阅读说明：本技术 用于确定多能量x射线成像设备的虚拟输出的方法和系统 (Method and system for determining virtual output of multi-energy x-ray imaging device ) 是由 卡里姆·S·卡里姆 塞巴斯蒂安·洛佩兹·毛里诺 希纳·甘巴尔扎德 于 2019-06-10 设计创作，主要内容包括：本公开涉及一种用于确定多能量x射线设备的虚拟输出的方法和设备。基于x射线设备正用于的应用,可以确定或选择通用算法。可以将从x射线设备接收的输入代入通用算法,以生成x射线设备的虚拟输出算法。然后可以使用该虚拟输出算法来计算虚拟输出。(The present disclosure relates to a method and apparatus for determining a virtual output of a multi-energy x-ray device. The general algorithm may be determined or selected based on the application for which the x-ray device is being used. Inputs received from the x-ray device can be substituted into the general algorithm to generate a virtual output algorithm for the x-ray device. The virtual output algorithm may then be used to compute a virtual output.)

1. A method of determining at least one virtual output of a multi-energy x-ray imaging device:

receiving a plurality of outputs generated by different x-ray spectra from the multi-energy imaging device;

determining a generic algorithm based on an x-ray imaging device application, physical properties of the x-ray imaging device, or x-ray source exposure settings;

substituting the plurality of outputs as inputs into the general algorithm to determine parameters and generate a virtual output algorithm for the multi-energy x-ray imaging device and the determined application; and

generating the at least one virtual output using the virtual output algorithm.

2. The method of claim 1, wherein the plurality of outputs received from the multi-energy x-ray imaging device are obtained from some or all layers of the multi-energy x-ray imaging device;

wherein the multi-energy x-ray imaging device is a single shot multi-slice x-ray imaging device.

3. The method of claim 1, wherein the plurality of outputs received from the multi-energy x-ray imaging device are obtained from two or more x-ray exposures taken at different x-ray source exposure settings;

wherein the multi-energy x-ray imaging device is a multi-shot x-ray imaging device.

4. The method of claim 3, wherein the x-ray source exposure settings comprise source voltage, source current, or source filtering.

5. The method of claim 1, wherein determining the generic algorithm comprises:

determining an x-ray application, wherein the multi-energy x-ray imaging device is being used for the x-ray application; and

selecting the generic algorithm based on the determined application.

6. The method of claim 5, wherein selecting the generic algorithm comprises:

selecting for multi-slice x-ray imaging deviceAs the general algorithm (where a, b and c are parameters, S_iFor the signal at each layer and l_iIs a defined number of layers).

7. The method of claim 5, wherein selecting the generic algorithm comprises:

selecting for multi-slice x-ray imaging deviceAs the general algorithm (where b and c are parameters, S)_iFor the signal at each layer and l_iIs a defined number of layers).

8. The method of claim 5, wherein selecting the generic algorithm comprises:

selecting for multi-slice x-ray imaging deviceAs the general algorithm (where, b and c are parameters,thickness of pre-filtering for scintillator of each layer and t_iIs the scintillator thickness of the layer).

9. The method of claim 5, wherein determining the generic algorithm comprises:

a minimization algorithm is selected as the generic algorithm.

10. The method of claim 1, wherein utilizing the virtual output algorithm comprises:

obtaining a virtual output having a noise component less than an output obtained from the multi-energy x-ray imaging device.

11. The method of claim 1, wherein utilizing the virtual output algorithm comprises:

obtaining a virtual output having a smaller component of scattered radiation of the object than the output obtained from the multi-energy x-ray imaging device.

12. The method of claim 2, wherein some or all of the at least one virtual output generated by the virtual output algorithm is used to correct for faulty array pixels, faulty rows, or faulty regions in one or more sensor layers of the multi-layer x-ray imaging device.

13. The method of claim 1, wherein some or all of the at least one virtual output generated by the virtual output algorithm is used to obtain bone mineral density or bone mineral area density measurements.

14. An x-ray imaging system for determining at least one virtual output of the x-ray imaging system, comprising:

an x-ray source;

a multi-energy x-ray imaging device comprising at least one sensor layer;

a processor for receiving a plurality of inputs from the x-ray imaging device and for determining at least one virtual output of the x-ray imaging device, the processor further comprising a computer readable medium having instructions stored therein that, if executed, cause the processor to:

determining a generic algorithm based on an x-ray imaging device application, physical properties of the x-ray imaging device, and/or exposure settings of the x-ray source;

substituting a plurality of outputs of the multi-energy x-ray imaging device as inputs into the generic algorithm to determine parameters of a virtual output algorithm for the x-ray imaging device and the determined application; and

generating the at least one virtual output using the virtual output algorithm.

15. The x-ray imaging system of claim 14, wherein the multi-energy x-ray imaging device comprises:

a set of sensor layers.

16. The x-ray imaging system of claim 15, wherein the multi-energy x-ray imaging device comprises:

at least two sensor layers.

17. The x-ray imaging system of claim 16, wherein the multi-energy x-ray imaging device further comprises:

at least one intermediate filter layer between at least two of the at least two sensor layers.

18. The x-ray imaging system of claim 17, wherein the intermediate filter layer comprises a metallic material filter, a photoconductor layer, or a scintillator layer.

19. The x-ray imaging system of claim 16, wherein the multi-energy x-ray imaging device further comprises:

at least one anti-grid layer between at least two of the at least two sensor layers.

20. The x-ray imaging system of claim 15, wherein each of the at least one sensor layer comprises:

a photoconductor layer or a scintillator layer.

21. The x-ray imaging system of claim 20, wherein the photoconductor layers or scintillator layers of adjacent sensor layers are adjacent to each other.

22. The x-ray imaging system of claim 16, wherein at least one of the sensor layers comprises a scintillator-implanted glass substrate layer.

23. The x-ray imaging system of claim 16, wherein at least one of the sensor layers comprises a flexible substrate layer and an x-ray absorber.

Technical Field

The present disclosure relates generally to x-ray imaging, and more particularly to a method and system for determining a virtual output of a multi-energy x-ray imaging device.

Background

The quality of a medical image and by extension its value as a tool depends only on the extent to which it can convey the anatomy of the patient being imaged to a viewer, such as a physician. The better the anatomy is understood, the more accurate the information the physician has for making the decision.

In x-ray imaging, a large source of noise that often degrades image quality is anatomical noise. It is caused by the superposition of normal anatomy derived from two-dimensional (2D) projections of a three-dimensional (3D) patient. Such noise may obscure the tissue being imaged or may be misread as an anatomical abnormality. A simple example of this is a chest film taken for the purpose of assessing the lung anatomy, which is inevitably obscured by ribs in the acquired image. In this case, ribs are the main source of anatomical noise, since they are not the anatomy of interest.

One proposed technique to reduce anatomical noise is Dual-Energy (DE) imaging. This technique exploits the fundamental properties of x-ray and substance interactions: not only will different tissue types have different mass attenuation coefficients (μ/ρ (E)) over the diagnostic energy range, but the rate of change of these coefficients will also be different.

One challenge in DE imaging comes from the need to obtain two separate low and high energy images. To achieve this, at the low end of the diagnostic range for Low Energy (LE) images, and at the high end for High Energy (HE) images, the x-ray spectrum absorbed at the detector should be heavily weighted. DE imaging can decompose a patient's projections into images of only soft tissue and only hard tissue. There are several mathematical methods for obtaining these DE images from the LE and HE inputs, most notably logarithmic subtraction and fundamental decomposition.

In practice, complete deletion of a particular organization type is often not possible. Several factors contribute to the formation of non-ideal scenarios that cannot be captured by mathematical techniques. These include: a broad spectrum of x-ray flux that will cause each image to be formed, as opposed to idealized sources used in mathematical analysis; inhomogeneity in the density or mass attenuation coefficient of the tissue being removed, which makes it impossible to determine the exact value that should be used in calculating the weighting factor; and x-ray scatter from both the object being imaged and the detector that is not interpreted by the specific law of beer lambertian. These non-idealities also mean that the theoretical values of the weighting factors may not provide the best possible deletion, requiring the observer to calculate their ideal values experimentally or qualitatively.

This spectral separation is achieved in practice in two fundamentally different ways: the source spectrum is different for the two images (referred to herein as multi-shot DE imaging), or the detector selectively absorbs different portions of the broader spectrum to form each image (referred to herein as single-shot DE imaging). Regardless of the method used, a large separation of the two spectra is necessary in obtaining high quality tissue-selective images.

One way to obtain images at different energies is to acquire them sequentially in time, not changing parts of the imaging system, but changing the spectrum generated by the x-ray tube. This is a concept behind multiple imaging (sometimes referred to as kVp-switched) in which a first image is taken using a low x-ray tube kVp and, immediately thereafter, a second image is obtained with a high kVp. Since the low kVp beam and the high kVp beam will have different effective energies, the two images obtained will contain primarily the information obtained in the low and high ends of the x-ray diagnostic spectrum, respectively. Alternatively, instead of modifying the source kVp between exposures, the source filtering may be changed by quickly moving the spectral filter in and out of the beam path. This will have the effect of presenting two different spectra to the detector, taking into account the selective nature of the source filtered energy spectrum.

This approach can also be extended to multi-energy images by obtaining several consecutive images at different kVp values or source filters, which then allows more spectral information to algorithmically generate an enhanced image.

Unfortunately, the time intervals inherent in this technique result in motion artifacts appearing in the final image, which can pose significant challenges to the radiologist or observer interpreting it. These artifacts are significant distortions in the images caused by slight misalignments of the anatomy in successive images and are typically due to patient or object motion that occurs during and between image acquisitions.

Ideally, the source tube voltage can be changed instantaneously so that once an exposure is completed, the next time can begin. However, currently commercially available sources require at least 150ms to 200ms intervals between successive exposures. This is not only due to the varying voltage, but also because the tube current needs to be changed to achieve the desired relative intensity of the image. While this interval is short enough for most patients to avoid large movements, cardiac, respiratory, and small muscle movements are constrained to occur throughout the interval. Due to these movements, motion artifacts will appear, which may be a particular obstacle in the imaging of the heart and lungs due to the large area of the heart. Furthermore, this problem will be exacerbated as more image acquisitions are added in multi-energy imaging to allow for more patient motion, as the total acquisition time will increase.

There are alternative methods for obtaining multi-energy images, which are commonly referred to as single shot imaging. This approach takes the opposite way to multi-shot imaging and achieves spectral separation at the detector rather than at the source. This is achieved by vertically stacking two sensor layers to form a two-layer detector known as a sandwich configuration. One layer (such as the top layer) absorbs primarily LE x-rays, while the second or bottom layer absorbs HE x-rays. Thus, using this technique, only a single exposure is required, which is performed at a higher kVp to allow coverage of the large spectrum of both LE and HE x-rays. The method extends from this to a multi-layer detector that can obtain multiple images of increased effective energy at subsequent stacked layers.

A practical problem with the single shot approach is that in order to obtain the desired effective energy separation between these layers, the mass loading (or equivalently, their thickness) of the sensitive materials (which are scintillators or direct conversion materials) must be tailored to the particular tissue type and patient anatomy. Since at the commercial level it is feasible to build only a few specific configurations, this leaves a compromise solution that can best fit all target applications and patient types to the only practical application.

Accordingly, a novel method and apparatus for mitigating or overcoming at least one of the disadvantages of the imaging methods and apparatus described above is provided.

Disclosure of Invention

In one aspect of the disclosure, a method of determining at least one virtual output of a multi-energy x-ray imaging device is provided, the method comprising: receiving a plurality of outputs generated by different x-ray spectra from the multi-energy imaging device; determining a generic algorithm based on the x-ray imaging device application, physical properties of the x-ray imaging device, or x-ray source exposure settings; substituting the plurality of outputs as inputs into the general algorithm to determine parameters and generate a virtual output algorithm for the multi-energy x-ray imaging device and the determined application; and generating at least one virtual output using the virtual output algorithm.

In another aspect, the plurality of outputs received from the multi-energy x-ray imaging device are obtained from some or all of the layers of the multi-energy x-ray imaging device; the multi-energy x-ray imaging device is a single shot multi-slice x-ray imaging device. In a further aspect, the plurality of outputs received from the multi-energy x-ray imaging device are obtained from two or more x-ray exposures taken at different x-ray source exposure settings; the multi-energy x-ray imaging device is a multi-shot x-ray imaging device. In another aspect, the x-ray source exposure settings include source voltage, source current, or source filtering. In yet another aspect, determining a generic algorithm comprises: determining an x-ray application for which the multi-energy x-ray imaging device is being used; and selecting a generic algorithm based on the determined application.

In another aspect, selecting a generic algorithm comprises: device alternatives for multi-slice x-ray imagingSelected fromAs the general algorithm (where a, b and c are parameters, S_iFor the signal at each layer and l_iIs a defined number of layers). In another aspect, selecting a generic algorithm comprises: selecting for multi-slice x-ray imaging deviceAs the general algorithm (where b and c are parameters,thickness of pre-filtering for scintillator of each layer and t_iIs the scintillator thickness of the layer). In another aspect, determining a generic algorithm comprises: the minimization algorithm is chosen as the general algorithm.

In yet another aspect, utilizing a virtual output algorithm includes: a virtual output is obtained having a noise component less than an output obtained from the multi-energy x-ray imaging device. In one aspect, utilizing a virtual output algorithm comprises: a virtual output is obtained having a smaller component of scattered radiation of the object than the output obtained from the multi-energy x-ray imaging device. In one aspect, some or all of the at least one virtual output generated by the virtual output algorithm is used to correct a faulty array pixel, faulty row, or faulty region in one or more sensor layers of the multi-layer x-ray imaging device. In yet another aspect, some or all of the at least one virtual output generated by the virtual output algorithm is used to obtain a bone mineral density or bone mineral area density measurement.

In another aspect of the present disclosure, there is provided an x-ray imaging system for determining at least one virtual output of the x-ray imaging system, the x-ray imaging system comprising: an x-ray source; a multi-energy x-ray imaging device comprising at least one sensor layer; a processor for receiving a plurality of inputs from the x-ray imaging device and for determining at least one virtual output of the x-ray imaging device, the processor further comprising a computer readable medium having instructions stored therein that if executed cause the processor to: determining a generic algorithm based on the x-ray imaging device application, physical properties of the x-ray imaging device, and/or exposure settings of the x-ray source; substituting a plurality of outputs of a multi-energy x-ray imaging device as inputs into a general algorithm to determine parameters of a virtual output algorithm for the x-ray imaging device and the determined application; and generating at least one virtual output using the virtual output algorithm.

In another aspect, a multi-energy x-ray imaging device includes a set of sensor layers. In yet another aspect, the multi-energy x-ray imaging device includes at least two sensor layers. In yet another aspect, the multi-energy x-ray imaging device further includes at least one intermediate filter layer between at least two of the at least two sensor layers. In yet another aspect, the intermediate filter layer comprises a metallic material filter, a photoconductor layer, or a scintillator layer. In yet another aspect, the multi-energy x-ray imaging device further includes at least one anti-grid layer between at least two of the at least two sensor layers.

In one aspect, each of the at least one sensor layers includes: a photoconductor layer or a scintillator layer. In another aspect, the photoconductor layers or scintillator layers of adjacent sensor layers are adjacent to each other. In a further aspect, at least one of the sensor layers includes a glass substrate layer in which a scintillator is implanted. In yet another aspect, at least one of the sensor layers includes a flexible substrate layer and an x-ray absorber.

Drawings

Embodiments of the present disclosure will now be described, by way of example only, with reference to the accompanying drawings.

FIG. 1 is a schematic diagram of a three-layer x-ray imaging apparatus;

FIG. 2a is a schematic view of a multi-slice x-ray imaging apparatus, with FIG. 2a showing an x-ray imaging apparatus having two or more slices;

FIG. 2b is a schematic diagram of a multi-shot x-ray imaging apparatus, FIG. 2b shows an x-ray imaging system obtaining two or more exposures at different source voltages, currents, and/or filtering;

FIG. 3a is a flowchart outlining a method of determining a virtual image output of a multi-energy x-ray imaging device;

FIG. 3b is a flowchart outlining a method of determining a virtual layer output of a multi-layer x-ray imaging device;

FIG. 3c is a flowchart outlining a method of determining a virtual energy output of a multi-x-ray imaging device;

FIG. 4a is a graph summarizing an example total signal versus scintillator filtering;

FIG. 4b is a graph of an example equation fit for sample outputs of a three-layer detector;

FIG. 5 is a schematic diagram of an indirect n-layer x-ray imaging device and a direct n-layer x-ray imaging device;

FIGS. 6a and 6b are schematic diagrams of different embodiments of an indirect 2-layer x-ray imaging device and a direct 2-layer x-ray imaging device;

FIGS. 7a and 7b are schematic diagrams of different embodiments of an indirect 3-layer x-ray imaging device and a direct 3-layer x-ray imaging device;

FIG. 8 shows a general schematic of a radiographic imaging environment;

FIG. 9 shows a two-dimensional active matrix imaging array structure;

FIG. 10a is a schematic diagram of an indirect n-layer x-ray imaging device with intermediate filters between layers, and a direct n-layer x-ray imaging device with intermediate filters between layers;

10b and 10c are schematic diagrams of different embodiments of an indirect 3-layer x-ray imaging device with intermediate filters between some layers and a direct 3-layer x-ray imaging device with intermediate filters between some layers;

FIG. 11a is a schematic diagram of an indirect n-layer x-ray imaging device with an anti-scatter grid between layers, and a direct n-layer x-ray imaging device with an anti-scatter grid between layers; and

fig. 11b and 11c are schematic diagrams of different embodiments of an indirect 3-layer x-ray imaging device with an anti-scatter grid between some layers and a direct 3-layer x-ray imaging device with an anti-scatter grid between some layers.

Detailed Description

The present disclosure relates to a method and apparatus for determining a virtual output of a multi-energy x-ray imaging apparatus. In one embodiment, the method receives the actual outputs of layers from the multi-layer x-ray imaging device, and then processes the outputs to determine the outputs of other non-existent layers within the multi-layer x-ray imaging device as if they were the actual physical layers within the x-ray imaging device. In another embodiment, the method receives actual outputs from different spectral/energy exposures obtained from multiple imaging devices, and then processes the outputs to determine outputs for other non-obtained spectral/energy exposures.

Fig. 8 shows a general schematic of a radiographic imaging environment. As shown, an x-ray source 10 generates an x-ray beam or x-rays 11 that are transmitted toward an object 12 (e.g., a patient's hand) for imaging by a Radiographic Detector System (RDS) 14. The results of the x-ray exposure may be observed on a computer or processor 16. In the present embodiment, which may be considered an indirect imaging system, the radiographic detector system 14 includes a scintillator 15. In the direct imaging system, the x-rays 11 generate electric charges within the radiographic detector system 14, and the scintillator 15 is not required.

For some radiographic detector systems 14, synchronization hardware 18 is necessary to obtain the correct timing between the x-ray source 10 and the radiographic detector system 14 that is sampling the incident x-ray beam 11. In the present disclosure, the radiographic detector system 14 includes a large area flat panel detector based on active matrix technology to enable imaging of the object 12.

Typically, an object 12 to be imaged is placed between the radiation source 10 and the radiographic detector system 14. X-rays 11 passing through the object 12 interact with a radiographic detector system 14. In indirect imaging, x-rays 11 are passed through a phosphor screen or scintillator 15 (such as structured cesium iodide (Csl), Gadolinium Oxysulfide (GOS), or calcium tungsten oxide (CaWO)⁴) Generates photons. These indirectly generated photons are further detected at the radiographic detector systemA charge is generated within the system 14.

Fig. 9 is a schematic diagram of the radiographic detector system 14. RDS 14 comprises an active matrix pixel array 20, which active matrix pixel array 20 has a two-dimensional matrix of pixel elements in which charges generated directly or indirectly by incident x-rays are sensed and stored. To access the stored charge at each pixel, the gate lines 21 are typically driven sequentially by a row switch control 22 so that all pixels in a row output their stored charge onto a data line 23, which data line 23 is coupled to a charge amplifier 24 at the end of each active matrix pixel array 20 column. The charge amplifier 24 sends the pixel charge data to an analog-to-digital converter (a/D)26, where the analog signal is converted to a digital representation. The digital representation is then stored in memory 28 awaiting transmission to computer 16 at a time determined by control logic 29. The charge amplifiers may perform a multiplexing function in addition to their amplifying function.

Turning to fig. 1, a schematic diagram of a multi-layered x-ray imaging detector element or device is shown. In the current embodiment, the detector element 14 includes three different sensor layers, considered a top layer 102, an intermediate or middle layer 104, and a bottom layer 106. As will be appreciated, in the preferred embodiment, each of the top layer 102, the intervening layer 104, and the bottom layer 106 are identical to one another. Each sensor layer may be viewed as a separate layer of a multi-layer x-ray detector element or imaging detector. In one embodiment, each layer may be an amorphous silicon (a-Si) flat panel sensor layer coupled to a scintillator layer. Alternatively, any type of indirect or direct conversion x-ray detection layer may be used for the various layers. In other embodiments, as shown in fig. 2a, the detector may include any number of stacked sensor layers (all labeled 102a through 102n, where n may be any number), each having its indirect or direct conversion material. During operation, each layer will produce an output that can be used by the method of the present disclosure to obtain further virtual outputs.

Alternatively, the x-ray imaging device may be part of a multi-shot imaging system. In this case, the detector includes only one sensor layer, but multiple images are obtained by changing x-ray source properties (such as, but not limited to, kVp and/or filtering) and re-exposure. Each of these images may be considered as an output from the detector, which may then be used by the presented method to obtain a further virtual output representing other source properties. A schematic diagram of an x-ray imaging detector for use in a multiple-shot imaging system is shown in fig. 2 b.

Turning to fig. 3a, a flow chart outlining the basic steps of the method of the present disclosure and how it may be used with a multi-energy x-ray imaging device or system to generate at least one virtual output is shown. FIG. 3b is a flow chart summarizing a method of determining an output of at least one virtual layer. In this embodiment, the method may be used for an x-ray detector element or an x-ray imaging device having two or more sensor layers. In one embodiment, the method and apparatus of the present disclosure overcomes the challenges of using x-ray detector imaging devices with different x-ray absorber thicknesses. In one embodiment, the method may allow for a simpler multi-layer detector design with more versatile and improved multi-energy imaging capabilities.

First, the x-ray imaging device is exposed to an x-ray source such that the output from each layer is read by readout electronics (such as, but not limited to, a readout array) to a processor. In other words, the system receives input from a multi-energy imaging device (considered as a slice output) that can be classified as being generated by different x-ray absorption spectra (200).

Based on the application for which the x-ray imaging device is being used, the processor may then input or substitute these inputs into a preferably predetermined or preselected general algorithm or equation to determine a virtual output algorithm for the x-ray device (204). This means that parameters for the general algorithm are calculated or determined. The general algorithm may be selected based on any of the following: application to x-ray imaging devices; physical characteristics of the x-ray imaging device or system; and/or the particular x-ray source settings used in one or more exposures. Once these parameters are calculated, they may be input into or used in a general purpose algorithm to determine or generate a virtual output algorithm. The virtual output algorithm may then be used to compute expected (or virtual) outputs of other virtual layers of the x-ray imaging device, such as an image (204).

To assist in understanding the method, exemplary embodiments of the method are provided. An overview of the amount of signal remaining in the x-ray beam after it has passed through the object when absorbed by a single, infinitely thick scintillator is provided. The amount of signal remaining at any point in the beam path is defined as:

where Φ (E) is the spectrum of the residual beam,is an average scintillator gain function, typically in the form of a normal inorganic scintillator

As can be seen in fig. 4a, the signal decays exponentially as it travels through the absorber. By considering an embodiment of a multi-layer detector with layers of the same scintillator material and thickness, at each layer (S)_i) The signals obtained can be used to generate equations that will describe their trends. The signal at each layer is expected to decrease exponentially, the rate of exponential decrease will change as the amount of signal in the bundle decreases. This is because the signal at each layer will be the difference in the values of two points on the curve shown in figure 4 a. Thus, the equation chosen in this example is:

wherein the value l in the equation_iReferred to as the number of layers. Mathematically, the number of layers corresponds to the total scintillator thickness of each layer. However, consider that the parameters a, b and c areFitted, for simplicity,/_iIs normalized to the layer thickness, where l_i1, 2 and 3. As will be appreciated, this is for simplicity only and is not necessary for this method. In fact, l can be modified_iTo account for x-ray losses in the detector elements, in addition to scintillators and other non-idealities. By substituting the received output into the general equation or algorithm shown above, the parameters of the virtual output equation can be determined to provide a virtual output equation that can be used to generate any virtual layer of the detector. Fig. 4b shows an example of how, once the parameters of the fitting equation are found, they can be used to approximate the values of the virtual layer.

Once fitted, the found parameters for each pixel may be used to generate an image of the virtual detector layer having any selected thickness and having any selected amount of pre-filtering. In this way, the virtual output algorithm of the x-ray imaging device and the application for which the x-ray imaging device is being used can be found and then used to calculate the values of the virtual layer. For example, an infinitely thick underlayer may be usedTo account for, or a half thickness of the top layer may be usedTo calculate. Note that even if the virtual output equation directly gives signals for layers of the same thickness as those layers that build the detector, by intelligently using this equation, values for layers of any desired thickness can be obtained indirectly.

Thus, an advantage of the present disclosure is that it may facilitate the computation of virtual multi-layer detector elements having any arbitrary number of layers of arbitrary thickness, even physically impossible detector configurations such as superimposed layers or infinitely thick layers. This can be a benefit or advantage of both dual energy techniques (where the virtual thickness can be customized to generate the best possible tissue subtraction image) and digital radiography techniques (where the quality of the image can be improved by generating a single virtual layer of impractical thickness or by intelligently reducing noise by means of more complex fitting methods).

Turning to FIG. 3b, a flow chart summarizing a method of determining virtual layer output for a multi-layer x-ray imaging device is shown. First, input (such as output from a multi-layer x-ray detector exposed to an x-ray source) is received from each layer of the multi-layer imaging apparatus (206). These inputs (or outputs) then replace each pixel as inputs to the general algorithm to determine the parameters of the virtual output algorithm and generate the virtual output algorithm (208). The virtual output algorithm may then be used to generate a full or partial image to be generated by the virtual layer (210).

Turning to fig. 3c, a flow chart summarizing a method of determining a virtual energy output of a multi-x-ray imaging device is shown. First, the output of each exposure from the multiple shot imaging device is received (212). These outputs then replace each pixel as input to the general algorithm to determine the parameters of the virtual output algorithm and generate the virtual output algorithm (214). The virtual output algorithm may then be used to determine a full or partial image of the virtual exposure (216).

Although some mathematical embodiments or equations to describe the signal changes are disclosed with respect to fig. 3a, 3b or 3c, any number of equations or algorithms may be used as a general algorithm. These general equations or algorithms may require different numbers of fitting parameters and may have varying fitting qualities. Some will fit the input signal exactly, while others may approximate a new signal curve by using the signal as a reference. However, they are all similar in that they employ the outputs or energy exposures of the different layers as inputs or signals as well as physical information of the detector and its operation, such as layer scintillator thickness and material, or different source voltages or filters used.

Further, it should be noted that while the disclosed embodiments discuss using a multi-layer detector with all equal absorbers to obtain the necessary fit, other configurations that vary sensor type and thickness are contemplated and may improve the fitting accuracy and allow for more complex fitting algorithms. The method of the flow chart in fig. 3b may be useful even if only two layers are utilized. Similarly, the method in the flow chart in fig. 3c may be used in a multiple-shot detector system as shown in fig. 2b, where any number of exposures at different source voltages, currents and/or filtering states may be used as input to an algorithm that may then generate a virtual exposure image.

In multi-layer detectors with fewer layers and therefore less output used by the general algorithm, the algorithm fitting accuracy may be low. However, this can be improved by, for example, using known materials as intermediate filters to spectrally separate the beam spectrum between detector layers, allowing for wider spectral coverage of the signal to the algorithm. As long as the physical configuration of the detector device is known, the general algorithm can be adapted to accommodate any configuration and generate an appropriate virtual output algorithm that allows the calculation of the virtual layer signal. Similarly, as long as the exposure settings (such as voltage, current, and filtering) are known in a multiple shot imaging system, a general purpose algorithm can be selected to accommodate the selected parameters and generate a virtual output algorithm that allows the virtual exposure signal to be calculated.

The embodiments presented above are examples for illustrating the present technology. As mentioned, implementation details of the methods of the present disclosure may be modified to allow better results to be obtained in a particular application or in a given particular detector system. The simplest modification to the example provided would be to modify the general equation or algorithm to another exponentially decreasing equation, such as

Another example is to use a multi-layer detector with scintillators of the same or different thickness to fit the amount of signal in the beam, rather than the absorbed signal, to approximate the curve in fig. 4a with a fitting equation and assuming that the signal at each layer will be a well-defined integral of the curve, a general algorithm can be retained, for example:

wherein the content of the first and second substances,is the thickness of the scintillator prefilter of each layer, and t_iIs the scintillator thickness of the layer.

Further, the method of the present disclosure may be modified for use with multi-layer detectors having scintillators of different materials and different thicknesses. In this case, the input x-ray spectrum at each pixel may be fitted to a parameterized function. This is possible because the signal at each layer is known to be proportional to the product of the residual spectrum at each layer and the absorption efficiency of that layer.

In another embodiment, a multi-layer detector of two or more layers may be used, and the obtained signals used to findThe best fit parameters of (1).

In a further implementation, a dual layer detector may be used with an intermediate filter made of the same scintillator material and the signal fitted to an equationBut using l for the top and bottom signals, respectively_i1, 5. This still effectively leaves S normalized to the double layer thickness_i. Again, note that l may actually be modified_iValues to account for other detector elements. This implementation can be extended to the aforementioned embodiment assuming that the signal at each layer is a well-defined integral of the curve with the fitted parameters, but the intermediate scintillator material is taken into account in the selection of the integration limits by adding the thickness of the intermediate scintillator material to the limits of the integration of those layers in the beam path after the intermediate filter. This can be achieved by using S_iTo further extend the different parameterized equations.

In another embodiment, the method can be usedWith a four-layer detector and fitting the signal to any of the previously mentioned general equations or new equations with four parameters (such as). In yet another embodiment, more complex general algorithms, such as a minimization algorithm in the form of a monte carlo minimization algorithm, are also possible.

From these examples, it is clear that different types of mathematical methods can be used in combination with any multi-layer x-ray detector to generate the virtual layer signals. It will also be understood that the method of the present disclosure may be extended to any multi-energy detector system, including but not limited to multi-shot imaging systems, where individual image exposures are taken at different source voltages, currents, and/or filtering. This approach may adapt to trends between different input spectra, and thus allow extrapolation to other input source voltages and a better understanding of the material being imaged. As should be apparent, the approach taken by the method of the present disclosure is equally valid in other applications, such as multispectral 3D computed tomography imaging or real-time imaging.

Further, the methods of the present disclosure may be used to algorithmically transfer information between layers or between exposures while maintaining local contrast. This allows for correction of other problems typically encountered in x-ray imaging, including correction of faulty array pixels, faulty rows or faulty areas, or reduction of electronic or quantum noise. Array fault correction may allow for relaxation of low or minimum defect density requirements on individual sensor layers. Similar improvements can be obtained for noise reduction, where data from multiple layers or exposures can reduce uncertainty in the measurement of the true signal.

One way in which the method of the present disclosure may be used to correct faulty array pixels, faulty rows, or faulty areas in various sensor layers in a multi-layer x-ray detector device is: firstly, identifying each faulty pixel or all pixels belonging to a faulty row or a faulty area in one sensor layer; taking outputs corresponding to those pixels or regions from all other sensor layers in the multi-layer detector device, wherein if a value of one layer corresponds to a similar portion of the object being imaged, the output from that layer corresponds to an output in another layer; fitting the outputs to a generic algorithm to generate a virtual output algorithm; obtaining virtual outputs of all faulty pixels or faulty areas using a virtual algorithm to match the physical properties of the original sensor layer; and replacing the value of the defective pixel in the original sensor layer with the dummy output. Obviously, the method can be reproduced for each sensor layer to remove all faulty pixel values from some or all layers of the multi-layer detector device.

Noise reduction of sensor output data may also be achieved by utilizing the methods of the present disclosure. This can be done by selecting a general algorithm that requires fewer fitting parameters than the number of layers in a multi-layer imaging device or exposures in a multi-shot imaging system, or by selecting an algorithm that does not weight all output data in the same way. Once a virtual output algorithm for this general-purpose algorithm is found, a virtual output layer or exposure may be generated that has the same or similar physical properties as one of the device outputs. This virtual output may have a similar local contrast as the original device output, but with a smaller noise component, depending on the nature of the general algorithm chosen. It is also possible to replace only certain regions or spatial frequency components of the original output to achieve better results.

One additional application of the method of the present disclosure is for measuring bone mineral density by dual-energy x-ray absorptiometry. The found parameters for the virtual output algorithm or the generated virtual layer or exposure image may be used in combination with any additional information about the x-ray imaging device, about the exposure settings used, or about the x-ray system configuration to calculate the density or areal density in some or all of the bone regions imaged.

A further application of this method of the present disclosure is object scatter correction. x-ray radiation is typically scattered from the object being imaged, resulting in an overall loss of image quality. The method of the present disclosure may exploit differences in spectral properties in typical object scatter radiation to separate and thereby remove the differences from the final output image, thereby improving image quality.

Different multi-layer detectors that can be used with the method of the present disclosure for both indirect scintillator-based x-ray detectors and direct photoconductor-based x-ray approaches are schematically illustrated in fig. 5 (n-layer), fig. 6a and 6b (two-layer approach), and fig. 7a and 7b (three-layer approach). Given the nature of the materials used, it is expected that there will be some amount of scattered or fluorescent radiation from one layer to another (grouped here under the first term) when the detector is exposed, thereby altering the signal output from each layer, which may affect the method presented here for determining the virtual output.

As shown in fig. 5, the detector 14 includes "n" sensor layers 500a, 500 b. As will be understood, "n" represents any number. For a direct multi-layer x-ray detector, each sensor layer 500 includes a photoconductor layer 502 and a substrate layer 504. For an indirect multi-layer x-ray detector, each sensor layer 500 includes a scintillator layer 506 and a substrate layer 508.

As shown in fig. 6a, the detector includes a first sensor layer 500a, an intermediate filter layer 510, and a second sensor layer 500 b. For a direct multi-layer x-ray detector, each sensor layer 500 includes a photoconductor layer 502 and a substrate layer 504. In the current embodiment, the intermediate filter layer 510 may be another photoconductor layer 512. For an indirect multi-layer x-ray detector, each sensor layer 500 includes a scintillator layer 506 and a substrate layer 508, where an intermediate filter layer 510 may be another scintillator layer 514.

The embodiment shown in fig. 6b is similar to the embodiment of fig. 6a, with the positions of the photoconductor layer 502 and the substrate layer 504 in the sensor layer 500 reversed (directly), and the positions of the scintillator layer 506 and the substrate layer 508 in the sensor layer 500 reversed (indirectly).

As shown in fig. 7a, the detector includes a first sensor layer 500a, a second sensor layer 500b, and a third sensor layer 500 c. For a direct multi-layer x-ray detector, each sensor layer 500 includes a photoconductor layer 502 and a substrate layer 504. For an indirect multi-layer x-ray detector, each sensor layer 500 includes a scintillator layer 506 and a substrate layer 508.

The embodiment shown in fig. 7b is similar to the embodiment of fig. 7a, with the addition of an intermediate filter layer between the second sensor layer 500b and the third sensor layer 500 c. As will be appreciated, an intermediate filter layer may also be placed between the first sensor layer 500a and the second sensor layer 500 b. Alternatively, the intermediate filter layer 510 may be placed between the first sensor layer and the second sensor layer and between the second sensor layer and the third sensor layer.

To overcome the challenge of reducing or minimizing radiation scattered by the x-ray absorbing layer, various strategies may be employed. One strategy may be to select a material with a low-k edge (such as an amorphous selenium photoconductor) where k fluorescent x-rays have energies less than 12keV and therefore do not travel too far, or alternatively, may be to select a CsI scintillator with 33keV fluorescent x-rays. Also, an intermediate filter made of the same material as the selected scintillator may be used to reduce the effect of scattered radiation. Furthermore, the orientation of the sensor layers may be varied as schematically shown in fig. 6a, 7a and 7b, wherein the orientation of the sensor layer 500a minimizes the distance between the photoconductor layers 502 (directly) or between the scintillator layers 506 (indirectly), thereby reducing the scattering distance associated with x-ray k-fluorescence.

Other techniques may be used to reduce cross-scattering between layers. As shown in fig. 11a, 11b and 11c, this involves adding an anti-scatter grid between the sensor layers in any of the configurations previously mentioned, which will absorb scattered radiation disproportionately and thus reduce the proportion of the signal value of the layer corresponding to the scattering (known as the scatter-to-primary ratio).

Fig. 11a is a schematic diagram of a multi-layer detector 500 including multiple sensor layers 500a, 500 b. Located between the sensor layers 500 is an anti-scatter grid layer 516. As with the previous embodiment, each direct sensor layer includes a photoconductor layer 502 and a substrate layer 504, and each indirect sensor layer includes a scintillator layer 506 and a substrate layer 508.

FIG. 11b is a schematic diagram of a multi-layer detector 500 including three (3) sensor layers 500a, 500b, and 500c and a single anti-scatter grid layer 516, the single anti-scatter grid layer 516 being between the first sensor layer and the second sensor layer. FIG. 11c is a schematic diagram of a multi-layer detector 500 including three (3) sensor layers 500a, 500b, and 500c and a single anti-scatter grid layer 516, the single anti-scatter grid layer 516 being between the second sensor layer and the third sensor layer.

Similarly, as shown in fig. 10a, 10b, and 10c, an intermediate filter may be added between the sensor layers that will disproportionately absorb scattered photons because these photons are primarily energy in the low end of the diagnostic x-ray spectrum. The specific material type of the intermediate filter may be selected to tune the scattered energy absorption. In one embodiment, the material selection for the one or more intermediate filters is metallic, such as copper, aluminum, or silver.

Fig. 10a is a schematic diagram of a multi-layer detector 500 including multiple sensor layers 500a, 500 b. Located between the sensor layers 500 is an intermediate filter layer 518. As with the previous embodiment, each direct sensor layer includes a photoconductor layer 502 and a substrate layer 504, and each indirect sensor layer includes a scintillator layer 506 and a substrate layer 508.

FIG. 10b is a schematic diagram of a multi-layer detector 500 including three (3) sensor layers 500a, 500b, and 500c and a single intermediate filter layer 518, the single intermediate filter layer 518 being between the first sensor layer and the second sensor layer. FIG. 11c is a schematic diagram of a multi-layer detector 500 including three (3) sensor layers 500a, 500b, and 500c and a single intermediate filter layer 518, the single intermediate filter layer 518 being between the second sensor layer and the third sensor layer.

Another technique is to reduce or minimize the distance between the x-ray absorber layers by utilizing as thin a substrate as possible, wherein the thickness of the x-ray absorber layers can be significantly reduced by using a flexible substrate. Finally, this distance can be completely removed by combining the substrate and the absorber layer in the form of a scintillator-infused substrate.

In the previous description, for purposes of explanation, numerous details were set forth in order to provide a thorough understanding of the embodiments. However, it will be apparent to one skilled in the art that these specific details may not be required. In other instances, well-known structures may be shown in block diagram form in order not to obscure the understanding. For example, specific details are not provided as to whether elements of the embodiments described herein are implemented as software routines, hardware circuits, firmware, or a combination thereof.

Embodiments of the present disclosure or components thereof may be provided as or represented as a computer program product stored in a machine-readable medium (also referred to as a computer-readable medium, a processor-readable medium, or a computer usable medium having computer-readable program code embodied therein). The machine-readable medium may be any suitable tangible, non-transitory medium including magnetic, optical, or electronic storage medium including a diskette, compact disc read only memory (CD-ROM), memory device (volatile or non-volatile), or similar storage mechanism. The machine-readable medium may contain various sets of instructions, code sequences, configuration information, or other data, which when executed, cause a processor or controller to perform steps in a method according to embodiments of the disclosure. Those of ordinary skill in the art will appreciate that other instructions and operations necessary to implement the described embodiments may also be stored on a machine-readable medium. The instructions stored on the machine-readable medium may be executed by a processor, controller or other suitable processing device and may have been interfaced with circuitry to perform the described tasks.

The above embodiments are intended to be examples only. Alterations, modifications and variations may be effected to the particular embodiments by those of skill in the art without departing from the scope, which is defined solely by the claims appended hereto.