WO2022130530A1

WO2022130530A1 - Data processing device, x-ray device with same mounted therein, and data processing method

Info

Publication number: WO2022130530A1
Application number: PCT/JP2020/046940
Authority: WO
Inventors: 勉山河; 修一郎山本
Original assignee: 株式会社ジョブ
Priority date: 2020-12-16
Filing date: 2020-12-16
Publication date: 2022-06-23

Abstract

According to the present invention, even when an object is substantially composed of two kinds of known materials A, B, the properties (bone density, bone quality, etc.) of the material A, which is one of the two materials and attracts attention, are obtained more accurately through simpler calculation. An X-ray image of the object, which is displayed on a monitor (38), is processed on the basis of photon counting data detected by a detector (25). On the X-ray image, in a direction of the path of the X-ray, an ROI (region of interest) is set in a portion in which the materials A (e.g. bone), B (e.g. "skin/muscle") are estimated to be present. An n-dimensional spatial vector (n is a positive integer of 2 or greater) of each of a plurality of pixels of the X-ray detector is calculated on the basis of the photon counting data, the spatial vectors corresponding to X-ray attenuation values in n respective energy regions of the X-ray when the X-ray passes through the object. The direction and magnitude of the spatial vector of each of the plurality of pixels are averaged and a representative vector, which represents the ROI, is calculated. An n-dimensional reference vector corresponding to the X-ray attenuation values of the material B is subtracted from an n-dimensional objective vector corresponding to X-ray attenuation values equivalent only to the material A.

Description

Data processing device, X-ray device equipped with the data processing device, and data processing method

The present invention relates to a data processing device that processes X-ray transmission data of an object imaged by using continuous X-rays, an X-ray device equipped with the data processing device, and a data processing method. In particular, the present invention is a data processing apparatus for processing X-ray transmission data collected using a photon counting type X-ray detector and evaluating the properties of an object such as bone mineral quantification. , An X-ray apparatus equipped with the data processing apparatus, and a data processing method.

In recent years, there have been many requests to identify the type and properties of objects using X-rays. One example is bone density measurement (bone mineral quantification), which measures the density of bone in the human body for the prevention and treatment of osteoporosis. Preventing this osteoporosis is also an important factor in extending healthy life expectancy.

In this osteoporosis diagnosis, in addition to bone density (bone mineral content), which is a typical index for determining bone strength, recently, bone quality has also been emphasized. Bone density (bone mineral content) indicates how much minerals such as calcium are present in bone, and bone quality is the microstructure of bone, the speed of bone turnover, the presence or absence of microfractures, and calcification. It is an index showing the state of calcium and the state of collagen.

Conventionally, the DEXA (dual-energy X-ray absorptiometry) method, the ultrasonic method, and the MD (MD) method are often used for the diagnosis of osteoporosis. The DEXA method uses two types of X-rays with different energies to measure bone density (bone mineral content) based on the difference information between the X-ray transmission data after the two types of X-rays have passed through the bone. It is a method. The ultrasonic method is a method of irradiating the heel and shin bones with ultrasonic waves and measuring the bone density from the reflected information. In the MD method, the bone density of the hand is measured by simultaneously X-raying the bones of the hand and aluminum plates (reference substances) of different thicknesses and comparing the concentrations of the bones and the aluminum plates on the X-ray images taken. It is a method to do. In addition, the presence or absence of fracture or deformation, the presence or absence of osteoporosis (decrease in bone density), and the like can be confirmed from the X-ray photograph by the X-ray examination. On the other hand, the measurement of bone quality is generally performed by evaluating the rate of bone metabolism by a blood test or a urine test using a bone metabolism marker. It was

An example of such an osteoporosis diagnostic method is known as described in Patent Document 1. The method described in Patent Document 1 belongs to the DEXA method and is disclosed as an X-ray diagnostic imaging apparatus. According to one aspect thereof, an X-ray beam having two types of high and low average energies is used. A difference image generation unit that generates a difference image from each X-ray image taken, a detection unit that detects a lumbar region from the difference image, and a transverse protrusion region and a soft tissue region from the periphery of the lumbar spine, and a detected soft tissue region. It includes a correction unit that corrects the pixel value of the lumbar region based on the pixel value of the tissue region, and a bone density calculation unit that calculates the bone density based on the corrected lumbar region. It was

In other words, this diagnostic method is a diagnostic method that utilizes the fact that the degree of attenuation of the bone component of X-rays differs depending on the energy.

By the way, the present inventors have already described the data processing described in Patent Document 2 (International Publication No. WO 2016/171186 A1 Publication (International Publication Date: October 27, 2016) regarding this photon counting type X-ray detection. Proposing a law.

According to this proposal, an image of an object is created from the count values detected by a photon counting type X-ray detector, a region of interest is set on the image, and a background of a substance existing in the region of interest in the image is created. Delete the pixel information that becomes. Further, for each of a plurality of energy regions of continuous X-rays in the region of interest, the transmission characteristic when X-rays are transmitted through the substance based on the count value for each pixel is expressed as a vector quantity, and the vector quantity is used as the vector quantity. Compute unique and unique information. It was

Assuming that the energy regions of continuous X-rays are, for example, three and the linear attenuation coefficients corresponding to the effective energy of each energy region are μ ₁ , μ ₂ , and μ ₃ , the above-mentioned vector quantity has the linear attenuation coefficient of μ ₁ . , Μ ₂ and μ ₃ are represented as a three-dimensional vector in a three-dimensional space having each dimension.

Of course, due to the influence of statistical noise and the thickness t of the material, the direction of the three-dimensional vector of each of the plurality of pixels forming the region of interest varies, and the length of the vector also varies, so that the end point of the vector starting from the coordinate origin is 3 It is sprayed while having a dimensional expanse. Therefore, in the method of Patent Document 2, first, in order to eliminate the factor of the thickness t of the material, all the three-dimensional vectors are normalized, and the spherical spray surface having the normalized length as the radius is used. , Displayed as the position (scattering point) of the vector tip (end point) connecting the coordinate origin. Then, in order to eliminate the influence of statistical noise, averaging processing is performed such as calculating the position of the center of gravity of the distribution for each set of scattering points, and the vector connecting the position of the center of gravity and the origin of the coordinates is obtained from the set distribution. Is set as a representative three-dimensional vector. The direction of this representative three-dimensional vector is peculiar to the substance or the property of the substance from the viewpoint of the attenuation of continuous X-rays. That is, the method of Patent Gazette 2 compares the vector direction with a reference value measured / calculated using a known phantom in advance or a reference value calculated theoretically, thereby determining the type and properties of the substance. It was possible to identify (estimate, evaluate). Further, in the method of Patent Publication Document 2, the dimension to be processed is not limited to three dimensions, but is a method applicable to two or more dimensions.

Japanese Patent Application Laid-Open No. 2017-131427 International Publication No. 2016/171186

However, the conventional DEXA method represented by the above-mentioned Patent Document 1 only measures the bone density (bone mineral content) by utilizing the difference in the energy information of two types of high and low X-rays, and is called bone quality. In the diagnosis and treatment of osteoporosis, the factors that have been attracting attention these days have not been taken into consideration. Therefore, this DEXA method does not completely meet the recent demands for the diagnosis and treatment of osteoporosis.
<About Patent Document 2>

On the other hand, in the above-mentioned Patent Document 2, the energy spectrum of photons forming continuous X-rays is divided into, for example, three energy regions, and the line attenuation coefficient corresponding to the effective energy of each energy region is μ ₁ , μ ₂ . , Even the vector of the three-dimensional space with μ ₃ as each dimension is obtained. Therefore, when the physical meaning of this 3D vector is applied to the evaluation of bone, the direction and size of this 3D vector is one of the indicators showing the state of bone including bone quality and bone density (bone mineral content). It is considered to be one.

The reason is that even if the substance has the same name (for example, bone), the degree of attenuation of the X-ray photon passing through the tissue of the substance differs depending on the energy level of the X-ray photon, but the substance has the same name. Even if there is, if the composition constituting it is different, it can be considered as a different substance from the viewpoint of X-ray attenuation. For example, in bones where the attenuation of high-energy X-ray photons is larger than that of low-energy X-ray photons, and bones where the attenuation is not, even if the substance is the same "bone", the above-mentioned three-dimensional vector can be used. The directions are different from each other. That is, it can be said that the direction and size of the vector are one of the indexes showing not only the amount of bone mineral but also the difference in composition and composition (that is, the difference in bone quality) constituting the bone.

However, even if the scatter diagram of the three-dimensional vector that does not depend on the material thickness t, which is proposed in Patent Document 2, is used, only the length information of the non-normalized three-dimensional vector called the absorption vector length image is used. Is not sufficient for the measurement and evaluation of bone density and bone quality required for the diagnosis and treatment of osteoporosis. That is, neither is accurate as it is.

For example, take an X-ray image of your hand to determine the amount of bone mineral in the bone (bone mineral is an inorganic bone mineral, and it is known that hydroxyapatite is a chemical substance). Consider doing (for convenience of explanation, bone is composed only of hard tissue (corresponding to bone mineral)). In this case, the region of interest is set in the bone portion reflected in the X-ray image. Both soft tissues such as skin and muscle and hard tissues of bones are present in the X-ray path leading to each pixel of the X-ray detector forming the region. Therefore, the X-ray detector collects count values depending on the attenuation coefficient and thickness of soft and hard tissues. Therefore, even if the above-mentioned three-dimensional vector is calculated from this count value, it is not possible to obtain a three-dimensional vector that accurately reflects the attenuation characteristic of hard tissue (bone mineral). Therefore, it is difficult to perform bone mineral quantification based on it with higher accuracy.

The above-mentioned problems have been described for osteoporosis diagnosis in the X-ray general radiography area by exemplifying bone mineral quantification, but a bird's-eye view of the so-called substance identification field in which it is desired to specify the type and shape of an object. Looking at it, it is not necessarily limited to the field of general X-ray photography. For example, even when quantifying bone minerals in dentistry or inspecting foreign substances in food, if there are substances with different attenuation factors and unknown thickness on the X-ray path, those substances It is difficult to easily identify the properties of one of the substances of interest.

Therefore, the present invention has been made in view of the above-mentioned substance identification in the conventional photon counting type X-ray detection, even when the target is substantially composed of two kinds of known substances A and B. On the other hand, the properties of the substance A of interest can be obtained with simpler calculations and more accuracy, and information on the properties of the substance of interest, such as bone density and bone quality, can be provided from multiple perspectives. It is an object of the present invention to provide a data processing device suitable for photon counting type X-ray detection, a data processing method, and an X-ray device equipped with or mounted thereof.

In order to achieve the above object, in the data processing apparatus according to one aspect of the present invention, continuous X-rays containing n (n is two or more positive integers) different energy regions are related to the transmission characteristics of the X-rays. When an object composed of substantially two types of known substances A and B is irradiated and the X-rays transmitted through the object are detected as detection data by an X-ray detector having a plurality of pixels, the detection is performed. Performs data-based processing. This data processing device includes an X-ray transmission image providing means that creates an X-ray image of the target based on the detection data detected by the X-ray detector and displays it on the monitor, and the X-ray transmission image display means displayed on the monitor. ROI setting means for setting ROI (region of interest) in a portion of the X-ray image where the total thickness of the substances A and B is estimated to be constant in the direction of the X-ray path, and the n pieces. One n-dimensional line attenuation corresponding to the line attenuation value when the X-ray is transmitted through the object in each of the energy regions and whose size is averaged over a plurality of the pixels forming the ROI. A line attenuation vector calculation means that calculates a vector based on the detection data, and the substance B when it is assumed that the X-ray is transmitted through only one of the two types of substances A and B, the substance B. The line includes a reference vector holding means that estimates or assumes and holds the n-dimensional reference vector corresponding to the line attenuation value, and the n-dimensional object vector corresponding to the line attenuation value equivalent only to the substance A. It is a data processing apparatus including a target vector calculation means for subtracting the n-dimensional reference vector from the n-dimensional line attenuation vector calculated by the attenuation vector calculation means. At this time, the data processing device may be provided with an arithmetic means for estimating or assuming a reference vector.

Further, as another aspect of the present invention, a data processing method is provided. In this data processing method, continuous X-rays containing n (n is a positive integer of 2 or more) different energy regions are composed of substantially two kinds of known substances A and B with respect to the transmission characteristics of the X-rays. When the X-ray that has been irradiated to the target and has passed through the target is detected as detection data by an X-ray detector having a plurality of pixels, processing based on the detection data is performed. According to this data processing method, an X-ray image of the target is created based on the detection data detected by the X-ray detector, displayed on the monitor, and displayed on the X-ray image displayed on the monitor. , ROI (region of interest) is set in the portion where the total thickness of the substances A and B is estimated to be constant in the direction of the X-ray path, and the X-rays are set in each of the n energy regions. One n-dimensional line attenuation vector corresponding to the line attenuation value when passing through the object and whose size is averaged over a plurality of the pixels forming the ROI is calculated based on the detection data. Then, when it is assumed that the X-rays pass through only one of the two types of substances A and B, the n-dimensional reference vector corresponding to the line attenuation value of the substance B is estimated or The reference vector that is assumed and held is subtracted from the n-dimensional line attenuation vector calculated by the line attenuation vector calculation means, and the n corresponding to the line attenuation value equivalent only to the substance A. It is characterized by computing a dimensional object vector. At this time, preferably, the data processing method includes an arithmetic process for estimating or assuming a reference vector.

This data processing device and data processing method can be mounted on a bone mineral quantifying device as an example. As an example in that case, the substance A is the bone (hard tissue) of the limbs of the subject, and the substance B is the skin and muscle (soft tissue) thereof.

According to the present invention, continuous X-rays containing n (n is a positive integer of 2 or more) different energy regions are derived from substantially two types of known substances A and B with respect to the transmission characteristics of the X-rays. The X-rays irradiated to the target and transmitted through the target are processed based on the count value detected by the X-ray detector having a plurality of pixels.

More specifically, an X-ray image of the target is created based on the count value and displayed on the monitor. On the X-ray image displayed on this monitor, ROI (region of interest) is set in the part where the total thickness of the substances A and B is estimated to be constant in the direction of the X-ray path, for example. Will be done. Further, in each of the n energy regions, the size corresponds to the line attenuation value when the X-ray is transmitted through the object, and the size is averaged over the plurality of pixels forming the ROI. One n-dimensional (n is a positive integer of 2 or more) line attenuation vector is calculated based on the count value. Of the two types of substances A and B, the n-dimensional reference vector corresponding to the line attenuation value of the substance B when it is assumed that only one of the substances B is transmitted by the X-ray is the line attenuation vector. By subtracting from the n-dimensional line attenuation vector calculated by the calculation means, the n-dimensional target vector corresponding to the line attenuation value equivalent only to the substance A is calculated. At this time, the reference vector is set in advance theoretically or experimentally, or in the case of a subject capable of setting the ROI for the reference vector calculation (for example, the reference vector is composed of only the substance B on the X-ray path. (For example, when there is a place where the line is present) is appropriately calculated in real time or from one image by a method similar to the method for deriving the line attenuation vector.

Therefore, on the X-ray image obtained by irradiating continuous X-rays, the ROI is set in the portion where the total thickness of the substances A and B, which is a desired portion, is estimated to be constant, for example. Further, one n-dimensional line attenuation vector whose size is averaged over a plurality of pixels forming the ROI is calculated. This n-dimensional line attenuation vector reflects the X-ray transmission characteristic in which two substances A and B of different types are synthesized in the ROI.

Therefore, the substance A is a tissue (hard tissue) of, for example, a bone part contained in a target (for example, a human limb), the substance B is a tissue of muscle and skin (soft tissue) of that part, and the target site is a bone part (substance A). The part where is present). In this case, the muscle and skin tissues correspond to the parts that interfere with the diagnosis. However, whether the information of the n-dimensional reference vector corresponding to the line attenuation value of the substance B and preset when it is assumed that the X-ray is transmitted through the substance B is stored in the memory in advance, for example. Since it can be easily calculated, the information of this reference vector is read from the memory or calculated. Further, this reference vector is subtracted from the n-dimensional line attenuation vector corresponding to the synthesized X-ray transmission characteristics of the two substances A and B. As a result, an n-dimensional target vector corresponding to the line attenuation value equivalent only to the substance A can be obtained.

Therefore, an objective vector showing X-ray attenuation of the substance A, for example, only the bone portion, can be obtained. This objective vector reflects the degree of attenuation of continuous X-ray photons with a continuous energy distribution from low to high energy as they pass through the tissue of the bone, so the density and quality of the bone. It is possible to collect count values that more accurately represent (characteristics). Moreover, even if both substances A and B are included in the ROI portion, the target vector reflecting the line attenuation of only the target substance A can be extracted with higher accuracy by a simple operation called vector subtraction.

That is, in the conventional case, even if the types of substances A and B (conceptual types such as bone and muscle) are known and the total thickness thereof is constant, the thickness in the X-ray path direction of each is unknown. However, since there are two substances having different X-ray transmission characteristics, it is difficult to obtain vector information based on the X-ray attenuation of only the target substance A by simple calculation and with high accuracy.

However, according to the present invention, the derivation of the target vector reflecting the line attenuation of only the target substance A can be easily and accurately performed by the vector operation for each region of interest.

Further, according to the present invention, a target vector of the substance A is obtained for each region of interest, and the length of the vector indicates, for example, the bone mass (bone density) per unit volume in the case of bone, and the vector of the vector. It is possible to provide information indicating the properties (states) of a more multifaceted substance for each region of interest, for example, the direction indicates the bone quality in the case of bone. Unlike the conventional process of providing information based only on bone density, it is possible to enrich the provided property information and meet the demands for diagnosis and treatment of osteoporosis, for example.
This effect is similarly enjoyed in the data processing method and the X-ray apparatus according to the present invention.

Here, preferably, the reference vector is i) estimated from the external size including the thickness of the X-ray irradiation site of the target, or the weight, or ii) statistically collected in advance and stored in a database. Read from the reference table, iii) The line attenuation vector is equivalent to the line attenuation vector in the partial region of the target imaging site that is only the substance B (since it is only substance B, the line attenuation vector = reference vector in this region). = Call the reference vector obtained and stored in advance, which is regarded as the line attenuation vector of only substance B), or when measuring the line attenuation vector of the region of interest including the substance A, the subject is photographed at the same time. It may be set by performing an operation on the assumption that it is equivalent to the line attenuation vector in the partial region of the portion that is only the substance B. Further, for example, if the direction of the reference vector exhibited by the portion of the substance B is known, the size thereof may be estimated from experiments or theoretical calculations and the information held in advance can be used. Therefore, in that case, the operation required for vector subtraction can be further simplified.

Furthermore, the direction of the reference vector itself may be stored experimentally and empirically in advance, and may be called when necessary. This makes the amount of operation of the reference vector extremely simple.

In the attached drawing
FIG. 1 is a block diagram illustrating an outline of an X-ray inspection system equipped with a data processing apparatus according to one embodiment of the present invention. FIG. 2 is a diagram illustrating an example of an energy region and an X-ray energy spectrum set in a photon counting type detector. FIG. 3 is a diagram illustrating the relationship between the single substance model and the photon count for each energy region. FIG. 4 is a diagram illustrating the relationship between the plurality of substance models and the photon count for each energy region. FIG. 5 is a flowchart illustrating an outline of the substance identification process and its preprocessing executed by the data processor. FIG. 6 is a diagram illustrating a preprocessing for substance identification performed by a data processor. FIG. 7 is a schematic flow chart illustrating a central portion of substance identification performed by a data processor in this embodiment. FIG. 8 is a diagram illustrating the generation of a three-dimensional vector of the amount of X-ray absorption from each pixel in the region of interest of the image for each energy region. FIG. 9 is a schematic flowchart illustrating a process from the creation of a three-dimensional scatter plot to the presentation of identification information. FIG. 10 is a partial flowchart illustrating the process of step S134 of FIG. 7 according to the above-described embodiment in more detail. FIG. 11 is a perspective view schematically illustrating a normalized three-dimensional scatter plot. FIG. 12 is a diagram illustrating the generation of a 3D vector from a substance-specific scatter point from a 3D scatter plot. FIG. 13 is a diagram illustrating a process from setting an ROI to the bone of the back of the hand (finger) as an object to calculating one objective vector representing only the bone portion designated by the ROI. FIG. 14 is a schematic flowchart illustrating a process of bone mineral quantification performed by a data processor. FIG. 15 is a diagram illustrating the relationship between the cross section of the finger portion and the passing X-ray path.

Hereinafter, embodiments of a data processing device and a data processing method for X-ray inspection according to the present invention will be described with reference to the attached drawings, and an X-ray inspection device equipped with the data processing device will be described as a modified example. ..
[Embodiment]

First, with reference to FIGS. 1 to 15, a data processing apparatus and a data processing method for X-ray inspection according to one embodiment of the present invention will be described as one embodiment. FIG. 1 shows a schematic configuration of an X-ray inspection system. This X-ray inspection system includes an X-ray inspection device 10 that functions as an X-ray device.

This X-ray inspection system also includes a data processing device for performing bone density measurement (bone mineral quantification) and a data processing device 12 equipped with and installed a data processing method according to one aspect of the present invention (see FIG. 1). ). The data processing device 12 may be integrated as an element of a system for collecting X-ray data, or may be provided as a general-purpose computer separate from the X-ray data collection system in a stand-alone manner. In the case of the stand-alone method, the X-ray data collection system can be connected to, for example, via the Internet, and the computer can also be configured to read the X-ray collection data and execute the bone mineral quantification process.

Note that this data processing device 12 may be pre-installed with other necessary programs so as to execute processing other than the processing for bone mineral quantification.

Further, except for the functional configuration and action / effect for quantifying bone minerals in this X-ray inspection system, the publication "WO 2016/171186 A1" (title of the invention: X-ray inspection) already disclosed by the present applicant. It can be configured in the same manner as the device described in (Applicant: Job Co., Ltd.), a data processing device and a data processing method for the purpose, and an X-ray inspection device equipped with the device. However, in the present embodiment, it is not always essential to scan the X-ray beam together with the collimator, and spot photography (simple photography) may be performed by one X-ray irradiation without scanning.

Further, it is effective to perform the bone mineral quantification according to the present embodiment in combination with the so-called substance identification already proposed by the present applicant. Therefore, in the description of this embodiment, the configuration of the X-ray inspection system, the substance identification process, and the bone mineral quantification process will be described in order.
<Configuration of X-ray inspection system>

As shown in FIG. 1, a data processing device 12 is communicably connected to the X-ray inspection device 10 via a communication line LN, and the data processing device 12 is connected to, for example, a control unit of the X-ray inspection device 10. It may be integrated or installed separately.

In the present embodiment, the X-ray inspection apparatus 10 is obtained by an X-ray image (reconstructed image or spot photography based on a laminography method) of the hand and foot (inspection target OB) of the patient (human body) as the subject. It is configured to perform bone mineral quantification based on an X-ray transmission image). Of course, this device 10 may be provided as, for example, a non-destructive inspection system such as a foreign substance inspection of food by X-ray, or an X-ray panoramic radiography system for medical use. Bone mineral quantification can also be considered as an aspect of non-destructive testing in a broad sense.

Hereinafter, the X-ray inspection apparatus 10 according to the present embodiment will be described as performing bone mineral quantification by a laminography method in which an X-ray beam is scanned by a relative movement between the X-ray beam and a subject. ..

When performing bone mineral quantification, which is one aspect of non-destructive inspection, the data processing device and data processing method for X-ray inspection according to this embodiment are absorbed information (or attenuation information) when X-rays pass through a substance. Based on the above, the basic element is to perform a process to identify (identify, discriminate, identify, or determine) the type and properties of the substance. In the following description, this process may be collectively referred to as "substance identification".

As shown in FIG. 1, the X-ray inspection device 10 has an object space OS that can virtually set an orthogonal coordinate system of the X, Y, and Z axes. Of these, the Z-axis direction corresponds to the scan direction in the object space OS in the case of non-destructive inspection. This device 10 has an X-ray beam having a predetermined cone angle θ in the Z-axis direction and a predetermined fan angle β in a direction (Y-axis direction) along a cross section (XY plane) orthogonal to the scan direction. An X-ray generator 23 including an X-ray tube 21 for generating XB and a collimator 22 is provided. The X-ray tube 21 is, for example, a rotating anode X-ray tube having a point-shaped X-ray tube focal point F (focal diameter is, for example, 1.0 mmφ). A driving high voltage for X-ray irradiation is supplied to the X-ray tube 21 from an X-ray high voltage device (not shown).

Further, the X-ray inspection device 10 includes an X-ray detector 24 (hereinafter, also simply referred to as a detector) arranged so as to face the X-ray tube 21 at a certain distance. The detector 24 is configured by connecting a plurality of modules in a line, whereby the detector 24 has an elongated rectangular X-ray incident window as a whole. Each module is made by forming a detection layer made of a semiconductor material such as CdTe, CZT (CdZnTe) into, for example, 20 × 80 pixels (each pixel has a size of 0.2 mm × 0.2 mm), and is electrically operated from X-rays. It is a so-called direct conversion type X-ray detection element that directly converts to a signal. Although not shown, a charged electrode and a collecting electrode are actually attached to both sides of the detection layer forming the plurality of pixels. A bias voltage is applied between these two electrodes.

The detector 24 regards X-rays as a collection of photons (photons) having various energies, and detects a photon counting type that can count the number of these photons for each energy region. It is a vessel. As this energy region, for example, as shown in FIG. 2, four energy regions Bin ₁ to Bin ₄ are set. Of course, the number of this energy region Bin may be a plurality.

In this detector 24, the X-ray intensity is detected as the number of X-ray photons per unit time for each pixel and each energy region Bin (actually, the cumulative number of photons for a certain period of time is measured. ). When one photon is incident on a pixel, an electric pulse signal having a peak value corresponding to the energy value is generated on the collecting electrode corresponding to the pixel. The peak value, that is, the energy value of this electric pulse signal is classified for each predetermined energy region Bin by the measurement circuit in the stage after the collection electrode, and the count value is incremented by one. This count value is collected as a cumulative value (digital value) at regular time intervals for each pixel and each energy region Bin.

This collection is performed by a data collection circuit 25 built as an ASIC layer on the lower surface of the detection layer of the detector 24. The detector 24 and the data acquisition circuit 25 constitute a detection unit 26. Therefore, X-ray transmission data (frame data) is sent from the detection unit 26, that is, the data acquisition circuit 25, to the data processing device 12 at a constant image transfer rate (frame rate). The frame is a data transfer unit, for example, a frame in which data collected at a fixed time in each pixel is collected like a still image.

An example of an X-ray inspection system having such a configuration is shown in, for example, Japanese Patent Application Laid-Open No. 2007-136163, International Publication No. WO 2007/110465 A1, and WO 2013/047778 A1. Further, an example of the photon counting type detector 24 described above is also shown in, for example, International Publication WO 2012/144589 A1.

When this X-ray inspection system is used for, for example, dental X-ray panoramic radiography, the inspection target OB is the head of the subject. In that case, the pair of the X-ray generator 23 and the detector 24 rotates and moves around the head in a state of facing each other, for example, sandwiching the head. A scan structure relating to this X-ray panoramic photography is also shown in, for example, Japanese Patent Application Laid-Open No. 2007-136163. Bone quantification is not necessarily limited to the bones of the limbs, but is performed on bones of various parts of the body. Therefore, the jaw of the subject is also one of the targets for bone mineral quantification.

Further, the data processing device 12 receives X-ray transmission data (frame data) from the X-ray inspection device 10 via the communication line LN.

As described in detail below, the data processing device 12 processes the X-ray transmission data to form an inspection target itself, and information specific to the type or property of the substance in the site of interest of the inspection target. It is configured to be able to acquire (unique information), detect whether or not other substances such as foreign substances are present in the inspection target, and perform bone mineral quantification.
[Acquisition of specific information on substances and data processing for bone mineral quantification]
Hereinafter, the configuration of the data processing device 12 and its operation will be described based on the bone mineral quantification performed together with the substance identification.

The data processing device 12 is configured by a computer system CP as an example. As shown in FIG. 1, the computer system CP itself may be a computer system having a known arithmetic function, and includes an interface (I / O) 31 connected to the detection unit 26 via a communication line LN. This interface 31 has a buffer memory 32, a ROM (read-only memory) 33 (functions as a “Non-transitory computer readable medium”), a RAM (random access memory) 34, and a CPU (central processing unit) via the internal bus B. A data processor 35 (the device may be simply referred to as a processor or a computer), an image memory 36, an input unit 37, and a display unit 38 are communicably connected to each other.

The ROM 33 stores in advance a computer-readable substance identification and bone mineral quantification program, and the data processor 35 reads the program into its own work area and executes it. The buffer memory 32 is used to temporarily store the frame data sent from the detection unit 26. The RAM 34 is used to temporarily store the data required for the calculation at the time of the calculation of the data processor 35.

The image memory 36 is composed of, for example, an SSD (solid state device) or an HDD (hard disk drive), and is used to store various image data and information processed by the data processor 35. The input device 37 and the display device 38 function as a man-machine interface with the user, and the input device 37 receives input information from the user. The display 38 can display an image or the like under the control of the data processor 35. An interface unit for obtaining information from the outside (for example, information from a user) is configured by an interface 31, an input device 37, and a display device 38.
・ Relationship between data collection by photon counting method and material model

Next, X-rays (fan-shaped beam X-rays) emitted from the X-ray tube 21 pass through the subject OB, and the transmitted X-rays are collected by the detector 24 under the photon counting method (photon counting method). The concept of data collection for each substance model at the time of counting) will be described with reference to FIGS. 2 to 4.

In FIG. 2, X-rays measured by an X-ray detector when the horizontal axis is the X-ray energy [keV] and the vertical axis is the incident frequency (count) of photons forming X-rays. The general profile of the spectrum is shown. In the case of photon counting, as is well known, a threshold value TH is set in order to divide the energy on the horizontal axis into a plurality of energy regions Bin. In the example of FIG. 2, four thresholds TH ₁ , TH ₂ , TH ₃ , and TH ₄ are given as appropriate reference voltage values to the comparator (not shown), thereby the first to first usable. The energy regions of ₃ are set to Bin ₁ , Bin ₂ , and Bin 3. The energy below the first energy region Bin ₁ belongs to an energy region that is noisy and cannot be measured, while the fourth energy region Bin ₄ located above the highest threshold value TH ₄ is a photon count. Not used as it is not involved in. Therefore, in the case of this example, the first to third energy regions Bin ₁ , Bin ₂ , and Bin ₃ are used for photon counting, excluding the uppermost and lowest energy regions.

The shape of the frequency profile shown in FIG. 2 is also determined by the type of the anode material of the X-ray tube 21 and the tube voltage, and usually, as shown in the figure, the count of the second energy region Bin ₂ is the largest. Therefore, the threshold value TH is appropriately determined in consideration of the balance of the count values (frequency, count) for each energy region. These four threshold values TH ₁ to TH ₄ are set as voltage threshold values to the comparator for each pixel of the detector 24 in the ASIC forming the data acquisition circuit 25. Therefore, the X-ray photons are counted for each pixel and each energy region. Of course, the number of threshold values TH for each pixel may be any number as long as it is three or more. If the number of threshold THs is three, then the number of energy regions used is two. Further, when the counting component contained in Bin ₄ is considered to be zero, the value of Bin ₃ + Bin ₄ can be used instead of the counting of Bin ₃ without setting TH ₄ . In this case, any positive integer may be used as long as the number of threshold values TH for each pixel is two or more. Therefore, in this case, if the number of threshold THs is 3, the number n (positive integer) of the energy regions used is 2.

When creating an X-ray transmission image (density image) from this count value, various forms can be taken. Counting information can be obtained for each pixel forming the X-ray incident surface of the detector 24 and for each energy region Bin. Therefore, when the inspection target OB is relatively moved, the count value of each pixel in each energy region Bin can be multiplied by an appropriate weighting coefficient to perform shift & add, or the inspection target OB can be stationary. In this case, if the count value of each pixel in each energy region Bin is simply added to each pixel in each energy region Bin, X-ray transmission data (frame data) in each energy region Bin can be obtained. Further, among these three energy regions Bin ₁ to Bin ₃ , the count values of any two or all energy regions Bin are multiplied by an appropriate weighting coefficient and added to the pixels at the same position to obtain one frame. It may be X-ray transmission data.

In this way, the number of X-ray photons is collected for each pixel in each energy region Bin, and it can be used for image creation in consideration of the contribution of photon energy to the pixels. It has an advantage over the collection of conventional integral type X-ray transmission data. It was

By the way, when this photon counting method is applied to substance identification, the substance (the substance in the part to be inspected in the inspection target OB: the substance that forms the inspection target itself or the substance other than the inspection target) It is appropriate to consider whether it is made up of a single tissue or multiple tissues, and consider the X-ray absorption of each tissue. For example, when bone mineral is quantified from the bones of the limbs, as shown by the one-point chain line IBn in FIG. 15, which will be described later, X-rays are skin / muscle (part B in FIG. Since it permeates in the order of 15 A part) and muscle / skin (B part in FIG. 15), there are two parts as a general name, soft tissue by "skin / muscle" and hard tissue by bone. Can be roughly divided into.
(I) When a substance consists of a single tissue (single substance model)

In the case of this single substance model, for example, in FIG. 15, the substances of the A portion and the B portion are the same, and as shown in FIG. 3 (A), the first, second, and third energy regions Bin. The linear attenuation coefficients representing ₁ , Bin ₂ , and Bin ₃ are set to μ ₁ , μ ₂ , and μ ₃ (cm ^-1 ), respectively. This line attenuation coefficient is an index showing the inherent transmission characteristics of a substance with respect to X-rays.

A model in which X-rays are incident on a substance having a line attenuation coefficient of μ ₁ , μ ₂ , μ ₃ and a thickness of t (cm), which are different for each energy region Bin, is represented as shown in the figure. That is, the incident X-ray doses (number of photons) _{Cl 1} , C _{l 2} , and _Cl 3 receive attenuation depending on the thickness t with the line attenuation coefficients μ ₁ , μ ₂ , μ ₃ , respectively, and the output X-ray dose (photons). Number) _Co1 , ^Co2 , and _Co3 are _Co1 = C _l1 x e- _μ1t
C _o2 = C _l2 x e- ^μ2t
_Co3 = C ^l3 x e- _μ3t
… (1)
It can be expressed as.

Therefore, in the case of a single substance model consisting of a single structure, as shown in FIG. 3 (B), when the X-dose (photon number) _Cli is incident on a substance having a linear attenuation coefficient μ _i and a thickness t, Its output X dose (number of photons) _Coi is _Coi = ^Cli × e- _μit
(I = 1-3)
… (2)
It can be expressed as.
(Ii) When a substance consists of multiple tissues (multiple substance model)

In the case of this multi-material model (a model in which n structures are layered), as shown in FIG. 4B, the material has a thickness ta and _a line attenuation coefficient from the viewpoint of its X-ray attenuation. It can be said that the layer structure is such that a layer of μ _ia , a layer having a thickness t _b and a linear attenuation coefficient μ _ib , ..., A layer having a thickness t _n and a linear attenuation coefficient μ _in are laminated. (The subscript i takes a value of 1 to 3 and corresponds to the subscript of Bin ₁ to Bin _3. ) Therefore, as shown in FIG. 4 (A), the first to third energy regions Bin. Considering that the line attenuation coefficient representing each of ₁ to Bin ₃ is different for each layer, μ _1a , ..., μ _1n ; μ _2a , ..., μ _2n ; μ _3a , ..., μ _3n (cm). ^-1 ) can be written. The line attenuation coefficient μ _1a , ..., _μ _1n ; _μ _2a , ..., _μ _2n ; μ _3a , ... The model when X-rays are incident on the substance of) is represented as shown in the figure. That is, the incident X-ray doses (number of photons) C _l1 , _Cl2 , and _Cl3 have linear attenuation coefficients μ _1a , ..., μ _1n ; μ _2a , ..., μ _2n ; μ _3a , ..., μ _3n , respectively, and their thicknesses. Due to the attenuation depending on ta, ..., t _n , the output X-ray dose (photon number) _Co1 , ^{Co2, and Co3 are Co1 = C l1 × e −μ1at a} _× ^… _× _e _−μ1ntn _.
C _o2 = C _l2 × e ^－μ2ata ×… × e ^－μ2ntn
C _o3 = C l3 × e _−μ3 ^ata ×… × e ^−μ3ntn
… (3)
It can be expressed as.

Therefore, in the case of a multi-material model consisting of a plurality of compositions, as shown in FIG. 4 (B), the output X-dose (photon number) C _oi is C with respect to the incident of the X-dose (photon number) C _li . _oi = C _li × e- ^μiata ×… × e ^-μintn
(I = 1-3)
… (4)
It can be expressed as.
[Processing procedure]

On the premise of the relationship between the photon measurement by the above-mentioned substance model and the line attenuation value μt, the substance identification and bone mineral quantification processing executed by the data processing apparatus 12 will be described. In the data processing apparatus 12, the data processor 35 executes a predetermined program to identify substances and quantify bone minerals according to the procedure shown in FIG. Of course, the data processor 35 may be configured to perform only bone mineral quantification.
[Preprocessing]

First, the data processor 35 determines, for example, whether or not to interactively or automatically acquire an image with the user (step S1), and waits until the timing of image acquisition. When the image acquisition is determined (steps S1, YES), the frame data is transferred from the detector unit 26 to the buffer memory 32 and saved, or the image acquisition is automatically determined in the buffer memory 32 regardless of whether or not the image acquisition is determined. The frame data that has been transferred and already stored is called to, for example, the RAM 34 (step S2). As schematically shown in FIG. 6, this frame data includes frame data FD ₁ , FD ₂ , and FD ₃ of the count values of X-ray photons having energies belonging to each of the _three energy regions Bin ₁ , Bin ₂ , and Bin 3. , The frame data FD _all of the count value of the X-ray photon in the entire energy region Bin _all (Bin ₁ + Bin ₂ + Bin ₃ ).

Next, the data processor 35 determines whether to perform substance identification and / or bone mineral quantification interactively with the user or in response to an automatic instruction (step S3). It waits until such an instruction is given, and ends the process when there is an end command (step S4).
[Creating a focused image]

When it is determined in step S3 that the substance is identified and / or the bone mineral is quantified (step S3, YES), the data processor 35 interactively or automatically with the user, for example, intersects with the test target OB. The cross section to be used is specified (step S5).

As an example, when the position of the cross section is interactively specified, as shown in FIG. 1, the user specifies the height Hc from the detector 24 via the input device 37. For example, in FIG. 1, the height in the height direction (Y-axis direction) of the inspection target _OB (for example, the instep of the hand or foot) placed on the bed BD formed of the X-ray permeable material is HOB or higher. If it is known that the cross section of the height _HC corresponding to the center in the height direction of the inspection target OB may be specified. Of course, in the case of this example, since the detection unit 26 is located below the bed BD, the height Hc is also taken into consideration for the height of the gap between the bed BD and the detection surface of the detector 24 of the detection unit 26. Is specified. That is, it can be specified as HC = _H _BD + H _OB / 2. When the height of the OB to be inspected is unknown or uneven, the height Hc may be set to the height of the surface of the bed BD. In this case, it can be specified as _HC = _HBD .

On the other hand, when it is desired to automatically specify the cross section of the inspection target OB, in step S5, it is specified that the focal plane of all pixels for optimal focusing is set for each pixel instead of the height Hc as the cross section designation information. Is done. In this case, the height of the focal plane of all pixels is not always constant, and in order to achieve optimum focusing for each pixel, there are many cases where the height is different for each pixel although it intersects the inspection target OB. .. Such a method for creating an all-pixel focal plane is exemplified in, for example, US Pat. No. 8,433,033 and PCT / JP2010 / 62842. A laminography method (or tomosynthesis method) is used to prepare these examples.

When the cross-section designation is completed in this way, the data processor 35 creates a tomographic image of the designated cross-section using, for example, a plurality of frame data FD _all for the entire energy region Bin _all (step S6).

When a certain height Hc is specified, a laminography method in which a plurality of frame data FD _alls are superimposed on each other and pixels are added while shifting with a shift amount corresponding to the height Hc. You can create it below. As a result, a tomographic image (laminography image) IM _all is created in which the optimum focusing position is adjusted to the specified height Hc (see FIG. 6). This tomographic image IM _all is also one of the in-focus images, although the in-focus position is limited to the height Hc.

On the other hand, when it is specified to set the focal plane of all pixels of the inspection target OB, all the pixels are used among the collected frame data, for example, a plurality of frame data FD _all belonging to the total energy region Bin _all . The in-focus image IM _all ´ is created under the laminography method (see FIG. 6). The inspected OB is reflected in this all-pixel in-focus image IM _all ´, and the all-pixel in-focus image IM _all ′ is a tomographic image optimized for each pixel in the height direction or the X-ray irradiation direction. It is a statue. Examples of this tomographic image include those described in US Pat. No. 8,433,033 and PCT / JP2010 / 62842, as in the above-mentioned preparation method. Although the preparation method described in this publication exemplifies for dental use, it can be used in the present embodiment by converting a curved pseudo-three-dimensional image created by this preparation method into a two-dimensional image. A two-dimensional tomographic image is created as a focal image. This two-dimensional tomographic image is more precise than the above-mentioned in-focus image IM _all with a constant height because it has undergone a process of focusing on all pixels. Since any in-focus image may be used in the present embodiment, the in-focus image IM _all will be described below.

Subsequently, the data processor 35 uses the frame data FD ₁ , FD ₂ , and FD ₃ collected from the three energy regions Bin ₁ , Bin ₂ , and Bin ₃ , respectively, and uses the specified height Hc, or, for example, all pixels. Tomographic images are sequentially created under the laminography method according to the average height of the focal surface (steps S7, S8, S9). As a result, as schematically shown in FIG. 6, a total of three in-focus images IM ₁ , IM ₂ , and IM ₃ for each energy region are created. The order in which these three in-focus images IM ₁ , IM ₂ , and IM ₃ are created is arbitrary. Of course, these three in-focus images IM ₁ , IM ₂ , and IM ₃ may also be created as all-pixel in-focus images in the same manner as described above.
[Setting the area of interest]

Next, the data processor 35 interactively or automatically sets the region of interest ROI with the user on the all-pixel focused image IM _all (step S10). This region of interest ROI is assumed to be composed of the same substance in the inspection target OB reflected in the in-focus image IM _all , for example, when identifying the type of the substance forming the inspection target OB. A region of interest ROI of appropriate size surrounding the portion (thickness may vary) is set. In the case of foreign body detection or lesion identification, a region of interest ROI of appropriate size is set to surround the suspected or pathologically suspected area (see FIG. 6).

Specifically, in the case of bone mineral quantification, the part that is presumed to be the same "skin / muscle" and "bone" in the direction of the X-ray path (for example, the second joint part of the index finger) is minute. A rectangular area of interest ROI is set (see FIG. 13 (A) described later). This region of interest ROI has a size of, for example, about 5 mm × 5 mm, and if the pixel size is 200 μm × 200 μm, the size of the pixel is 5 × 5 = 25 pixels. This region of interest ROI does not necessarily have to be rectangular and may be amorphous.

When the region of interest ROI is determined on this all-pixel in-focus image IM _all , the region of interest ROI is similarly set on the three in-focus images IM ₁ , IM ₂ , and IM ₃ for each energy region using this region information. (See FIG. 6).
[Background estimation and background deletion]

Next, the data processor 35 estimates the pixel component (background component) that is the background in the region of interest ROI on the focused image IM _all (step S11). As described above, this background component is determined by what kind of identification information is desired. When identifying or specifying the type and properties of a substance, and when performing bone mineral quantification by X-ray scanning as in the present embodiment (X-ray spot photography may be used), the background components are often a bed and air. It is a known component including. When identifying (estimating) the type of foreign substance or the state of the lesion, the component of the OB to be inspected itself is added to the known components as the background component of the foreign substance or the lesion. If the information of this background component is known, it is set as a fixed value and subtracted from the ROI of each of the three in-focus images IM ₁ , IM ₂ , and IM ₃ for each energy region (step S12).

On the other hand, if the amount of background component is unknown, it is necessary to estimate the background component. As this estimation method, it may be estimated by an appropriate method, for example, by an interpolation method from pixel values at arbitrary plurality of positions separated from each other, including only the background component outside the region of interest in the X-ray path. It was

The main purpose of the above-mentioned pretreatment is to set the ROI of the region of interest in each of the focused images IM ₁ , IM ₂ , and IM ₃ for each of the three energy regions and to remove the background component thereof. Therefore, instead of creating an all-pixel in-focus image IM _all in the entire energy region, an image sufficient for estimating the background component, that is, an in-focus image IM ₁ , IM ₂ , or IM ₃ can be used instead. good. In this case, it is possible to indirectly estimate the background component such as the in-focus image that was not directly used for the background component estimation by using the estimated background component database or the like.
[Main processing of substance identification]

When the preprocessing is completed as described above, the data processor 35 performs the main processing for substance identification (step S13). This main treatment is also used as a part of the bone mineral quantification treatment described later, and is performed as shown in FIG. 7.
<Calculation of line attenuation value μt>

First, the data processor 35 calculates the line attenuation value μt using the pixel values surrounded by the region of interest ROI and the background component removed in each of the three focused images IM ₁ , IM ₂ , and IM ₃ (FIG. 7). , Step S131). Here, μ is the linear attenuation coefficient of the substance (also simply referred to as the attenuation coefficient), and t is the thickness of the substance along the X-ray irradiation direction.

In the above-mentioned single substance model and multiple substance model, the line attenuation value μt is the following modified equations (2) and (4) for each pixel for each energy region Bin _i (i = 1 to 3). Calculated from the formula.
μ it ₌ lnC _li -lnC _oi
(I = 1-3: In the case of a single substance model)
… (5)

(I = 1 to 3, j = a to n: in the case of multiple substance models)
… (6)
Here, ln means to take the natural logarithm.

Therefore, if the number of photons incident (input) on the substance and the number of photons emitted (output) from the substance are known, the line attenuation value μt can be calculated. The number of emitted photons _Coi is the number of photons detected by the detector 24 for each energy region and for each pixel. _Cli is the number of photons of X-rays incident under the same conditions as the actual X-ray examination, and is, for example, a preset known value. Of course, it may be a value estimated at the time of substance identification in consideration of fluctuations in actual X-ray inspection conditions each time.

Since the line attenuation value μt is usually affected by the beam hardening phenomenon, it is desirable to perform the vector calculation described later after performing the correction process. Beam hardening is a phenomenon in which low-energy photons are absorbed more than high-energy photons when continuous X-rays pass through a substance, and as a result, the average (effective) energy shifts to the higher energy side. be. When this beam hardening occurs, artifacts occur and the pixel values of the reconstructed image become inaccurate. Beam hardening occurs to varying degrees and depends on the thickness of the material (the thicker the beam hardening, the greater the beam hardening). Therefore, it is desirable to correct the line attenuation value μt for each energy region and each pixel based on the correction processing method described in, for example, International Publication No. WO 2017/069286 A1 which the applicant has already applied for.

In particular, as a method for correcting the above beam hardening, the applicant may already adopt the method described in International Publication No. WO 2019/083014 A1. This method aims to contribute to the presentation of more quantitative X-ray images by performing more accurate beam hardening correction to objects with a wider range of elements with effective atomic number Z _eff with a low computational load. Proposed.

This correction method has been proposed in various aspects. According to one aspect, a desired effective atomic number (for example, Zm = 7) is specified from an effective atomic number in a desired range (Zmin to Zmax), and this designation is made. Assuming that a substance composed of an element having an effective atomic number (for example, Zm = 7) is irradiated with monochromatic X-rays, a straight line on the two-dimensional coordinates is set as a target function. Further, on the two-dimensional coordinates, the slope of the target function (μ / ρ) is multiplied in the horizontal axis direction, and a plurality of curves of each of the plurality of effective atomic numbers (for example, Z = 5 to 14) are obtained. Generalize as a variable. Further, from the plurality of generalized curves, a curve of the element having a designated effective atomic number (for example, Zm = 7) is designated, and the beam is based on the residual of this designated curve and another curve. The beam hardening correction function for correcting the hardening is stored in advance in the storage unit as the correction information. Therefore, if the generalized target function and the information regarding the residual of the specified effective atomic number in the range of the predetermined effective atomic number are possessed, the beam hardening correction function can be calculated by the above procedure. Therefore, even if the range of the effective atomic number set in advance is wider, the calculation amount does not have to be proportional to the range in calculating the beam hardening correction function. That is, the beam hardening can be corrected with a smaller computational load for an object having an element having an effective atomic number Z _eff in a wider range.

In the case of medical examination, the soft tissues of the breast and limbs can be regarded as being composed of a simpler substance, and an instrument used for compressing or fixing the imaging part is used. Even in this case, since the flat plate structure and the material are known, the accuracy of background removal is good, and this line attenuation value μt can be calculated more accurately. Further, even in the non-destructive inspection of foods and the like, if the background component can be estimated appropriately as described above, the line attenuation value μt can be calculated accurately from the pixel information after the background component is removed.

Next, the data processor 35 picks up and vectorizes the line attenuation value μt of each pixel forming the ROI of interest in the focused images IM ₁ to IM ₃ of the above-mentioned three energy regions Bin ₁ to Bin ₃ . (Step S132: see FIG. 8).

That is, a three-dimensional line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ t) is created for each pixel (see FIG. 8). Since this 3D line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ t) still contains the thickness t and density factors, this vector itself is an X-ray derived from the thickness t and density. It only indicates the amount of attenuation and cannot be a substance-specific index. This is because, as in the case of X-ray scanogram and X-ray simple radiography, since the thickness t is unknown, it is not possible to obtain the substance-specific ray attenuation coefficients μ ₁ , μ ₂ , and μ ₃ for X-rays. Furthermore, in the application of X-ray examination and diagnosis, the moving speed of the belt conveyor used for the examination may be high and the X-ray irradiation area may be passed immediately, and the patient exposure dose for diagnosis may be reduced. For the purpose of, the X-ray dose is limited. In such a case, since the count value of photons in each pixel collected for inspection or diagnosis becomes small, only one three-dimensional line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ t) is sufficient. , It is difficult to obtain information specific to a substance because it is buried in other noise components.

Therefore, the substance identification is performed by normalizing this three-dimensional line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ t) and treating it as a set.

First, each three-dimensional line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ t) is normalized (or standardized) to a unit length (length 1) by the following equation (7), and the thickness is t. And a three-dimensional mass attenuation vector (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ) that does not include the factor of the substance density is created (step S133).
(Μ ₁ ^' , μ ₂ ^' , μ ₃ ^' )
= (Μ ₁ t, μ ₂ t, μ ₃ t) / ((μ ₁ t) ² + (μ ₂ t) ² + (μ ₃ t) ² ) ^1/2
= (Μ ₁ , μ ₂ , μ ₃ ) / (μ ₁ ² + μ ₂ ² + μ ₃ ² ) ^1/2 … (7)

Of course, this normalization is to make the lengths of each three-dimensional mass attenuation vector (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ) uniform, and the length does not necessarily have to be 1, and is multiplied by an appropriate coefficient. It may be any length combined.

By normalizing in this way, the thickness t and density factors disappear, so on the three-dimensional coordinates whose linear attenuation coefficients μ ₁ , μ ₂ , and μ ₃ are orthogonal to each other, each three-dimensional mass is at the coordinate origin. If the start point of the attenuation vector (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ) is placed (step S134), the position coordinates of the end point will be the substance-specific information (material type, properties) that causes a change in μ ^′ . Information).

As described above, in the present embodiment, the vector quantity indicating the X-ray attenuation is treated as a three-dimensional line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ t) before normalization, and the three-dimensional mass after normalization. It is treated as an attenuation vector (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ). In this embodiment, all the processes are performed in three dimensions, but the same applies even if they are two-dimensional.

In the process of this step S134, for example, as shown in FIG. 10, the coordinate data of the orthogonal three axes representing the mass line attenuation coefficients μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ , which are stored in advance in the ROM 33, are spatially generated. Read (S134-1) for (for display), for example, when the length of the mass attenuation vector is 1, a partial spherical surface passing through the length of the three orthogonal axes = 1 is set in the memory space (step S134-2). ), The tip of each three-dimensional mass attenuation vector (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ) is arranged (also referred to as a dot or mapping) on this partial spherical surface from the origin O (step S134-3).

The three-dimensional tilt information of the three-dimensional mass attenuation vector (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ) for each pixel changes depending on the type and properties of the substance in the three-dimensional space set in step S134-1. It can also be said to be spray data that represents (virtually) information unique to a substance. Therefore, the position pointed to by the tip of the three-dimensional mass attenuation vector (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ), that is, the three-dimensional mass attenuation vector (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ) 3 A set of dimensional tilt information (that is, a scatter point) is also called a "three-dimensional scatter diagram". That is, if the substance changes, the inclination of the three-dimensional mass attenuation vector (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ) changes, and the three-dimensional position (position of the scattering point) pointed to by the tip also changes. The three-dimensional position information reflects the distribution of X-ray photon energy before and after passing through the inspection target OB.

Further, the data processor 35 sets the length of each three-dimensional line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ t) for each pixel to ((μ ₁ t) ² + (μ ₂ t) ² ). + (Μ ₃ t) ² ) ^1/2 ... (8)

Calculate as. The amount represented by this formula (8) is the amount of X-ray absorption (or X-ray attenuation; since the absorption of X-rays is the largest in the X-ray imaging region, it is described as "absorption" hereafter. ), Which is also useful as complementary information for substance identification, and forms a pixel value as a substitute image for a conventional absorption image. Therefore, an image is created in which the value obtained by gradation of the absorption amount is used as the pixel value (step S135). The length of this three-dimensional line attenuation vector is called the "absorption vector length" that corresponds to the pseudo (virtually) X-ray attenuation value, and the image using this as the pixel value is the "absorption vector length image (or pseudo). Absorption image) ”. This absorption vector length image is a stable image because it does not easily depend on the shape of the incident energy spectrum of X-rays, and comprehensively reflects each line attenuation value μt. As a result, this absorption vector length image becomes an image with high contrast. The absorption vector length image may be stored in the image memory 36 and displayed on the display 38 when necessary. In particular, it is possible to obtain a characteristic image for a substance having a large mass and strong X-ray beam hardening.

Finally, the data processor 35 stores the above-mentioned three-dimensional scatter diagram data as substance-specific information and the absorption vector length image as supplementary information for substance identification in the image memory 36 (FIG. 5, step S14), and is necessary. Accordingly, they are presented to the user, for example, via the display 38 (step S15).

As described above, based on the X-ray photon counting value for each energy region collected by the photon counting type detector 24, it is possible to acquire the substance-specific information regardless of the thickness of the inspection target OB. This has a great advantage when combined with the display and analysis of substance-specific information described below.
[Example of display and analysis of substance-specific information]

This process of displaying and analyzing the substance-specific information is executed, for example, as part of step S15 described above. The data processor 35 displays the above-mentioned substance-specific information in response to an instruction from the user, for example. Specifically, a sphere surface with a radius of 1 centered on the origin is set in a three-dimensional coordinate space having each element μ ₁ ^′ , μ ₂ ^′ , and μ ₃ ^′ of the three-dimensional mass attenuation vector as three axes (Fig.). 9, step S31).

Next, a three-dimensional scatter diagram consisting of three-dimensional mass attenuation vectors (μ ₁ ^′ , μ ₂ ^′ , μ ₃ ^′ ) of each pixel is set as a starting point of the origin of the three-dimensional coordinate space, and the ending point is taken as an example of the same surface. It is mapped (dotted) on the surface of a sphere (a spherical surface normalized to a radius = 1) and displayed (step S32). The set of end points on this mapped sphere surface is a set of substance-specific scatter points based on the substance-specific information. Therefore, even if substances having different thicknesses t between pixels are to be inspected, a set of scatter points that does not depend on the factor of the thickness t can be obtained.

FIG. 11 schematically shows an example in which a set of scatter points is set as a three-dimensional scatter plot and dots are made on a part of a normalized sphere surface (a part of the same surface).

The data processor 35 then groups the scatter points guided for all or part of each pixel forming the region of interest ROI, for example, as shown in FIG. 12 (A) (see dotted box: step S33). , As shown in the figure (B), the center of gravity position GR of the grouped scatter points is calculated (step S34). Next, as shown in FIG. 3C, the vector V _obj connecting the center of gravity position GR of each scatter point group and the origin is calculated (step S35).

The scope of grouping can be changed as appropriate depending on the content of the analysis. That is, all the scatter points guided to all the pixels forming the region of interest ROI may be grouped, or once all the scatter points are grouped, the scatter is statistically irregular (largely separated from the position of the center of gravity). You may remove the dots and then regroup them. Alternatively, if the ROI range is not appropriate and multiple substances are spread in the in-plane direction of the pixel, the scatter points will naturally spread or be separated, so that grouping can be performed at close scatter points. The ROI may be reset to, or the user or the automatic determination software may specify the grouping target range on the scatter point to perform grouping.

Next, the type and properties of the substance are identified or specified by comparing the vector V _obj with the reference data held in advance (step S36). In the reference data, for example, as a storage table, the three-dimensional inclination of the vector V _obj measured in advance according to the type and properties of the substance is stored together with the allowable width. Therefore, the substance can be identified depending on whether or not the slope of the calculated vector V _obj falls within the allowable range, and the vector information that becomes noise can be excluded. The identified information is stored (step S37).

This vector V _obj corresponds to an average vector obtained by averaging the directions of the three-dimensional line attenuation vectors (μ ₁ t, μ ₂ t, μ ₃ t) of each of the plurality of pixels forming the region of interest ROI (however, its length). Is normalized).

In step S15 described above, the three-dimensional scatter plot and the absorption vector length image can be presented and provided in various modes. For example, the data processor 35 may display the three-dimensional scatter diagram and the absorption vector length image separately on the display 38, or first display the three-dimensional scatter diagram and supplementarily display the absorption vector upon request from the user. A long image may be displayed, and vice versa. Further, at the request of the user, the range of grouping of scatter points may be redesignated or the range of ROI may be redesignated on the screen once displayed.
<Bone mineral quantification>

For example, when bone mineral quantification is performed on the back OB (finger) of the subject's hand, the process of FIG. 14 is executed by the data processor 35.

When YES, that is, bone mineral quantification is performed in step S51 of FIG. 14, the finger FG of the hand (for example, the portion between the second joint and the third joint, “skin / muscle, bone” has already been performed in step S10 described above. The region of interest ROI is set in the tomographic image IM _ALL of the designated cross section (a place that matches the plural material model of ", muscle / skin") (see FIGS. 13 (A) and 13 (B)). Here, in step 132 already described above, the three-dimensional line attenuation vectors (μ ₁ t, μ ₂ t, μ ₃ t) in each pixel PX of this region of interest ROI are calculated (see FIG. 13 (C)). .. This three-dimensional line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ t) is n-dimensional (here, three-dimensional) calculated by the pixel-specific vector calculation means functionally configured by steps S131 and S132 described above. ) Corresponds to the space vector.

Therefore, when performing bone mineral quantification, the data processor 35 performs the three-dimensional line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ t) of each pixel PX of the region of interest ROI by the calculation of steps S31 to S35 described above. The information indicating the vector V _obj (however, the length is normalized), which is the average vector of each of the scatter point groups obtained by using the above, is called from the image memory 36 to the own work area (step S52: FIG. 13). See (D)). In the case of this bone mineral quantification, as shown in the X-ray path IBn (FIG. 15), X-rays are transmitted in the order of "skin / muscle B part, bone A part, muscle / skin B part". The vector V _obj forms one group of scattering points determined by the synthetic characteristics of all the substances existing on the X-ray path IBn (however, it has a spread due to noise). From the vector V _obj , the direction of the representative vector (three-dimensional mass attenuation vector) representing the region of interest ROI can be known.

Further, the data processor 35 reads data indicating the absorption vector length forming the absorption vector length image already calculated for each pixel PX of the region of interest ROI from the image memory 36 into its own work area in step S135 (step S53). ). In the case of bone mineral quantification, this absorption vector length corresponds to the length of the three-dimensional line attenuation vector according to the above definition, and is the length of the X-ray transmitted through "skin / muscle, bone, muscle / skin". Approximately corresponds to pseudo (virtual) X-ray attenuation values.

Therefore, the data processor 35 calculates the average value of the absorption vector lengths for each read pixel PX (step S54). As a result, the average value of the lengths of the three-dimensional line attenuation vectors of the plurality of pixels PX forming the region of interest ROI can be found.

Therefore, the data processor 35 uses a three-dimensional vector having the direction of the vector obtained in step S52 and the average value of the absorption vector length obtained in step S54 as a three-dimensional representative vector (three-dimensional) representing the region of interest ROI. The average of the line attenuation vector; hereinafter referred to as a three-dimensional representative vector) is calculated as V _obj-d (step S55: see FIG. 13 (E)).

As a modification for calculating the three-dimensional representative vector (average of the three-dimensional line attenuation vector) V _obj-d that can be carried out in this step S55, the three-dimensional line attenuation vector (μ ₁ t, μ ₂ t, μ ₃ ). It is also possible to use the vector averaging method of averaging each element of the three-dimensional line attenuation vector itself for a plurality of pixels forming the grouping region described above for t).

As can be seen from FIG. 15, this three-dimensional representative vector V _obj-d is the total when the soft tissue of "skin / muscle B", the hard tissue of "bone A", and the "skin / muscle B" are sequentially transmitted. Contains X-ray attenuation information. On the other hand, the information desired for bone mineral quantification is information on the bone itself surrounded by skin and muscle (bone density, bone mass). From this point of view, this 3D representative vector V _obj-d contains extra X-ray attenuation information due to skin and muscle.

Therefore, the data processor 35 reads out, for example, the three-dimensional reference vector V _ref set and stored in advance in the ROM 33 (see FIG. 13 (F): step S56). This three-dimensional reference vector V _ref is a three-dimensional equivalent to the line attenuation value of the skin and muscle when it is assumed that X-rays are transmitted only through the skin and muscle (see the path IP shown by the virtual line in FIG. 15). It is a reference vector of, and is estimated and measured in advance. Instead of this preliminary estimation / measurement, at almost the same time when calculating the three-dimensional representative vector V _obj-d , the ROI: It is also possible to set the ROI _ref (see FIG. 13 (A)) and calculate the three-dimensional reference vector V _ref in the same manner as the above-mentioned calculation of the three-dimensional representative vector.

Specifically, this 3D reference vector V _ref is i) estimated from the external size including the thickness of the target X-ray irradiation site or weight, or ii) statistically collected in advance and stored in the database. Read from the converted reference table, iii) The 3D reference vector V, which is considered to be equivalent to the line attenuation vector in the partial region of the target imaging site, which is only the skin and muscles, and is obtained and stored in advance. Call _ref (three dimensions have dimensions of μ ₁ t, μ ₂ t, μ ₃ t), or, as mentioned above, iv) a partial region of the subject's imaging site that is only the skin / muscle (3D). For example, it is set by calculating the three-dimensional reference vector V _ref on the assumption that it is equivalent to the line attenuation vector in the region indicated by ROI _ref (see FIGS. 13 (A) and 15). When performing the calculation shown in item iv, it is necessary to read and write the image data, and not only the data read from the ROM 33 but also the RAM 34 is naturally used, and the calculation is performed by the data processor 35.

The size of this three-dimensional reference vector V _ref is usually considerably smaller than that of the three-dimensional representative vector V _obj-d , but it is an amount that must be surely excluded in order to perform accurate bone mineral quantification. Is.

Therefore, the data processor 35 subtracts the reference vector V _ref on the three-dimensional coordinates from the representative vector V _obj-d that represents the region of interest ROI that has already been obtained (step S57). By this vector subtraction, a three-dimensional vector V _obj-d ′ that substantially reflects the X-ray attenuation information of only the target finger bone A can be obtained. This three-dimensional vector V _obj-d ´ is called an objective vector. Therefore, this objective vector V _obj- d'represents the entire area of interest ROI set on the tomographic image of the designated cross section of the finger FG, has an average line attenuation value as the vector length, and is a mass attenuation vector. It has a three-dimensional vector direction that reflects information. Therefore, this objective vector V _obj- d'is information that reflects the state of bone mass and bone quality when quantifying bone mineral through the bone of a finger. Specifically, according to the simulation conducted by the inventors, the length of the target vector V _obj-d ′ strongly reflects the bone mass (bone mineral content) only in the bone region, and the vector direction is that of the bone. It is presumed that it strongly reflects the bone quality of only the site.

Next, the data processor 35 performs a process of visualizing the vector length and vector direction of the above-mentioned target vector V _obj-d ′ to display and save the data, or presents only the data of the bone mineral quantification result. Do that (step S58). This visualization provides easy-to-read bone mineral quantification information to an image interpreter or a patient, and color imaging, its display, and quantification are typical.

In particular, in foreign matter detection, it is possible to display the image as an effective atomic number image by displaying the image in color. For example, when a foreign substance is mixed in a product having a relatively uniform substance (for example, chocolate, cereal, milk powder, etc.), a substance other than the substance of the product may be displayed in color. Foreign matter can be detected.
<Action effect>

As described above, according to the X-ray inspection system according to the present embodiment, the three-dimensional line attenuation vector (μ ₁ t) of each pixel PX obtained by the photon counting type X-ray detection, which has already been proposed by the present inventors. , Μ ₂ t, μ ₃ t) can be used to more accurately quantify bone information (bone mass (bone mineral content), bone quality) for bone diagnosis, which is also an aspect of searching for the properties of substances.

According to this embodiment, a subject OB (eg, a patient) consisting of substantially two types of known substances A (bone (hard tissue)) and B (skin / muscle (soft tissue)) with respect to the transmission characteristics of continuous X-rays. Processing based on the count values in each of the three X-ray energy regions Bin ₁ to Bin ₃ in which the X-rays irradiated to the instep of the hand or foot and transmitted through the object are detected by the detector 24 having a plurality of pixels. Is done.

Specifically, an X-ray image of the target OB is created based on the counted value and displayed on the display 38. On the X-ray image displayed on the display 38, ROI (region of interest) is set for the same bone portion in the direction of the X-ray path.

Further, each of the three energy regions corresponds to the line attenuation value when the X-ray passes through the object, and the three-dimensional space vector (three-dimensional line attenuation vector) of each of the plurality of pixels is a photon. It is calculated based on the counting data. Further, the three-dimensional representative vector V _obj-d representing the ROI is calculated by averaging the directions and sizes of the space vectors of each of the plurality of pixels. Of the two types of substances A and B, the three-dimensional reference vector Vref corresponding to the line subtraction value of the substance B equivalent to the line subtraction value when it is assumed that one of the substances B is transmitted by X-rays is of interest. Subtracting from the representative vector V _obj-d of the region ROI, the target vector V _obj-d ′ equivalent only to the substance A corrected by the subtraction is obtained, at which time the reference vector V _ref is theoretically or It is set (estimated / evaluated) in advance by experiments, etc., and is kept readable.

In the determination of the reference vector V _ref , the portion composed of only the substance B from the X-ray image of the target OB displayed on the display 38 is set as the region of interest ROI _ref for the reference vector determination, and the determination thereof is performed. After calculating the 3D line attenuation vector of the part, the correlation information of the thickness of the material B of the ROI part and the ROI _ref part (may be actually measured or statistically determined and retained from the previous experiment). Therefore, the magnitude of the three-dimensional line attenuation vector of the ROI _ref portion may be adjusted to estimate or calculate the reference vector (three-dimensional line attenuation vector V _ref of only the substance B of the ROI portion). In particular, if the thickness of the target OB in the part where the three-dimensional representative vector V _obj-d is calculated by actual measurement and the thickness of the target OB in the part where the reference vector V _ref is calculated are known, the target vector V _obj- d'is used. It can be calculated analytically.

The above-mentioned objective vector V _{obj-d'reflects} the degree of attenuation of continuous X-ray photons having a continuous energy distribution from low energy to high energy as they pass through the tissue of the bone part. It is possible to collect count values that more accurately represent the density and condition (property) of bone quality. Moreover, even if the ROI portion contains the substances A and B, the target vector reflecting the line attenuation of only the target substance A can be extracted with higher accuracy by a simple operation called vector subtraction.

That is, in the conventional case, even if the types of substances A and B are known and their total thickness is constant, the thickness in the X-ray path direction of each is unknown and there are two different substances. Therefore, it is difficult to obtain the vector information based on the X-ray attenuation of only the target substance A by simple calculation and with high accuracy.

However, according to the present embodiment, the target vector reflecting the line attenuation of only the target substance A can be easily and accurately performed by the vector calculation for each region of interest.

Further, according to the present embodiment, when performing bone diagnosis (including bone mineral quantification), an objective vector indicating at least the properties of the substance A can be obtained for each region of interest, so that the length or direction of the vector is the bone mass or It can provide more multifaceted information about bone quality. Unlike the conventional process of providing information based only on bone density, it is possible to enrich the provided property information and meet the demands for diagnosis and treatment of osteoporosis, for example.

Furthermore, the information of the 3D reference vector can be stored in advance by a relatively simple method. That is, as described above, i) estimate from the external size or weight including the thickness of the target X-ray irradiation site, or ii) read from the reference table statistically collected in advance and compiled into a database. iii) Set by calling a reference vector that is considered to be equivalent to the line attenuation vector in a partial region that is only the substance B in the imaging site of the target and is obtained and stored in advance. It's fine. In this case, the operation required for vector subtraction (that is, the operation for obtaining the reference vector) can be further simplified.

Furthermore, the direction itself of the 3D reference vector may be stored in advance with the direction information that has been empirically acquired, and may be called when necessary. This makes the amount of operation of the reference vector extremely simple.

Further, if the thickness of the OB to be inspected is appropriately measured and used for estimation or calculation of the 3D line attenuation vector (representative vector) V _obj-d or the 3D reference vector V _ref , depending on the application situation, it may be used. Although the amount of calculation increases, on the other hand, the quantitative accuracy can be improved.
<Other effects>

In addition to the above-mentioned action and effect of bone mineral quantification, various actions and effects can be obtained according to the X-ray inspection system according to the present embodiment.

First, the region of interest is set in the focused tomographic image (image) of the cross section (or uneven cross section) of the inspection target OB, and from the image, the substance of interest (likely the inspection target or foreign matter) existing in the region of interest. The pixel information (background component) that is the background of the object is removed. Based on the data of the tomographic image after this removal and the count value for each X-ray energy region and each pixel in the region of interest, the unique transmission characteristic of the substance of interest to X-rays (for example, the line attenuation coefficient μ) is unique to each pixel. Calculated as information. Since this unique information does not depend on the thickness t of the substance, the type and properties of the substance of interest can be identified or specified based on this information. For example, a substance can be identified by comparing the calculated eigeninformation with known eigeninformation (known eigenvector information unique to a substance (information having a certain permissible range)) held in advance. ..

Also, depending on the setting of the area of interest, it is possible to adjust the range in which the substance is to be identified to the whole or part of the inspection target. At this time, since this unique information can be obtained as information unique to the type and properties (state) of the substance that is not affected by the thickness t, the area of interest can be selected as long as the type and properties of the substance do not change. It may be set to an appropriate size regardless of the change in the size. Unlike conventional substance identification, since background components that are unnecessary information for substance identification are removed and then unique information is obtained, substance identification can be performed with higher accuracy and its reliability is improved.

More specifically, it is possible to normalize the vector consisting of the line attenuation coefficient μ for each energy region and present a three-dimensional scatter plot on the spherical surface. This scatter point (spectrum) represents the three-dimensional slope information (that is, the specific information of the substance) of the vector. Therefore, just by looking at the state of this scatter point, it is possible to determine whether the inspection target OB is, for example, metal or something else, and whether the inspection target OB has something different (foreign matter, etc.). It is easy to grasp visually and quantitatively by adding information such as the state of (what ratio of muscle and fat is) by finding the center of gravity of the scatter point with variation.

In addition, in the process of obtaining a three-dimensional scatter plot, data of an absorption vector length image is also obtained. The present inventors have stated that this absorption vector length image is less dependent on the energy spectrum shape of the irradiated X-ray than the conventional X-ray absorption image, and that the thickness of the muscle and cartilage is gradually changed. I'm checking using. The spectrum shape is, for example, as illustrated in FIG. 2, a spectrum shape in which the counting frequency of X-ray photons in the energy region Bin ₂ in the middle is higher than that on both sides thereof. In the case of this embodiment, since the processing of the equation (8) according to the above-described embodiment is performed, the difference in X-ray absorption depending on the spectrum shape is unlikely to occur, and the counting on the low energy side having the largest linear attenuation coefficient. This is thought to be because the effect of frequency on the image is stable.

Therefore, this absorption vector length image is more robust to X-ray irradiation conditions such as X-ray tube voltage because the shape dependence of the energy spectrum is small, has good image contrast, and is proportional to the line attenuation value μt. Then, the line attenuation value μt of all energy bands (the noise is superimposed on each pixel and the line attenuation value of each energy band reflecting the quantization noise existing in the count value for each energy band) is averaged. Since it is effective, noise is reduced.
<Modification example>
Further, another modification of a method of actually measuring the thickness of the target OB to improve the evaluation accuracy of the bone diagnosis of the substance B will be described.

As schematically shown in FIG. 15, among the target OBs, the measured thicknesses of a plurality of substances in the region of interest ROI for which the line attenuation vector is calculated are t, and the thickness of the substance A to be calculated for the target vector is t. _1. Let the thickness of the substance B corresponding to the reference vector be t ₂ (= t ₂₁ + t ₂₂ ). Then, each three-dimensional line attenuation vector can be expressed as follows.
ROI 3D line attenuation vector:
μt = (μ ₁ t, μ ₂ t, μ ₃ t) ‥‥ (A.1)
3D reference vector:
V _ref = μ _ref t ₂ = (μ 1 _ref t ₂ , μ 2 _ref t ₂ , μ 3 ref t ₂ ) _‥‥ (A.2)
3D objective vector:

V _obj-d '= μ _obj- d't ₁ = (μ _1obj- d't ₁ , μ _2obj- d't ₁ , μ _3obj-d't ₁ )
‥ (A.3)

Here, from the definition, V _obj-d '= μt-V _ref , so it can be expressed as follows for each element of the vector using the equations (A.1) to (A.3). can.
μ _1obj-d't ₁ = μ ₁ t --μ _1ref t ₂ ‥‥ (A.4)
μ _2obj-d't ₁ = μ ₂ t _{--μ 2ref} t ₂ ‥‥ (A.5)
μ _3obj-d't ₁ = μ ₃ t _{--μ 3ref} t ₂ ‥‥ (A.6)
Furthermore, from the assumption of the multi-material model, there is the following relationship.
t = t ₁ + t ₂ ‥‥ (A.7)

Here, the relationship between the thickness t ₃ of the substance B in the region of interest ROI _ref and the thickness t ₂ of the substance B in the region of interest ROI when the line attenuation coefficient of the three-dimensional reference vector is determined is clarified. In this case, since t ₃ is actually measured, t ₂ is known. Furthermore, since μ _1ref , μ _2ref , and μ _3ref are known from the calculation of the region of interest ROI _ref , in that case, independent equations (A.4) to (A.7) exist and are unknown. There are four variables of μ _1obj-d ', μ _2obj-d ', μ _3obj-d ', and t ₁ , which can be solved a priori.

Therefore, for example, when photographing a human hand (the ROI part is a finger), the region of interest ROI and ROI _ref are designed to photograph the same region even if the patient changes, and the data is accumulated to accumulate the region of interest. It is desirable to statistically process the relationship between the thickness t ₃ of the substance B in the ROI _ref portion and the thickness t ₂ of the substance B in the region of interest ROI so that it can be estimated accurately. More directly, the direction of X-ray photography may be changed to directly measure the thickness t ₁ of the finger bone (substance A). In this case, even if t ₂ is not estimated, there are four unknown variables, which can be solved a priori.

In the present invention, for example, only a configuration for carrying out bone mineral quantification may be adopted. That is, the X-ray examination system of the above-described embodiment is provided as a system specialized in bone mineral quantification, and the data processing device 12 is provided as a data processing device specialized in bone mineral quantification.

Although various aspects of the data processing apparatus, the data processing method, and the X-ray inspection apparatus according to the present invention have been described above, the present invention is, of course, not limited to the above-mentioned examples, and the gist of the claims. It can be changed to various modes without departing from the above.

10 X-ray inspection system (X-ray inspection device equipped with a data processing device: X-ray inspection device that implements the data processing method)
12 Computer system (data processing device)
21 X-ray tube 24 Detector 25 Data acquisition circuit 26 Detection unit 12 Data processing device 32 Buffer memory (storage means)
33 ROM
34 RAM
35 data processor (CPU)
36 Image memory (storage means)
37 Input device 38 Display device OB Inspection target (object)

Claims

Continuous X-rays containing n (n is a positive integer of 2 or more) different energy regions are applied to an object consisting of substantially two kinds of substances A and B with respect to the transmission characteristics of the X-rays. In a data processing device that performs processing based on the photon counting data when the X-ray transmitted through the X-ray is detected as photon counting data by an X-ray detector having a plurality of pixels.
An X-ray image display means that creates an X-ray image of the target based on the photon count data detected by the X-ray detector and displays it on a monitor.
An ROI setting means for setting an ROI (region of interest) in a portion of the X-ray image displayed on the monitor where the substances A and B are presumed to be present in the direction of the X-ray path. ,
The photon count data corresponds to the line attenuation value when the X-ray is transmitted through the object in each of the n energy regions, and the space vector of the n dimensions of each of the plurality of pixels is obtained. Vector calculation means for each pixel that calculates based on
A representative vector calculation means for averaging the directions and sizes of the space vectors of each of the plurality of pixels to calculate a representative vector representing the ROI.
The n-dimensional reference corresponding to the line attenuation value of the substance B equivalent to the line attenuation value when it is assumed that the X-ray is transmitted through one of the two types of substances A and B. A reference vector holding means that estimates or assumes a vector and holds it,
An objective vector acquisition means for acquiring an objective vector corrected by the subtraction by subtracting the n-dimensional reference vector from the n-dimensional objective vector corresponding to the line attenuation value equivalent only to the substance A.
A data processing device characterized by being equipped with.
The data processing apparatus according to claim 1, further comprising a reference vector calculation means for estimating or assuming the n-dimensional reference vector.
The representative vector calculation means is
A direction calculation means for obtaining a distribution obtained by normalizing the magnitude of the space vector of each of the plurality of pixels and calculating the direction of the representative vector from the position of the center of gravity of the distribution.
A size setting means for setting the size of the representative vector by averaging the vector length pixel value or the average vector length pixel value, which is the size of the space vector of each of the plurality of pixels.
The data processing apparatus according to claim 1 or 2, wherein the data processing apparatus is provided.
An image data creation means for creating image data based on the corrected target vector information, and an image data creation means.
The data processing apparatus according to any one of claims 1 to 3, further comprising an image display means for displaying image data created by the image data creation means as an image.
The subject is the hand or foot of a human or animal,
The substance A is the tissue of the bone portion of the hand or toe.
The substance B is a tissue of the muscle and skin of the hand or finger.
The fourth aspect of claim 4, wherein the image data creating means is configured to create image data representing information on the bone density of the bone portion from the information of the target vector of the bone portion. Data processing device.
The reference vector calculation means estimates the reference vector from the external size or weight including the thickness of the X-ray irradiation site of the target, ii) a reference table statistically collected in advance and compiled into a database. Read from, iii) Call the pre-obtained and stored reference vector that is considered to be equivalent to the line attenuation vector in the partial region of the subject imaging site that is only the substance B, or iv) The invention according to any one of claims 2 to 5, wherein the calculation is performed on the assumption that it is equivalent to the line attenuation vector in the partial region of the target imaged portion, which is only the substance B. Data processing device.
The data processing apparatus according to any one of claims 1 to 6, wherein the n-dimensional is three-dimensional.
The X-ray device is characterized in that the data processing device according to any one of claims 1 to 7 is integrally incorporated or is incorporated in a collaborative manner by communication.
Continuous X-rays containing n (n is a positive integer of 2 or more) different energy regions are applied to an object consisting of substantially two known substances A and B with respect to the transmission characteristics of the X-rays. In a data processing method that performs processing based on the detected data when the X-ray transmitted through the target is detected as detection data by an X-ray detector having a plurality of pixels.
An X-ray image of the target is created based on the photon count data detected by the X-ray detector and displayed on a monitor.
On the X-ray image displayed on the monitor, ROI (region of interest) is set in the portion where the substances A and B are presumed to be present in the direction of the X-ray path.
The photon count data corresponds to the line attenuation value when the X-ray is transmitted through the object in each of the n energy regions, and the space vector of the n dimensions of each of the plurality of pixels is obtained. Calculated based on
The direction and size of the space vector of each of the plurality of pixels are averaged to calculate a representative vector representing the ROI.
Of the two types of substances A and B, the substance B equivalent to the line subtraction value held in advance estimated or evaluated when it is assumed that the X-ray has transmitted through one of the substances B. The n-dimensional reference vector corresponding to the line attenuation value is subtracted from the n-dimensional target vector corresponding to the line attenuation value equivalent only to the substance A, and the target vector corrected by the subtraction is obtained.
A data processing method characterized by that.
The reference vector is the n-dimensional vector information prepared in advance, and is
i) Estimate from the external size or weight including the thickness of the X-ray irradiation site of the target, or ii) Read from the reference table statistically collected in advance and compiled into a database, iii) The imaging site of the target In the partial region that is only the substance B in the above, it is considered to be equivalent to the line attenuation vector and is read out from the information obtained and stored in advance, or iv) the substance in the imaging site of the target. The data processing method according to claim 9, wherein the calculation is performed on the assumption that the partial region is only B, which is equivalent to the line attenuation vector.
The data processing method according to claim 9, wherein the n-dimensional is three-dimensional.