278 is determined so that the reference interval (final interval) R2 closest to the boundary 282 is appropriately determined. Incidentally, in the example shown in FIG. 26, the L section and the H section coincide on the time axis between the forward scan 262 and the return path 272. This corresponds to the setting example shown in FIG. Of course, under the situation shown in FIG. 26, an irradiation sequence corresponding to the setting example shown in FIGS. 21 to 23 may be applied.

  As described above, according to the second configuration example shown in FIGS. 18 to 26, the boundary of the target bone is specified by pre-scanning, and the main scanning condition (that is, the bone density calculation pixel string) is set based on the boundary. The advantage is that it can be predetermined. Although the exposure to the subject increases by the amount corresponding to the pre-scan, if the main scan area can be reduced, the exposure amount in the main scan can be reduced. Further, there is an advantage that the main scan condition can be set finely after the boundary is specified in advance.

(4) Third example of bone density measuring device (explanation about boundary determination and detection value replacement)
Next, a third example of the bone density measuring apparatus will be described with reference to FIGS. In the configuration shown in FIG. 27, the same reference numerals are given to the same configurations as those shown in FIG. 1, and the description thereof is omitted.

  In FIG. 27, the data memory 36 stores a two-dimensional detection value array. The boundary determination unit 286 is a module that determines a boundary for a symmetric bone based on the two-dimensional detection value array. The determination method is basically the method described with reference to FIGS. 5 to 12 and the like, but this boundary determination unit 286 determines whether or not a boundary is included for each detection value. For example, in the determination condition shown in FIG. 6, the boundary inclusion is determined when it is indicated by reference numeral 98 (that is, when the two individual determination values do not match). Moreover, in the determination condition shown in FIG. 8, when a plurality of individual determination results are separated, the boundary inclusion may be determined.

  The bone density calculation unit 288 is a module that calculates a bone density for each pixel after uniformly setting a two-dimensional pixel array for the two-dimensional detection value array. However, the preprocessing is applied prior to the calculation of the bone density, and the function is shown as the preprocessing unit 290 in FIG. As will be described later, this preprocessing replaces a detection value that is considered to contain a boundary with another detection value. As a result, the number of effective pixels in the bone region can be increased apparently. For example, when measuring the average bone density of the femur of a small experimental animal, the femur itself is small and it is often impossible to ensure a sufficient number of effective pixels. In such a case, the accuracy or reliability of the average bone density can be improved by considering not only pixels that completely belong to the bone region but also pixels that belong incompletely. Therefore, a replacement process, which will be described later, is performed in order to apply a certain correction or correction to such an incomplete pixel to make it a semi-perfect pixel.

  Hereinafter, the preprocessing unit will be described in detail.

  FIG. 28 shows a specific configuration example of the preprocessing unit 290. The target specifying unit 296 specifies a detection value to be replaced according to the determination condition 300 based on the two-dimensional detection value array 298. The computing unit 302 computes a replacement value to be substituted for the replacement target based on one or more detection values having a certain relationship with the replacement target. However, the detected value may be simply copied without calculating the replacement value. The replacement execution unit 304 executes a process of substituting the detection value prepared for the replacement target.

  FIG. 29 specifically illustrates determination conditions. The replacement target is specified when two conditions indicated by reference numerals 316 and 318 are satisfied. Specifically, the condition indicated by reference numeral 316 is a condition that is currently focused on, “one detection value of detection value pairs belongs to the bone region”. The condition indicated by reference numeral 318 is a condition that is currently focused on, “the other detected value of the detected value pair contains a boundary”. When these two conditions are satisfied, as indicated by reference numeral 320, the other detected value containing the boundary is determined to be a replacement target, and the other detected value is corrected. That is, a replacement process is performed on it. Further, when determining whether or not to perform the replacement process, the magnitude of the other detected value may be taken into consideration. There are several methods for specific examples of replacement processing, which will be described later with reference to FIGS.

  FIG. 30 shows a comparative example. Reference numeral 322 indicates a bone region, and reference numeral 324 indicates a two-dimensional detection value array. For this, a two-dimensional pixel array 326 is set as in the prior art. In this case, a detection value pair indicated by a broken line is an effective pixel. The detection value pair indicated by reference numerals 328 and 330 and the detection value pair indicated by reference numerals 332 and 334 are not regarded as effective pixels. They are because one detected value contains the boundary 322.

FIG. 31 shows a representative example of the replacement process executed in the bone density measuring device shown in FIG. Assuming the situation shown in FIG. 30, the detection values 328 and 332 are determined to be replacement targets as shown in FIG. 31, and for these, the nearest effective detection value 338 is the same type. It has been copied (see reference numerals 340 and 342). That is, a replacement process is performed on them. Thereby, as shown in FIG. 31, two effective pixels can be increased. In this example, three L ₁₃ are generated. By applying such processing to a necessary replacement target, the pre-processed two-dimensional pixel array 336 is configured. Since the replaced detection value belongs to the bone region and is the nearest value, even if it is regarded as the value to be replaced, it is considered that there is not much error. The detection value paired with the replacement object is an effective detection value, and the replacement process can be said to be a method of utilizing such an effective detection value. According to such replacement processing, the number of effective pixels is increased, and in this sense, the reliability of measurement can be improved.

Incidentally, in the example shown in FIG. 31, the detection value L ₁₁ may be a replacement target, and the above replacement process may be applied to the detection value L ₁₁ . Further, the detection value L ₁₅ and replaced, may be applied to the replacement process to it. However, not all of the detected values determined to contain the boundary may be replaced, but the replacement process may be performed only when the detected values satisfy a predetermined condition.

  Next, a specific example of the replacement process will be described with reference to FIGS.

  FIG. 32 shows a first example. (A) shows a two-dimensional detection value array 344. Reference numeral 350 represents a boundary. (B) shows the specific conditions to be replaced and the contents of the replacement process. In this example, on the premise of the replacement condition shown in FIG. 29, as indicated by reference numeral 400, when the detected value containing the boundary is equal to or less than a predetermined value, that is, it can be considered that there is a high possibility of being in the bone region In this case, it is determined that the detected value is a replacement target. As indicated by reference numeral 402, the same type and nearest detection value in the bone region is copied for the replacement target (see reference numeral 354). Specifically, in the case where the detection value pair 346, 348 constitutes one pixel, when the detection value 346 is specified as a replacement target, the closest effective pixel value 354 of the same type is determined. It is referenced and copied to the replacement object.

  FIG. 33 shows a second example. (A) shows a two-dimensional detection value array 344 in which a boundary 350 exists. (B) shows the specific conditions to be replaced and the contents of the replacement process. As indicated by reference numeral 404, on the premise of the condition shown in FIG. 29, a detection value 346 that includes a boundary and is equal to or less than a predetermined value is specified as a replacement target. Then, as indicated by reference numeral 406, in the bone region, a neighborhood detection value group is specified on the basis of the replacement object, and an interpolation value (extrapolated value) is calculated based on the group, whereby the interpolation value is replaced with the replacement object. 346 is substituted. Such a process is indicated by reference numeral 358.

  FIG. 34 shows a third example. In (A), the code | symbol 344 has shown the two-dimensional detection value array, and the code | symbol 350 has shown the boundary. Reference numeral 346 is a detected value specified as a replacement target. That is, as indicated by reference numeral 408 in (B), the replacement target is specified as a detection value that includes a boundary and is equal to or less than a predetermined value on the premise of the condition shown in FIG. In addition, as indicated by reference numeral 410, a neighborhood detection value group to be replaced is specified in the bone region, and a replacement value is calculated by weighted addition processing based on them. Then, the replacement value is assigned to the replacement target. This is indicated by reference numeral 362.

  As described above, the number of effective pixels existing in the bone region can be apparently increased by performing a replacement process on a specific detection value, that is, by applying a pre-process. As a result, for example, In calculating the average bone density, there is an advantage that the calculation accuracy can be improved.

(5) Bone Density Image with Double Resolution FIG. 35 shows a method for generating a bone density image with double resolution. A two-dimensional pixel value array 364 is set for the two-dimensional detection value array 366. The two-dimensional pixel value array 364 is composed of a plurality of pixels set in units of half pixels in the X direction. For example, when focusing on the nth pixel 368 and the (n + 1) th pixel 370, half pixels overlap between them, and as a result, the pixel density is doubled in the X direction.

  In each of the above configuration examples, the bone density measuring device is shown, but the principle described above can also be applied to fat measurement and the like. As the subject, human bodies and animals other than human bodies can be considered. In particular, when measuring small animals, the number of effective pixels cannot be increased in many cases, so it is desirable to apply the above method.

  DESCRIPTION OF SYMBOLS 10 Measurement unit, 12 Computation control unit, 14 Imaging stand, 16 Subject, 18 Lower part, 20 Upper part, 22 Scan mechanism, 24 Generator, 34 Detector, 36 Data memory, 38 Boundary determination part, 40 Bone density calculation part, 42 pixel array setting unit, 44 control unit.

In the conventional bone density measuring apparatus, as described above, each pixel is configured by the L detection value (or H detection value) acquired earlier and the H detection value (or L detection value) acquired later. . Strictly speaking, the acquired coordinates of the two detection values do not coincide with each other in each pixel. Depending on the machine scanning speed and energy switching period, there is a certain difference between these coordinates. Therefore, when the boundary between the bone and the soft tissue is included in the pixel, there is a possibility that the bone density calculated for the pixel or the tissue type determined based on the bone density is not an accurate value. In order to avoid the problem, if pixels near the boundary (contour) in the bone region are uniformly excluded from the calculation target, the bone density calculation range becomes small. That is, the number of effective pixels that can be used for measurement is reduced. Since bones of small animals such as mice and rats are very small, when setting the calculation range for it, there is a request to make the calculation range as large as possible, but the above-mentioned uniform exclusion results in contrary to such a request. It invites.

Claims (8)

By scanning the X-ray beam that passes through the subject while switching the X-ray energy, the detection value is composed of a plurality of low-energy X-ray detection values and a plurality of high-energy X-ray detection values that are alternately arranged in the beam scanning direction. An acquisition means for acquiring a column;
Setting means for setting a pixel column pattern selected from a pixel column pattern group including a first pixel column pattern and a second pixel column pattern for the detection value column;
A calculation means for calculating a calculation value based on a detection value pair constituting the pixel for each pixel in the pixel column to which the specific pixel column pattern is applied;
Including
The detection value pair constituting each pixel in the first pixel column pattern is composed of a low energy detection value that exists first in the beam scanning direction and a high energy detection value that exists immediately thereafter.
A detection value pair constituting each pixel in the second pixel column pattern is composed of a high energy detection value that exists first in the beam scanning direction and a low energy detection value that exists immediately thereafter.
A medical X-ray measuring apparatus characterized by that. The apparatus of claim 1.
The first pixel column pattern and the second pixel column pattern are in a relationship shifted by half a pixel in the beam scanning direction.
A medical X-ray measuring apparatus characterized by that. The apparatus of claim 2.
The setting unit selects a pixel column pattern to be applied to the detection value column based on a contour of a target tissue;
A medical X-ray measuring apparatus characterized by that. The apparatus of claim 3.
A plurality of adjacent detection value pairs are set for the detection value sequence, and includes a determination unit that determines the presence or absence of the contour of the target tissue for each adjacent detection value pair,
The determination means includes
First determination means for determining a tissue type based on a low energy X-ray detection value in the adjacent detection value pair;
Second determination means for determining a tissue type based on a high-energy X-ray detection value in the adjacent detection value pair;
Based on the determination result of the first determination unit and the determination result of the second determination unit for the adjacent detection value pair, a comprehensive determination unit that determines the presence or absence of the contour of the tissue of interest;
A medical X-ray measuring apparatus comprising: The apparatus of claim 1.
The acquisition means includes
An X-ray generation unit that is disposed on one side of the subject and that generates an X-ray fan beam that is scanned in the X direction and spreads in the Y direction;
An X-ray detection unit disposed on the other side of the subject and detecting an X-ray fan beam transmitted through the subject;
Including
A two-dimensional detection value array comprising a plurality of detection value rows arranged in the Y direction by scanning with the X-ray fan beam is configured,
The setting unit individually selects a pixel column pattern to be applied to each detection value column;
A medical X-ray measuring apparatus characterized by that. The apparatus of claim 3.
The tissue of interest is bone, and the calculated value is bone density.
A medical X-ray measuring apparatus characterized by that. In a method of processing a detection value sequence acquired by scanning an X-ray beam that passes through a subject while switching X-ray energy,
The detection value sequence includes a plurality of low energy X-ray detection values and a plurality of high energy X-ray detection values arranged alternately in the beam scanning direction,
The method is
A setting step of setting a pixel column pattern selected from a pixel column pattern group including a first pixel column pattern and a second pixel column pattern for the detection value column;
A calculation step of calculating a calculation value based on a detection value pair constituting the pixel for each pixel in the pixel column to which the specific pixel column pattern is applied;
Including
The detection value pair constituting each pixel in the first pixel column pattern is composed of a low energy detection value that exists first in the beam scanning direction and a high energy detection value that exists immediately thereafter.
A detection value pair constituting each pixel in the second pixel column pattern is composed of a high energy detection value that exists first in the beam scanning direction and a low energy detection value that exists immediately thereafter.
And a detected value sequence processing method. A program that is executed in an information processing apparatus and processes a detection value sequence acquired by scanning an X-ray beam that passes through a subject while switching X-ray energy,
The detection value sequence includes a plurality of low energy X-ray detection values and a plurality of high energy X-ray detection values arranged alternately in the beam scanning direction,
The program is
A function of setting a pixel column pattern selected from a pixel column pattern group including a first pixel column pattern and a second pixel column pattern for the detection value column;
A function of calculating a calculation value based on a detection value pair constituting the pixel for each pixel in the pixel column to which the specific pixel column pattern is applied;
Including
The detection value pair constituting each pixel in the first pixel column pattern is composed of a low energy detection value that exists first in the beam scanning direction and a high energy detection value that exists immediately thereafter.
A detection value pair constituting each pixel in the second pixel column pattern is composed of a high energy detection value that exists first in the beam scanning direction and a low energy detection value that exists immediately thereafter.
A program characterized by that.

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