Method and system for coincidence detection in an X-ray detector

Abstract

An improved X-ray detector system is provided. [Solution] An X-ray detector system (5) is provided that includes a photon-counting X-ray detector (20) that detects X-ray radiation from an X-ray source, and a coincidence detection system (60) that determines and / or obtains information about radiation incident on the X-ray detector based on information about the time of photon interaction at the X-ray detector and information about the position of the X-ray source relative to the X-ray detector. An X-ray imaging system that includes such an X-ray detector system, as well as a corresponding coincidence detection system and corresponding method are also provided.

Description

[Technical field]

[0001] The proposed technology relates to X-ray imaging and X-ray detectors, and more particularly to photon counting X-ray detectors, X-ray detector systems, coincidence counting detection systems, corresponding methods and systems, X-ray imaging systems, computer programs, and computer program products. [Background technology]

[0002] Radiation imaging, such as X-ray imaging, has been used for many years in medical applications and non-destructive testing.

[0003] Typically, an X-ray imaging system includes an X-ray source and an X-ray detector system. The X-ray source emits X-rays, which pass through the subject or object being imaged and are detected by the X-ray detector system. Some materials absorb more X-rays than others, so an image of the subject or object is formed.

[0004] It is useful to start with a brief overview of an exemplary X-ray imaging system in general, with reference to FIG. 1. In this non-limiting example, the X-ray imaging system 100 essentially includes an X-ray source 10, an X-ray detector 20 or X-ray detector system, and an associated image processor 30. In general, the X-ray detector 20 detects radiation from the X-ray source 10, possibly focused by any X-ray optical elements, that has passed through an object, subject, or part thereof. The X-ray detector 20 may be connected to the image processor 30 through analog processing and readout electronics (which may be integrated into the X-ray detector 20), and image processing and / or image reconstruction may be performed by the image processor 30.

[0005] Generally, there is a demand for improved performance regarding x-ray imaging devices and x-ray detectors.

[0006] For example, it is desirable to improve the signal-to-noise ratio and spectral performance of photon-counting X-ray detectors.

[0007] For example, it is also desirable to be able to obtain and / or determine useful information regarding the radiation incident on the x-ray detector. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] US Patent Application Publication No. 2016 / 653200 [Patent Document 2] International Publication No. 2020 / 106198 [Non-patent literature]

[0009] [Non-Patent Document 1] H. Bornefalk and M. Danielsson, “Photon-counting spectral computed tomography using silicon strip detectors: a feasibility study” Physics in Medicine and Biology 55, 1999-2022, 2010 Summary of the Invention

[0010] One object is to provide an improved X-ray detector system.

[0011] Another object is to provide an improved X-ray imaging system.

[0012] It is also an object to provide a method for obtaining or determining information about radiation incident on an X-ray detector.

[0013] Yet another object is to provide an improved coincidence detection system.

[0014] These and other objectives may be achieved by one or more embodiments of the proposed technology.

[0015] According to a first aspect, there is provided an X-ray detector system comprising: a photon-counting X-ray detector (20) for detecting X-rays from an X-ray source; and a coincidence detection system for determining and / or obtaining information about X-rays incident on the X-ray detector based on information about a time of photon interaction at the X-ray detector and information about a position of the X-ray source relative to the X-ray detector. Includes.

[0016] According to a second aspect, there is provided an X-ray imaging system including such an X-ray detector system.

[0017] According to a third aspect, there is provided a method for obtaining or determining information about radiation incident on an X-ray detector, the method comprising the steps of: using a photon-counting X-ray detector to detect X-rays, the photon-counting X-ray detector operating in a broad energy band of the X-ray spectrum having a maximum energy less than 160 keV emitted from a localized X-ray source; detecting timing information of photon interactions at the photon-counting X-ray detector; and and obtaining or determining information about X-rays incident on the X-ray detector based on the timing information and information about a position of the X-ray source relative to the X-ray detector, the information including at least one of the following expressions: a number of incident photons in a particular area, a spatial distribution of the incident photons, and an energy distribution of the incident photons.

[0018] According to a fourth aspect, there is provided a coincidence detection system configured to operate with a photon-counting X-ray detector to determine and / or obtain information about radiation incident on the X-ray detector based on information about a time of photon interaction at the X-ray detector and information about a position of the X-ray source relative to the X-ray detector.

[0019] In this manner, beneficial improvements may be made with respect to X-ray imaging and / or detector technology.

[0020] As an example, the signal-to-noise ratio and spectral performance of photon-counting X-ray detectors can be significantly improved. [Brief description of the drawings]

[0021] The embodiments, together with further objects and advantages thereof, may be better understood by referring to the following description taken in conjunction with the accompanying drawings, in which: [Figure 1] FIG. 1 is a schematic diagram showing an example of an entire X-ray imaging system. [Figure 2A] FIG. 13 is a schematic diagram illustrating another example of an X-ray imaging system. [Figure 2B] 1 is a schematic diagram showing an example of an X-ray detector system according to the proposed technique. [Figure 2C] FIG. 1 is a schematic diagram illustrating an example of a non-limiting specific embodiment in which the coincidence detection system is implemented in a digital processing circuit. [Diagram 3] FIG. 2 is a schematic diagram showing example energy spectra for three different X-ray tube voltages. [Figure 4] FIG. 1 is a schematic diagram showing an example of a conceptual structure for realizing an energy-discriminating photon counting detector. [Diagram 5] 1 is a schematic diagram of an X-ray detector in accordance with an exemplary embodiment; [Figure 6] 1 is a schematic diagram illustrating an example of a solid state detector module in accordance with an exemplary embodiment. [Figure 7]FIG. 13 is a schematic diagram illustrating another example of an X-ray detector sub-module in accordance with an exemplary embodiment. [Figure 8] FIG. 1 is a schematic diagram illustrating an example of a modular X-ray detector including several detector sub-modules arranged so as to be aligned, for example in a slightly curved shape, as a whole with respect to an X-ray source located at an X-ray focal spot. [Figure 9] FIG. 1 is a schematic diagram illustrating an example of a modular X-ray detector that includes several detector sub-modules arranged side-by-side and stacked one on top of the other. [Figure 10] FIG. 1 is a schematic diagram illustrating an example of a photon-counting X-ray detector based on an X-ray detector sub-module 21 (herein referred to as a wafer). [Figure 11] FIG. 1 is a schematic diagram for explaining the Compton effect. [Figure 12] FIG. 2 is a schematic diagram showing an example of the spectrum of deposited energy in the Compton and photoelectric parts of the interaction spectrum. [Figure 13] 1 is a schematic diagram showing an example of interactions over a time interval: the black lines show interactions belonging to the same incident photon. [Figure 14] FIG. 13 is a schematic showing an example of a 1D scattering distance for an interaction chain (one Compton interaction + one photoelectric interaction). [Figure 15] FIG. 1 is a schematic diagram showing an example of a spectrum of incident photon energy for different interaction chains. [Figure 16] FIG. 2 is a schematic diagram illustrating an example of a pixel of a particular wafer in the xz plane. [Figure 17] FIG. 13 is a schematic diagram illustrating an example of a charge cloud profile in the x-direction of a charge cloud. [Figure 18] FIG. 13 is a schematic diagram illustrating an example of a charge cloud profile in the z direction of a charge cloud. [Figure 19] FIG. 1 is a schematic diagram showing an example of how the width of a charge spread or charge cloud depends on the distance from the initial point of interaction to the point of detection along the thickness of a detector submodule or wafer of interest of an X-ray detector. [Figure 20] FIG. 2 is a schematic diagram illustrating an example of an X-ray detector sub-module according to one embodiment. [Figure 21] FIG. 13 is a schematic diagram illustrating another example of an X-ray detector sub-module according to an embodiment. [Figure 22] FIG. 1 is a schematic diagram illustrating an example of an active integrated pixel according to one embodiment. [Figure 23] FIG. 13 is a schematic diagram illustrating another example of an active integrated pixel according to another embodiment. [Figure 24] FIG. 13 is a schematic diagram illustrating yet another example of an active integrated pixel according to another embodiment. [Diagram 25] FIG. 13 is a schematic diagram illustrating yet another example of an active integrated pixel according to yet another embodiment. [Figure 26] FIG. 2 is a schematic diagram illustrating an example of a computer implementation according to one embodiment. [Figure 27] 1 is a flow diagram that illustrates generally an example of a method for obtaining or determining information about radiation incident on an X-ray detector. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] For a better understanding, it is useful to proceed with an introductory discussion of a non-limiting example of a complete X-ray imaging system.

[0023] FIG. 2A is a schematic diagram showing an example of an X-ray imaging system 100, which includes an X-ray source 10 that emits X-rays, an X-ray detector 20 that detects the X-rays after passing through an object, an analog processing circuit 25 that processes and digitizes raw electrical signals from the detector, a digital processing circuit 40 that can perform further processing operations on the measurement data (such as performing corrections, temporarily storing the measurement data, or performing filtering), and a computer 50 that can store the processed data and perform further post-processing and / or image reconstruction.

[0024] The entire detector may be considered to be an X-ray detector system 20, or an X-ray detector system 20 in combination with associated analog processing circuitry 25.

[0025] The digital part including the digital processing circuit 40 and / or the computer 50 in Fig. 2 can be considered as the digital image processing system 30 in Fig. 1 that performs image reconstruction based on image data from an X-ray detector. Therefore, the image processing system 30 in Fig. 1 can be understood as the computer 50 in Fig. 2, or as a system combining the digital processing circuit 40 and the computer 50, or as the digital processing circuit 40 alone when the digital processing circuit is dedicated to image processing and / or reconstruction.

[0026] One example of a commonly used X-ray imaging system is a computed tomography (CT) system. A CT system can include an X-ray source that produces a fan or cone beam of X-rays and an opposing X-ray detector system for detecting the X-rays that pass through a patient or object. The X-ray source and detector system are typically mounted on a gantry that rotates around the object being imaged.

[0027] Thus, the X-ray source 10 and X-ray detector 20 shown in Figures 1 and 2 may be arranged as part of a CT system, for example so as to be mounted on a CT gantry.

[0028] The X-ray imaging system 100 may also include a coincidence detection system 60 for implementing the proposed techniques. Referring to Fig. 2A, the coincidence detection system 60 may, by way of example, be implemented at least partially in the digital processing circuitry 40 and / or at least partially in the analog processing circuitry 25 and / or at least partially as executable program code for execution by the computer 50.

[0029] 2B is a schematic diagram showing an example of an X-ray detector system according to the proposed technology. The X-ray detector system 5 includes an X-ray detector 20 and a coincidence detection system 60.

[0030] FIG. 2C is a schematic diagram illustrating an example of a particular, non-limiting embodiment in which the coincidence detection system 60 is implemented in the digital processing circuit 40.

[0031] Thus, according to one aspect, there is provided an improved X-ray detector system 5 comprising: a photon-counting X-ray detector 20 for detecting X-rays from an X-ray source; and a coincidence detection system 60 for determining and / or obtaining information about X-rays incident on the X-ray detector 20 based on information about the time of photon interaction at the X-ray detector 20 and information about the position of the X-ray source relative to the X-ray detector; Contains:

[0032] By way of example, such a detector system may be incorporated into an imaging system that includes the detector system, an X-ray source, and a computer for data processing.

[0033] As an example, the X-ray detector system can be configured to operate with a broad energy band of the X-ray spectrum having a maximum energy of less than 160 keV. This X-ray spectrum is emitted by an X-ray source that is a localized X-ray source that is less than 0.5 millisteradians from a point on the X-ray detector. This non-limiting example corresponds to typical operating conditions of a medical X-ray or CT system. Such systems also typically operate with smaller sources to further localize the direction of incidence of the radiation.

[0034] In certain examples, the coincidence detection system determines and / or obtains information about the X-rays incident on the X-ray detector based on the information regarding the time of photon interaction and the information regarding the position of the X-ray source relative to the X-ray detector, the information including at least one of the number of incident photons in a particular area, the spatial distribution of the incident photons, and the energy distribution of the incident photons.

[0035] As an example, a coincidence detection system can be configured to operate based on a photon scattering model that can be combined with information regarding the position of an X-ray source relative to an X-ray detector to determine and / or obtain the information regarding the X-ray. In a non-limiting example, the information regarding the position of an X-ray source can be used along with a measurement of the position of interaction to measure the scattering angle of an incident X-ray, and the photon scattering model can be used to estimate the likelihood that a scattering angle will be observed with one or more of the detected photon energies.

[0036] The inventors have realized that having a localized radiation source, such as an X-ray tube, can provide an improved coincidence detection system. By way of example, when the direction of radiation incidence is known with high precision (e.g., when the X-ray source is localized as a point of size on the order of 1 mm, or, more generally, when the X-ray source subtends a solid angle of less than 0.5 millisteradians as seen by the detector), this information can be combined with a model of X-ray photon scattering to improve coincidence detection.

[0037] For example, if the first interaction is a Compton interaction and the second interaction is a photoelectric interaction, the total incident photon energy can be estimated as the sum of the energies deposited in the two interactions, and the scattering angle can be calculated from the positions of the two interactions relative to the incident direction. This angle can then be compared to the detected energy of the Compton interaction and the estimated incident energy using the Compton scattering equation or the Klein-Nishina cross section. In this way, the likelihood that two interactions were generated from a single incident photon can be calculated.

[0038] It is understood that this is a non-limiting example and that other numbers of interactions and other combinations of interactions can be treated in a similar manner. It is also understood that having a localized source, thereby obtaining information about the direction of incidence of the photons on the detector, is necessary for this type of coincidence detection.

[0039] For example, the coincidence detection system may combine the photon scattering model and prior knowledge of the position of the X-ray source with prior knowledge of the probability of different incident X-ray energy distributions to determine and / or obtain the information about the X-rays. For example, such prior knowledge may take the form of a model of the X-ray source spectrum based on a tabulated data spectrum of the X-ray tube or a simulated spectrum of the X-ray tube that has been filtered through different materials. The prior knowledge may also include information that there are a few incident X-rays with energies below a certain energy (e.g., 20 keV) or above a certain energy (e.g., 160 keV). Such prior information may also include a model of the probability that the X-ray beam has passed through a combination of different reference materials with different thicknesses in combination with a model of the output spectrum from the X-ray tube. Such prior information may also include information about typical interaction energies of secondary photoelectric interactions, for example, that these energies are localized in a particular part of the detected spectrum of the applied energy.

[0040] In a particular example, the X-ray detector is a photon counting multi-bin X-ray detector capable of discriminating between different energies of photon interactions, and the coincidence detection system uses information about the energy of the photon interactions to determine the information about the X-rays.

[0041] By way of example, the coincidence detection system may determine and / or obtain said information regarding the X-rays based on at least one representation of the time and / or timing of the photon interaction, which may be obtained, by way of example, as a measurement of the time at which an electrical pulse reaches a maximum amplitude, the electrical pulse being generated by the interaction of the X-ray photon in the sensor material.

[0042] Optionally, the coincidence detection system may determine and / or obtain said information about the X-rays based on at least one of information about the position of the photon interaction and information about the energy imparted in the photon interaction.

[0043] For example, a coincidence detection system can determine and / or obtain said information regarding X-rays incident on a detector based on identifying at least one set of photon interactions that can be generated by a single incident photon.

[0044] In certain examples, a coincidence detection system generates and / or obtains information about x-rays incident on the x-ray detector based on identifying at least two sets of photon interactions that are likely to have been generated by at least two different incident photons, where all photon interactions in each set are likely to have been generated by a single incident photon, and the coincidence detection system identifies the at least two sets of photon interactions as likely to have been generated by at least two different incident photons based on comparing the at least two sets of photon interactions to at least one other possible set of photon interactions.

[0045] For example, the coincidence detection system can generate and / or obtain information about the X-rays incident on the X-ray detector based on combining information about the time of the photon interaction with at least one angle defined by at least two positions of the photon interaction, and / or based on at least one angle defined by three positions of the photon interaction, and / or based on at least one angle defined by the incident radiation direction and two positions of the photon interaction. By way of example, such an angle is related to the energy deposited in at least one of the interactions, and such an angle can be used to calculate, using a photon scattering model, the likelihood of a particular interaction order or the likelihood that the interactions are classified into a set of interactions that can be generated by a single interaction. An interaction order is an order of interactions that are considered to be generated consecutively by a single photon. The correct interaction order corresponds to the chronological order of the interactions generated by a single incident photon.

[0046] In a particular example, the x-ray detector is a silicon detector.

[0047] Typically, X-ray detector systems distinguish between Compton and photoelectric interactions based on an energy threshold. For example, interactions that deposit energy below a certain threshold can be identified as Compton interactions, and interactions with energy above a certain threshold can be identified as photoelectric interactions. The threshold is illustratively selected as the energy at which the spectrum of deposited energy has a minimum, or as the energy at which the number of Compton interactions and the number of photoelectric interactions are approximately equal.

[0048] Optionally, the X-ray detector system has high attenuation shielding to reduce scattering within the X-ray detector. Reducing scattering reduces the number of interactions detected, thereby reducing the total number of interactions in a given time interval. This can simplify coincidence detection methods, for example, by reducing the number of possible coincidences. However, reduced scattering can also make coincidence detection more difficult, as photons are absorbed without imparting their full energy to the detector.

[0049] As an example, an X-ray detector system may use a method for estimating the position of an interaction based on an estimate of the amount of charge diffusion.

[0050] In a particular example, the coincidence detection system can be configured to operate based on a model of an X-ray detector.

[0051] By way of example, the coincidence detection system may be configured to operate based on a photon scattering model, which may be based on at least one of the Compton scattering equation, the Klein-Nishina equation, the Beer-Lambert law, X-ray interaction cross sections for the photoelectric effect, the Compton effect, or Rayleigh scattering, and simulations of photon transport.

[0052] In certain examples, the coincidence detection system can be configured to operate based on a photon scattering model that includes or excludes Rayleigh scattering, which describes the elastic diffusion of photons from bound electrons. In this type of scattering, the incident photon is deflected but does not gain energy and thus does not produce a free electron-hole pair.

[0053] The coincidence detection system can process photon interactions detected in the entire volume of the detector or in a subvolume that is independent of at least one subvolume in the detector. Processing data in a subvolume is preferred because, for example, it is computationally easier to perform corrections on a small number of interactions in the subvolume without having to aggregate data from the entire detector together. By way of example, a subvolume can be composed of a single physical detector module or can be composed of multiple physical detector modules. However, a subvolume does not necessarily have to be defined by a physical detector module, but can also include one or multiple partial volumes of one or multiple physical detector modules.

[0054] For example, the coincidence detection system may obtain and / or determine the information regarding the incident radiation based on at least one of a maximum likelihood method, a maximum a posteriori probability estimation method, a neural network, a support vector machine, or a decision tree method.

[0055] The maximum likelihood method may include calculating the likelihood of a certain incident photon and selecting a type of photon by optimizing said likelihood. By way of example, prior information may be incorporated, for example by including a priori models of the probabilities of different incident spectra or other prior information, thereby creating a maximum a posteriori estimation algorithm to improve the estimation.

[0056] As an example, a neural network estimator can receive input data including detected photon counts, energies, and positions, and process the input data using an artificial neural network to generate output data related to estimated incident counts or estimated incident energies. The network can be trained on simulated or measured data.

[0057] For example, a decision tree method may process input data in several successive comparison steps and generate an output based on the results of the comparison. Several decision trees may be aggregated to form a composite reasoner, for example by bootstrap aggregation.

[0058] As an example, the coincidence detection system may obtain and / or determine the information regarding x-rays incident on the x-ray detector based on assigning at least one likelihood to at least one set of photon interactions, the likelihood being based on a probability of observing those photon interactions.

[0059] Optionally, the coincidence detection system may obtain and / or determine the information regarding X-rays incident on the X-ray detector based on optimizing a likelihood, the likelihood being based on a probability of observing these photon interactions.

[0060] For example, the coincidence detection system may obtain and / or determine the information regarding x-rays incident on the x-ray detector based on assigning at least one likelihood to at least one set of photon interactions, the likelihood being based on the probability of observing those photon interactions if they all originate from a single incident photon.

[0061] In certain examples, the coincidence detection system assigns each of a plurality of photon interactions to a set of photon interactions based on the at least one likelihood of observing the photon interactions from a single incident photon.

[0062] As an example, the coincidence detection system may assign the multiple photon interactions into sets of photon interactions such that no interaction is assigned to more than one set.

[0063] For example, the coincidence detection system may assign at least one interaction order to the photon interactions in at least one of the multiple sets based on the likelihood of the interaction order, which may be selected, by way of example, as the interaction order that has the highest likelihood of all possible interaction orders.

[0064] In certain examples, the coincidence detection system assigns an estimated position of photon incidence to at least one set of photon interactions based on a position of a first photon interaction in the set identified by the at least one interaction order.

[0065] As an example, the X-ray detector system estimates the energy of at least one incident photon based on the detected energies of photon interactions in at least one set of photon interactions likely to be attributable to a single incident photon, which may be performed by summing the energies of the photon interactions in the set.

[0066] In an optional embodiment, the X-ray detector system estimates a number of photons incident on the X-ray detector or on at least one sub-volume of the X-ray detector in at least one time interval based on the at least one likelihood.

[0067] As an example, the likelihood may be calculated based on a prior probability distribution over the set of possible spectra incident on the x-ray detector.

[0068] Optionally, a coincidence detection system may be applied to the measurement data prior to at least one of summing the counts measured over multiple time intervals and reading out the measured counts from the photon-counting X-ray detector.

[0069] For example, the X-ray detector system may output the information regarding the X-rays incident on the X-ray detector to be used as input data for at least one of an image reconstruction algorithm, a reference material decomposition algorithm, a noise reduction algorithm, a deblurring algorithm, a pile-up correction algorithm, and a spectral distortion correction algorithm.

[0070] As examples, an image reconstruction algorithm may take projection count data as input and output a reconstructed image. A reference material decomposition algorithm may take count data as input and output a reference image or reference sinogram. A denoising algorithm may take a noisy image or sinogram as input and output a denoised sinogram or image. A deblurring algorithm may take a low resolution image as input and output a high resolution image. A pile-up algorithm may take count data distorted by pile-up as input and output a corrected image. A spectral distortion correction algorithm may take count data distorted by a non-ideal detector response function as input and output corrected count data.

[0071] The image reconstruction algorithm, reference material decomposition algorithm, noise removal algorithm, blur removal algorithm, pile-up correction algorithm, or spectral distortion correction algorithm can be built on, for example, maximum a posteriori probability, block matching, bilateral filtering, or convolutional neural networks.

[0072] In a preferred embodiment, the coincidence detection is performed by a digital processing circuit connected to the detector, such as a microcode sequencer or FPGA, in another embodiment, the coincidence detection is performed by an analog processing circuit or a computer after reading out the data from the detector.

[0073] According to another aspect, there is provided a general X-ray imaging system including such an X-ray detector system.

[0074] As an example, the X-ray imaging system may estimate the energy of at least one incident photon based on detected energies of photon interactions within at least one set of photon interactions likely to be attributable to a single incident photon.

[0075] According to yet another aspect, a coincidence detection system 60 is provided that operates with the photon-counting X-ray detector 20. The coincidence detection system 60 determines and / or obtains information regarding X-rays incident on the X-ray detector 20 based on information regarding the time of photon interaction at the X-ray detector and information regarding the position of the X-ray source relative to the X-ray detector.

[0076] According to yet another aspect, as will be described in more detail below, there is provided a method for obtaining or determining information about x-rays incident on an x-ray detector.

[0077] For better understanding, the proposed technique will now be described with reference to specific, non-limiting examples.

[0078] It is convenient to first provide a brief description of X-ray detector technology in general, after which non-limiting examples of the present invention are described.

[0079] In general, the challenge of an X-ray imaging detector is to extract maximum information from the detected X-rays and provide input data for an image of an object or specimen to depict the object or specimen in terms of density, composition, structure, etc. Although it is common to use a film screen as a detector, today's detectors most often provide a digital image.

[0080] Current X-ray detectors usually require the conversion of incident X-rays into electrons. This typically occurs by optical absorption or Compton interaction, and the resulting electrons usually generate secondary visible light until they lose their energy, which is detected by a photosensitive material. There are also semiconductor-based detectors, where the electrons generated by the X-rays create a charge in the form of electron-hole pairs, which are collected by applying an electric field.

[0081] Conventional x-ray detectors are energy-integrating, so the contribution to the detection signal from each detected photon is proportional to the energy of the detected photon, and conventional CT takes measurements for a single energy distribution, so images produced by conventional CT systems show how different tissues and materials exhibit normal values ​​within a range.

[0082] There are detectors that operate in an integral mode, which obtains an integrated signal from a large number of x-rays, which is later digitized to extract a best estimate of the number of incident x-rays in a pixel.

[0083] Photon-counting detectors have also emerged as a viable alternative for some applications and are currently commercially available mainly for mammography. Photon-counting detectors have the advantage that, in principle, the energy of each x-ray can be measured, thus providing additional information about the composition of the object. This information can be used to improve image quality and / or reduce radiation dose.

[0084] The most promising materials for photon-counting X-ray detectors are cadmium telluride (CdTe), cadmium zinc telluride (CZT), and silicon. CdTe and CZT are being used in several photon-counting spectral CT projects due to their high absorption efficiency for the high-energy X-rays used in clinical CT. However, these projects have been slow to move forward due to several shortcomings of CdTe / CZT. CdTe / CZT has low charge carrier mobility, which results in severe pulse pile-up at flux rates 10 times lower than those experienced in clinical practice. One way to mitigate this problem is to reduce the pixel size, but this approach increases spectral distortion as a result of charge sharing and K-escape. CdTe / CZT also suffers from charge trapping, which creates polarization and is thought to rapidly reduce the output count rate when the photon flux reaches a certain level.

[0085] Silicon, on the other hand, has high charge carrier mobility and is free of polarization problems. It also has the advantage that the manufacturing process is mature and relatively cheap. However, silicon has limitations that CdTe / CZT do not have. Silicon sensors must be made much thicker to compensate for their low stopping power. Typically, silicon sensors need to be several centimeters thick to absorb most of the incident photons, whereas CdTe / CZT only need a few millimeters. On the other hand, silicon has a long attenuation path, which allows the detector to be divided into different depth segments, as will be described later. This improves the detection efficiency and enables silicon-based photon counting detectors to adequately handle the high flux of CTs.

[0086] When using single-element semiconductor materials such as silicon or germanium, Compton scattering can occur, in which only a portion of the photon energy is deposited in the detector. As a result, a large proportion of X-ray photons, which originally had a high energy, generate far fewer electron-hole pairs than expected, and a significant portion of the photon flux therefore appears in the low end of the energy distribution. Therefore, in order to detect as many X-ray photons as possible, it is necessary to detect the lowest possible energies.

[0087] Figure 3 is a schematic diagram showing example energy spectra for three different X-ray tube voltages, resulting from the energy deposited from a mixture of different types of interactions, such as Compton events in the low energy range and photoelectric absorption events in the high energy range.

[0088] FIG. 4 is a schematic diagram showing an example of a conceptual configuration for realizing an energy discrimination type photon counting detector.

[0089] Another improvement relates to the development of so-called energy discriminating photon counting detectors, as for example shown diagrammatically in Figure 4. In this type of X-ray detector, each detected photon produces a current pulse which is compared to a set of thresholds, thereby counting the number of incident photons in each of several so-called energy bins. This can be very useful in the image reconstruction process.

[0090] FIG. 5 is a schematic diagram of an X-ray detector according to an exemplary embodiment. In this example, a schematic diagram of an X-ray detector (A) is shown together with an X-ray source (B) emitting X-rays (C). The detector elements (D) are located on the opposite side of the source and are therefore preferably designed in an overall slightly curved structure. Two possible scanning motions (E, F) of the detector are shown. In each scanning motion, the source may be stationary or moving, and in the scanning motion shown in (E), the X-ray source and the detector may rotate around an object placed between them. Also, in the scanning motion shown in (F), the detector and the source may move relative to the object or the object may move. Also, in the scanning motion (E), the object may move during the rotation, so-called spiral scan. As an example, in a CT implementation, the X-ray source and the detector may be mounted on a gantry that rotates around the object or subject to be imaged.

[0091] 6 is a schematic diagram showing an example of a semiconductor detector module according to an exemplary embodiment. This is an example of a semiconductor detector module (A) in which the sensor part is divided into detector elements or pixels (B), each of which is typically a diode. X-rays (C) enter from the edge (D) of the semiconductor sensor.

[0092] 7 is a schematic diagram showing another example of an X-ray detector submodule according to an exemplary embodiment. In this example, the sensor part of the X-ray detector submodule 21 is divided into so-called depth segments in the depth direction, assuming that X-rays are incident from the edge. Each detector element 22 typically uses a diode with a charge collection electrode as an important component.

[0093] A detector element usually refers to an individual sub-element of a detector that senses X-rays. In general, photon interactions occur on a detector element, and the resulting charge is collected by the corresponding electrode of the detector element. Each detector element usually measures the incident X-ray flux as a series of frames. A frame is a measurement data for a specific time interval called the frame time.

[0094] FIG. 8 is a schematic diagram illustrating an example of a modular X-ray detector that includes several detector sub-modules 21 arranged side-by-side in an overall slightly curved shape relative to an X-ray source located at an X-ray focal spot, for example.

[0095] 9 is a schematic diagram illustrating an example of a modular X-ray detector that includes several detector sub-modules 21 arranged side-by-side and further stacked. The X-ray detector sub-modules are in turn stacked to form larger detector modules that can be assembled side-by-side to create an X-ray detector system.

[0096] As previously mentioned, edge-on is an X-ray detector design in which an X-ray sensor, such as an X-ray detector element or pixel, is designed to face an edge toward the incident X-rays.

[0097] For example, the detector may have detector elements in at least two directions, where one of the at least two directions of the edge-on detector may have a component in the x-ray direction. Such edge-on detectors may also be referred to as depth-segmented x-ray detectors, which have detector elements in two or more depth segments in the direction of the incident x-rays.

[0098] Alternatively, the x-ray detector may not be segmented in depth but rather remain positioned edge-on to the incident x-rays.

[0099] Depending on the detector topology, for example if the detector is a flat panel detector, one detector element may correspond to one pixel. However, a depth-segmented detector may be considered to have several detector strips, each strip having several depth segments. In such a depth-segmented detector, each depth segment may be considered to be a separate detector element, especially if each of the multiple depth segments is associated with a separate charge collection electrode for each depth segment.

[0100] The detector strips of a depth segmented detector typically correspond to the pixels of a typical flat panel detector, but a depth segmented detector can also be viewed as a three-dimensional array of pixels, where each pixel (sometimes called a voxel) corresponds to an individual depth segment / detector element.

[0101] Photon counting detectors have emerged as a viable alternative for some applications, and photon counting detectors are currently commercially available mainly for mammography. Photon counting detectors have the advantage that, in principle, the energy of each x-ray can be measured, thus providing additional information about the composition of the object. This information can be used to improve image quality and / or reduce radiation dose.

[0102] Compared to energy-integrating systems, photon-counting CT has the following advantages: First, the electronic noise incorporated in the signal by the energy-integrating detector can be removed by setting a minimum energy threshold that is higher than the noise floor of the photon-counting detector. Second, energy information can be extracted by the detector, which allows an improved contrast-to-noise ratio by optimal energy weighting and also allows so-called material basis decomposition, by which different materials and / or components of the examined specimen or object can be identified and quantified. Third, more than two reference materials can be used, which is advantageous for discrimination techniques such as K-edge imaging to quantitatively determine the distribution of contrast agents (e.g. iodine or gadolinium). Fourth, the absence of detector afterglow means that a high angular resolution can be obtained. Last but not least, a high spatial resolution can be obtained by reducing the pixel size.

[0103] A problem with X-ray photon counting detectors is the so-called pile-up problem. At high X-ray photon flux rates, there may be problems distinguishing between the two subsequent charge pulses. As mentioned above, the pulse length after filtering depends on the shaping time. If this pulse length is longer than the time between the two charge pulses induced by the X-ray photons, the two charge pulses may merge and the two photons may not be distinguished and may be counted as one pulse. This is called pile-up. Therefore, one way to avoid pile-up at high photon flux is to use a short shaping time or to use depth segmentation as proposed in any embodiment described herein.

[0104] To increase the absorption efficiency, the detector can be placed edge-on, in which case the absorption depth can be chosen to be any length and the detector can be fully depleted without applying very high voltages.

[0105] In particular, silicon has many advantages as a detector material, including its high purity, the low energy required to generate charge carriers (electron-hole pairs), and the high mobility of charge carriers, allowing it to operate at high X-ray rates.

[0106] The solid-state X-Ray detector sub-modules are typically arranged in tiles to form a complete detector of virtually any size with near perfect geometric efficiency (excluding any anti-scatter modules (e.g., tungsten foils or sheets) that may be incorporated between at least some of the solid-state detector modules).

[0107] Further information regarding so-called photon-counting edge-on X-ray detectors in general can be found, for example, in U.S. Patent No. 8,183,535, which discloses an example of a photon-counting edge-on X-ray detector. U.S. Patent No. 8,183,535 describes a plurality of solid-state detector modules arranged to form an overall detector area, each solid-state detector module including an X-ray sensor oriented edge-on with respect to incident X-rays and connected to an integrated circuit for recording X-rays interacting within the X-ray sensor.

[0108] As described, the overall X-ray detector may, for example, use multiple detector sub-modules or multiple wafers, each of which has several depth segments in the direction of the incident X-rays.

[0109] Such multiple detector sub-modules can be arranged one after the other or stacked and / or side-by-side in various configurations to provide any useful detector area or volume. For example, a full detector for a CT application typically has an area of ​​200 cm. 2 It has a larger total area, which requires a large number of detector modules (eg, 1500-2000 detector modules).

[0110] By way of example, multiple detector sub-modules may be arranged side-by-side and / or stacked, for example, in a generally planar configuration or a generally slightly curved configuration.

[0111] It is generally desirable to have as many detector elements and detector segments as possible, as this increases spatial resolution, and smaller electrodes generally reduce electronic noise and improve dose efficiency and energy resolution.

[0112] Since the X-ray interactions occur distributed among different depth segments along the sensor depth (depth length), the overall count rate is distributed among the segments in the depth direction, as can be seen, for example, in Figure 5. Figure 5 is a schematic diagram showing an example of the count rate in each segment. In this example, the first segment is the segment closest to the X-ray source.

[0113] For example, a sensor over 40 mm deep can have 400 or more segments, with the count rate decreasing accordingly. The sensor depth is important for dose efficiency, and segmentation prevents pulse pile-up and maintains the spatial resolution of the system.

[0114] The current may be measured, for example, by an amplifier such as a charge sensitive amplifier (CSA) followed by a filter such as a shaping filter (SF), as shown generally in FIG. 4 above.

[0115] Since the number of electrons and holes from an X-ray event is proportional to the X-ray energy, the total charge of an induced current pulse is proportional to this energy. The current pulse is amplified in a (CSA) amplifier and filtered in a (SF) filter. By appropriately selecting the shaping time of the SF filter, the pulse amplitude after filtering is proportional to the total charge of the current pulse and therefore to the X-ray energy. After the (SF) filter, the value of the pulse amplitude is compared to one or more thresholds (T1-T N ) the pulse amplitude can be measured by comparing it with the threshold. A counter is then provided to record the number of times that the pulse is greater than the threshold. In this way, the pulses detected within a certain time frame and the respective thresholds (T1-T N It is possible to count and / or record the number of X-ray photons having energies greater than the energy corresponding to the x-ray photon count (x-ray photon count).

[0116] When different thresholds are used, a so-called energy-discriminating photon counting detector is obtained, which can sort the detected photons into energy bins corresponding to the various thresholds, and this type of photon counting detector is sometimes called a multi-bin detector.

[0117] In general, energy information allows the creation of new kinds of images that can provide new information and eliminate image artifacts typical of prior art techniques.

[0118] In other words, in an energy-discriminating photon counting detector, the pulse height is detected by a comparator at a number of programmable thresholds (T1-T N ) and classified according to pulse height, which is proportional to the energy.

[0119] However, charge-sensitive amplifiers have an inherent problem of adding electronic noise to the detected current, so to avoid detecting noise instead of real X-ray photons, it is important that the minimum threshold is set high enough so that the number of times the noise value exceeds the threshold is low enough so as not to prevent the detection of X-ray photons.

[0120] By setting the minimum threshold value higher than the noise floor, electronic noise, which is a major obstacle to reducing the radiation dose of X-ray imaging devices, can be significantly reduced.

[0121] Shaping filters have the general property that larger values ​​of the shaping time lengthen the pulses caused by the X-ray photons and reduce the amplitude of the noise after the filter. Smaller shaping times result in shorter pulses and larger noise amplitudes. Therefore, in order to count as many X-ray photons as possible, it is desirable to use as long a shaping time as possible (without causing pile-ups), which minimizes noise and allows the use of relatively small threshold levels.

[0122] The values ​​of the set of thresholds or table of thresholds, which are compared to the pulse heights in the comparator, affect the quality of the image data generated by the photon-counting detector. Furthermore, these thresholds are temperature dependent. Thus, in one embodiment, the calibration data generated by the power dissipation circuitry includes a set of thresholds or table of thresholds (T1-T N ).

[0123] However, it should be understood that it is not necessary to have an energy discriminating photon counting detector, although this has advantages.

[0124] FIG. 10 is a schematic diagram showing an example of a photon-counting X-ray detector, in which several X-ray detector sub-modules 21, referred to here as wafers, are used. A number of wafers 21 are stacked in turn. It can be seen that each wafer has a length (x) and a thickness (y) and that each wafer is divided in depth direction (z), a so-called depth segmentation. By way of example only, the length of the wafers may be of the order of 25-50 mm, the depth of the wafers may also be of the order of 25-50 mm, while the thickness of the wafers may be of the order of 300-900 um.

[0125] As an example, each wafer has detector elements distributed in two directions on the wafer, including the direction of incident x-rays (z).

[0126] Each wafer has a thickness (y) with two opposing surfaces (e.g., a front and a back surface) that are at different potentials to allow charge drift towards the surface on which the detector elements (also called pixels) are typically located.

[0127] To better understand the proposed technology, it is useful to return to the basic ideas of the Compton effect.

[0128] Incident X-ray photons can interact with the semiconductor material of the detector module either by the photoelectric effect (herein simply referred to as the optical effect) or by the Compton interaction (see FIG. 11).

[0129] Compton interaction, also called Compton scattering, is the scattering of a photon by a charged particle, usually an electron. This results in a decrease in the energy of the photon, called the Compton effect. Part of the photon's energy is transferred to the recoil electron. A photon may be involved in multiple Compton interactions during its passage through a semiconductor substrate. Briefly, in a Compton interaction, an incident X-ray photon is deflected from its original path by an interaction with an electron, which is ejected from its initial orbital position, generating so-called secondary or "free" electrons. Such secondary electrons may also be the result of the photo effect, in which the entire energy of the incident X-ray photon is transferred to the electron.

[0130] Specifically, X-ray photons may generate secondary electrons by Compton interaction or photo effect. Electrons gain kinetic energy from X-ray photons and travel short distances (e.g., 1um-50um), generating electron-hole pairs during the travel. Each electron-hole pair requires about 3.6eV to generate, which means that, for example, in a Compton interaction that gives an electron an energy of 15keV, about 4200 electron-hole pairs are generated, forming a so-called charge cloud. This charge cloud moves or drifts following the electric field lines, and if the backside of the detector submodule or wafer is positively biased, the holes move towards the readout electrode located on the frontside of the detector submodule or wafer, and the electrons move towards the backside. During the drift, the electron-hole pairs forming the charge cloud also diffuse, which means that the charge cloud becomes larger.

[0131] The readout electrodes function as detector elements or pixels. As an example, the backside voltage may be about 200V and the frontside may be at virtual ground.

[0132] As will be appreciated, in order to be able to resolve the charge cloud, it may be desirable to subdivide the sensor area to a relatively high resolution, for example 5um to 100um resolution, and orient the X-ray detector edge-on to the beam (i.e. edge-on to the incident X-rays).

[0133] Typically, X-ray photons are converted into electron-hole pairs within the semiconductor material of the X-ray detector, with the number of electron-hole pairs being roughly proportional to the energy of the photon. The electrons and holes drift toward the detector elements and then leave the photon-counting detector. During this drift, the electrons and holes induce a current in the detector elements.

[0134] Non-limiting examples of the proposed technique are now described primarily with reference to photon-counting silicon X-ray detectors, although the invention is also applicable to other types of X-ray detectors.

[0135] Compton interactions in silicon detectors can result in multiple counts from a single photon. In the absence of tungsten shielding, this reduces the signal-to-noise ratio and reduces the spectral information. On the other hand, silicon has a purity and crystalline quality superior to other materials, which allows for very high spatial and spectral resolution. We propose to combine multiple Compton interactions caused by the same incident photon in a probabilistic manner, using the knowledge of the energy deposited at each interaction point.

[0136] Due to silicon's low atomic number, Compton interactions are frequent. In Compton interactions, only a portion of the energy of the incident photon is transferred, and a single incident photon can generate multiple counts. Silicon has been shown to be a competitive material for photon-counting CT detectors, but to further improve performance, it would be desirable to combine multiple Compton-scattered photons using coincidence techniques.

[0137] For example, scattered photons can be removed with a tungsten shield or similar anti-scatter module, leaving Compton counts that contain little energy information but correspond to unique photons and contribute to image contrast as photon counts. However, if a photon deposits energy through a series of interactions with a photoelectric event, the total photon energy can be estimated by adding up the energy deposited by the series of interactions. Extracting this information is desirable because it improves the spectral performance of the detector.

[0138] Because Compton scattered photons can be distinguished based on their energy and scattering angle, the inventors realized that it is possible to distinguish interactions belonging to the same photon based on the interaction position and the energy deposited. Higher spatial and energy resolution increases the likelihood of finding the correct combination of interactions.

[0139] Furthermore, the inventors have recognised the feasibility of using coincidence techniques to identify and combine interactions belonging to the same incident photon to improve the signal-to-noise ratio and spectral performance of photon-counting X-ray detectors, which is particularly useful for silicon X-ray detectors.

[0140] In silicon detectors, some of the incident photons interact with each other through Compton interactions. In Compton interactions, only a portion of the energy of the incident photon is transferred, resulting in multiple interactions from a single photon. To eliminate this possibility, a tungsten shield can be used to remove secondary interactions. Since each resulting Compton count corresponds to a unique photon, Compton counting is not a penalty but rather a contribution to imaging performance. Compton counting is particularly important for density imaging tasks, but also improves the contrast of spectral images, as described in "Photon-counting spectral computed tomography using silicon strip detectors: a feasibility study", H. Bornefalk and M. Danielsson, Physics in Medicine and Biology 55, 1999-2022, 2010.

[0141] To further improve the performance of silicon detectors, it is desirable to use a coincidence technique to detect Compton scattered photons instead of (or in combination with) a tungsten shield. In a detector without a tungsten shield, many photons interact in a series of Compton interactions due to a photoelectric event. If the total photon energy is deposited in the detector, the energy of the incident photon can be found by adding the energy deposited in the series of interactions. Identifying and combining interactions belonging to the same photon is more efficient in achieving high spatial and energy resolution.

[0142] Our patent applications US16 / 653200 and PCT / SE2019 / 051011 propose a method to achieve 1um resolution with photon-counting silicon detectors.

[0143] The present invention aims to assess whether the achieved spatial resolution can be used to distinguish Compton scattered photons, for example based on timing information of the photon interaction (optionally in combination with information of the deposited energy and the position of the interaction).

[0144] A non-limiting objective of this work is to evaluate the feasibility of using coincidence techniques to identify and combine interactions belonging to the same incident photon to improve the signal-to-noise ratio and spectral performance of X-ray detectors, such as silicon photon counting detectors.

[0145] Non-limiting examples The well-known GATE simulation toolkit was used to model a silicon detector and deliver an X-ray beam with photon energies sampled from the spectrum of an X-ray source operating at 120 kVp, with a means to create 30 cm of soft tissue filtering between the X-ray source and the detector.

[0146] For more information on the GATE simulation toolkit, see “GATE: a simulation toolkit for PET and SPECT”, S. Jan, G. Santin, D. Strul, et al., Physics in Medicine and Biology 49, 4543-4561, 2004.

[0147] For each interacting photon, the energy and position of the resulting interaction was detected along with the type of interaction (photoelectric, Compton).

[0148] The resulting data was organized into smaller subsets, each representing interactions occurring at the detector during a certain time window (snapshot). The interactions within each snapshot were then characterized for their energy and position. A maximum likelihood method was then implemented to classify the interactions according to their most likely interaction chains.

[0149] Illustrative Results The following table shows an example of the probability of interaction chains in a silicon detector without tungsten shielding. TIFF0007625687000001.tif170167Table 1: Probability of interaction chains in a silicon detector without tungsten shielding

[0150] 12 is a schematic diagram showing an example of the spectrum of the deposited energy of the Compton and photoelectric parts of the interaction spectrum. The vertical dashed line indicates the Compton threshold, above which 99.75% of all photoelectric interactions occur, and below which 99.70% of all Compton interactions occur.

[0151] Figure 13 is a schematic diagram showing an example of interactions in one snapshot, i.e. during a time interval: the black lines show interactions belonging to the same incident photon.

[0152] FIG. 14 is a schematic diagram showing an example of a 1D scattering distance in an interaction chain (one Compton interaction + one photoelectric interaction).

[0153] FIG. 15 is a schematic diagram showing an example of the spectrum of incident photon energy for different interaction chains.

[0154] Thus, the dynamics of interactions in photon-counting X-ray (silicon) detectors, e.g. for spectral CT, was investigated and characterized. Furthermore, the feasibility of using Compton coincidence techniques to identify and combine interactions belonging to the same incident photon (e.g. based on maximum likelihood) was evaluated and the effect of Compton coincidence techniques on the spectral performance of the detector was shown. The proposed technique allows realizing an ideal X-ray detector with very high energy resolution and very high position resolution for each incident photon.

[0155] We have demonstrated that it is possible to distinguish between photoelectric and Compton interactions in X-ray detectors such as silicon detectors, and to characterize different interaction chains based on the photon energy and scattering distance. As a result, it has been shown that it is possible to identify interactions belonging to the same incident photon based on the energy imparted and the interaction position.

[0156] Conventional coincidence detection techniques can generally be found in Compton cameras used in nuclear medicine and astrophysics, and are described, for example, in: R. Todd, J. Nightingale, D. Everett, A proposed γ camera. Nature 251, 132-134 (1974). https : / / doi.org / 10.1038 / 251132a V. Schonfelder, A. Hirner, K. Schneider, A telescope for soft gamma ray astronomy, Nuclear Instruments and Methods, Volume 107, Issue 2, 1973, Pages 385-394, https: / / doi.org / 10.1016 / 0029-554X(73)90257-7. To determine the location of the emission source, the incident gamma photons are detected using a Compton camera. In nuclear medicine, the incident photons are monoenergetic, but for astrophysics applications a wide energy spectrum (in the keV-MeV range) is included.

[0157] The present invention provides a solution for using and / or improving coincidence detection techniques, such as the Compton coincidence technique, in X-ray detectors that detect photons of many different energies when the position of the emission source is known.

[0158] Compton gamma cameras including coarse collimators to limit the acceptance angle of the incident radiation have been previously proposed in the field of nuclear medicine, see for example U.S. Pat. No. 7,291,841, which describes the use of highly localized sources in X-ray photography and how focal X-ray optical collimators can be designed for specific X-ray tube focal spot distributions. In contrast, a coincidence detection method is described herein in which the position of the source is used in coincidence techniques.

[0159] For applications in nuclear medicine (such as single photon emission computed tomography (SPECT) and, in some applications, positron emission tomography (PET)), Compton cameras usually have two different detectors (scatterer and detector), for example Si+CdTe can be used (see the following paper “Compton imaging with 99mTc for human imaging”, M. Sakai,Y. Kubota, RK Parajuli et al. Sci Rep 9, 12906 (2019), doi: 10.1038 / s41598-019-49130-z)

[0160] In contrast, the present invention proposes a coincidence detection method that can be used with a single silicon detector.

[0161] In a Compton camera such as Si+CdTe, the incident photon undergoes Compton scattering in the silicon and photoelectric interaction in the CdTe, meaning that the total photon energy is deposited in the detector. The direction of the incident photon can be determined based on the interaction position and the deposited energy using the Compton scattering equation.

[0162] It has been proposed to perform gamma-ray tracking with Ge detectors to distinguish interactions belonging to the same incident photon and obtain the gamma-ray energy along with the direction of the incident photon, as described, for example, in IY Lee, Gamma-ray tracking detectors, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Volume 422, Issues 1-3, 1999, pages 195-200, https: / / doi.org / 10.1016 / S0168-9002(98)01093-6.

[0163] However, in many applications, such as computed tomography (CT), it is important to quantify the number of incident photons and their energy instead of determining their direction. Therefore, coincidence detection methods in this application have quite different requirements. These requirements include identifying interactions that belong to the same incident photon to avoid double counting of single photons, and combining the interactions to obtain the energy of the incident photon. Also, computed tomography requires a higher incident photon flux, which makes it difficult to use coincidence techniques.

[0164] Various detector systems have been described in the past, including CT and Compton cameras (see, e.g., U.S. Patent 10,088,580, U.S. Patent 10,067,239, WO2017015473A8, U.S. Patent 10,274,610, U.S. 2018 / 0172848A1, U.S. Patent 10,365,383, and U.S. 2020 / 0096656A1). None of these documents includes a localized source where the location of the source can be used in a coincidence detection method, as described herein.

[0165] Most conventional coincidence methods rely solely on time, meaning that two interactions with the same timestamp are automatically assigned to the same photon.

[0166] In many applications and / or situations of interest, there is a high probability that interactions belonging to multiple photons exist within the same time window. This necessitates more sophisticated coincidence counting methods, such as finding the optimal solution (number of incident photons and energy of the incident photons) that corresponds to the detected interaction. The proposed technique provides such an advanced solution.

[0167] Other design considerations include: A system and / or processing method for coincidence detection needs to be able to separate photoelectrons and Compton scattered photons.

[0168] To simplify the implementation and use of coincidence detection methods, it may be desirable to omit the identification of long interaction chains.

[0169] There is usually a trade-off between recognizing too many coincidences and recognizing too few. Ideally, there should be one detected event for each incoming photon. However, recognizing too many coincidences will result in some events being falsely dropped. On the other hand, recognizing too few coincidences will result in multiple detected events due to a single photon.

[0170] Even interaction chains in which the entire photon energy is not deposited in the detector are advantageous for discrimination, since they eliminate double counting.

[0171] Without the use of a tungsten shield or similar anti-scatter module, many photons deposit their full energy into the detector, but this results in longer interaction chains, which makes it more difficult overall to properly combine the interactions. The use of a tungsten shield makes it easier to combine the interactions by removing the long interaction chains, but it also reduces the number of photons that deposit their full energy into the detector, reducing the overall spectral information.

[0172] Coincidence counting can be performed as a post-processing step or can be performed directly in the detector electronics during data acquisition. Post-processing requires data output of the deposited energy and interaction position for each interaction. Coincidence counting in the detector impacts the detector design and may require electronics and / or software specifically designed to perform coincidence counting techniques.

[0173] Coincidence detection techniques can be applied continuously as events are detected, or they can be applied to interactions that occur within a time window (snapshot).

[0174] High spatial resolution is usually required to obtain the angle between the interactions, and high energy resolution may be required to properly detect the energy deposited in each event.

[0175] Thus, the basic idea is to quantify the number of incoming photons and their energy based on the timing of the photon interactions (optionally combined with information about the interaction position at the detector and the energy deposited).

[0176] By way of example, this quantification can be done by identifying and combining interactions belonging to the same incident photon based on the interaction position and the deposited energy, or by ignoring the identification and combination steps and more directly deriving the number of incident photons and their energy from the interaction position and the deposited energy.

[0177] Below are non-limiting examples of novel coincidence methods and / or procedures. 1. The energy and position of each interaction are detected. 2. Based on the interaction energy, the interactions are classified as Compton interactions or photoelectric interactions. 3. From the detected interactions, possible interaction chains are created. Each interaction chain represents the interactions from a single incident photon. An example of an interaction chain could be, for example, one Compton interaction + one photoelectric interaction. 4. For each possible interaction chain, calculate the distance and angle between the interactions along with the total energy and photon energy deposited between successive interactions. 5. The distance, angle and energy are then used to estimate the likelihood function for each interaction chain, which may be based on, for example, the Compton scattering equation, the Klein-Nishina equation, the Beer-Lambert law or the interaction cross section. 6. The interactions are classified according to the interaction chain that maximizes the likelihood function.

[0178] Some steps are optional and may be performed to combine a single interaction with nearby interactions and / or to sort a set of interactions to obtain several interaction chains.

[0179] This method can also be used to directly obtain the number and energy of incident photons from a set of interaction positions and deposited energies (e.g., where a likelihood function is obtained by simulating incident photons of well-defined energies and collecting the interactions obtained at the detector for the interaction type, position, and deposited energy as a result of the simulation).

[0180] When assigning interaction chains to a large set of interactions, it may be desirable to initially assign each interaction to an interaction chain randomly or using a probability-based method, resulting in an initial set of interaction chains that is then iteratively modified to maximize the collective likelihood of the constructed interaction chains, resulting in a set of the most likely interaction chains.

[0181] Alternatively, it is possible to apply methods that use machine learning to determine the number of incident photons and the energy of the incident photons. This can be done by using deep neural networks to identify and combine interactions that belong to the same incident photon based on the location of the interaction and the energy imparted. Both supervised and unsupervised learning can be applied, as can reinforcement learning.

[0182] According to another alternative, a method is provided for determining the number of incident photons and the energy of the incident photons using a decision tree approach. This can be done by combining interactions that meet certain criteria based on the interaction location and the energy deposited. For example, two interactions are combined if they are within a certain distance of each other and the sum of the energy deposited by the two interactions exceeds a certain value.

[0183] Optionally, the present invention can be combined with techniques that allow for estimating the initial point of interaction of X-ray photons in a photon-counting X-ray detector, as described below.

[0184] As a complementary aspect, it is desirable to be able to improve the estimation of the initial point of interaction of X-ray photons in a photon-counting X-ray detector in which several X-ray detector sub-modules or wafers are used, each of which contains detector elements, and which are arranged such that the edges are edge-on oriented towards the X-ray source, assuming that the X-rays are incident through the edges.

[0185] Each detector sub-module or wafer has a thickness with two opposing sides (e.g., a front / main side and a back side) that are at different potentials to allow charge drift towards the (front / main) side where the detector elements (also called pixels) are located.

[0186] It is possible to determine an estimate of charge diffusion due to photoelectric interaction or Compton interaction associated with X-ray photons in a (specific) detector sub-module or wafer of the X-ray detector, and based on the determined charge diffusion estimate, estimate an initial point of interaction at least partially along the thickness direction of the detector sub-module.

[0187] As an example, the shape, particularly the width, of the charge spread can be measured or estimated, and based on the shape or width of the charge spread or charge distribution the distance between the initial point of interaction and the detection point can be determined.

[0188] For example, the charge diffusion is represented by a charge cloud, and the detector elements distributed over the main surface of a detector sub-module or wafer may realize an array of pixels, the pixels being generally smaller than the charge cloud to be resolved.

[0189] As previously mentioned, the X-ray detector sub-module may be positioned such that the edge is edge-on, directed towards the X-ray source, assuming that the X-rays are incident through the edge.

[0190] Edge-on is an X-ray detector design that means that the X-ray sensors, such as X-ray detector elements or pixels, are oriented edge-on with respect to the incident X-rays.

[0191] As an example, each of the X-ray detector submodules may include detector elements distributed in two directions including the incident direction of X-rays in the detector submodule or wafer. This usually corresponds to a so-called depth-segmented X-ray detector submodule. However, the proposed technique is also applicable to an X-ray detector submodule that is not segmented in the depth direction. A plurality of detector elements are arranged like an array in a direction substantially perpendicular to the direction of the incident X-rays, but each detector element is arranged edge-on with respect to the incident X-rays. In other words, the X-ray detector submodule may be arranged edge-on with respect to the incident X-rays but not divided in the depth direction.

[0192] In certain examples, at least some of the detector elements or pixels have a larger size in the direction of the incident x-rays than they have a size in a direction perpendicular to the direction of the incident x-rays, such that there is at least a 2:1 relationship, i.e., the detector elements or pixels are asymmetric in geometric design, such that the detector elements or pixels are at least twice as long (deep) in the direction of the incident x-rays as they are in a direction perpendicular to the direction of the incident x-rays.

[0193] Optionally, the initial point of interaction of the incident X-ray photon in the thickness direction of the detector sub-module is estimated based on the measured width of the cloud and the total charge of the cloud. As explained, the charge cloud can be represented by an induced current in the detector element caused by the operation of the detector sub-module.

[0194] As an example, it is possible to determine an estimate of the distance between the detection point of an X-ray photon in the detector submodule and the initial point of interaction, the distance along the thickness of the detector submodule, based on an estimate of the charge diffusion, and to determine an estimate of the initial point of interaction based on the determined estimate of the distance between the detection point and the thickness of the detector submodule.

[0195] The interaction is between X-ray photons and a semiconductor substrate, typically a substrate made of silicon.

[0196] The thickness of a detector sub-module or wafer generally refers to the length between two opposite sides (eg, back and front) of a detector sub-module.

[0197] As an example, the shape, particularly the width, of the charge spread can be measured or estimated and based on the shape or width of the charge spread or charge distribution the distance between the detection point and the initial point of interaction can be determined.

[0198] As an example, a system can be provided that allows for estimating the initial point of interaction of an X-ray photon in a photon-counting X-ray detector. The X-ray detector can use several X-ray detector sub-modules or wafers, each X-ray detector sub-module or each wafer containing a detector element. The X-ray detector sub-modules can be positioned such that the edge is edge-on, directed towards the X-ray source (10), assuming that the X-rays are incident through the edge.

[0199] Each detector sub-module or wafer has a thickness with two opposing faces, which are at different potentials to allow charge drift towards the face on which the detector elements (also called pixels) are located.

[0200] The system can then determine an estimate of charge diffusion due to photoelectric interaction or Compton interaction associated with X-ray photons in a detector sub-module or wafer of the X-ray detector, and estimate an initial point of interaction along a thickness direction of the detector sub-module based on the determined estimate of charge diffusion.

[0201] FIG. 16 is a schematic diagram showing an example of pixels of a portion of a particular wafer in the xz plane. In this embodiment, the pixels 22 are typically smaller than the charge cloud to be resolved. For example, the charge cloud may have a width on the order of 100 um, and therefore the pixels are typically designed to be smaller or much smaller than the charge cloud. Thus, an X-ray photon passing through the semiconductor substrate typically creates a charge cloud that covers multiple adjacent pixels of the detector module. This means that a single X-ray photon is likely to trigger an event to be detected in multiple pixels.

[0202] Although the pixels 22 are illustrated as squares, it should be understood that the pixels may be rectangular or have other shapes.

[0203] In a particular example, information about the charge diffusion can be used to improve the resolution in at least one of two directions along which the detector elements are distributed on the front side of the detector sub-module or wafer. For example, the resolution can be improved based on information about the charge cloud profile in one of two directions or in both directions. Possible directions include the length (x) direction and / or the depth (z) direction of the detector sub-module or wafer.

[0204] By way of example, the method further comprises a step of determining an estimate of the point of interaction of the incident X-ray photon in at least one of two directions (x, z) in which the detector elements are distributed on the main surface of the X-ray detector sub-module or wafer.

[0205] For example, the step of determining an estimate of the point of interaction of an incident X-ray photon in at least one of the two directions (x, z) in which the detector elements are distributed on the main surface can be performed based on information of the charge cloud profile in one or both of the two directions (x, z) in which the detector elements are distributed on the main surface of the X-ray detector sub-module or wafer.

[0206] FIG. 17 is a schematic diagram illustrating an example of a charge cloud profile in the x-direction of the charge cloud.

[0207] FIG. 18 is a schematic diagram illustrating an example of a charge cloud profile in the z-direction of the charge cloud.

[0208] As an example, the figure shows that one or more charge cloud profiles (see, e.g., Figs. 17 and 18) are determined and curve fitting is performed using any common curve fitting method, such as weighted average and / or least squares. For example, by finding where the curve has a peak and identifying the peak as a point of interaction in a particular direction, the resolution can be improved to sub-pixel resolution (e.g., to 1 um resolution). This is in contrast to the spatial resolution of conventional x-ray imaging systems, which is approximately 1 mm.

[0209] Alternatively, information representing which pixel 22 detected the highest charge can be used as the point of interaction. For example, the step of determining an estimate of the point of interaction of an incident X-ray photon in at least one of the two directions (x, z) in which the detector elements are distributed on the main surface side can be performed by identifying the pixel that detected the highest charge as the point of interaction.

[0210] However, it should be understood that by using appropriate curve fitting as described above, sub-pixel resolution can be obtained.

[0211] As indicated above, the inventors have realised that in the thickness (y) direction of the detector sub-module or wafer, the point of detection of a photon may differ significantly from the point of initial interaction.

[0212] After careful analysis and experimentation, the inventors further realized that the shape, particularly the width, of the charge spread or charge cloud depends on the distance from the point of initial interaction to the detection point through the thickness of the detector submodule or wafer of interest of the X-ray detector. This is shown diagrammatically in Figure 19 for three different distances or depths (100 μm, 300 μm, and 600 μm).

[0213] For example, if the cross-section of the charge cloud is not circular but is elliptical or of some other shape, and therefore has different extents in different directions in the zx-plane, it is recommended to use the minimum width of the cross-section of the charge cloud as a relevant measure of charge spreading.

[0214] During the charge cloud movement, the charges diffuse and this diffusion is accelerated by electrostatic repulsion. The induced current is dominated by the movement of charges occurring near the front surface. Since diffusion is a function of time, the width of the charge cloud will be wider (when collected at the front surface) if the interaction occurs near the back surface (where the time is longer) compared to near the front surface (where the diffusion contributed by the charge carriers is negligible). Knowing the total energy (integrated charge of the electron-hole cloud) and the width of the cloud allows an estimation of the interaction point through the thickness of the edge-on-wafer.

[0215] When simultaneous or nearly simultaneous events are detected (in the xy plane) at adjacent detector elements in the area of ​​the photon counting detector, depth information (in the z direction) can also be obtained that indicates the interaction point between the incident X-ray photon and the semiconductor material. Thus, as shown diagrammatically in FIG. 19, a larger detection area results in a wider charge spread, which means that the interaction points are farther apart (e.g., 600 μm) compared to a smaller detection area and narrower charge spread (e.g., 100 μm). Experiments have shown that the resolution can be improved considerably, for example to 50 μm. This is a significant improvement compared to simply knowing on which wafer the interaction occurred. It is also possible to know where in the thickness of the wafer the initial interaction point occurred, within a resolution of about 50 μm.

[0216] 20 is a schematic diagram of a detector module, also referred to as a chip or wafer, according to one embodiment. In this example, the detector module 21 includes a semiconductor substrate or material that includes a plurality of active integrated pixels disposed on the semiconductor substrate. In a particular embodiment, the plurality of active integrated pixels are arranged in a grid or matrix pattern or other pattern on a major surface (front surface) of the semiconductor substrate, as shown. Also shown in this figure is the arrangement of pixels in different depth segments with respect to an edge facing the x-ray source and where the x-rays are incident on the detector module.

[0217] In one embodiment, the detector module also includes other processing circuitry, such as analog and / or digital processing circuitry, illustrated in this figure as readout circuitry, control circuitry, and analog-to-digital conversion (ADC) circuitry, which may be implemented in or as one or more ASICs.

[0218] The other processing circuitry is advantageously located on the same main surface of the semiconductor substrate as the active integrated pixels. In that case, the other processing circuitry is preferably located on or in relation to an edge of a portion of the main surface away from the X-ray source and the incident X-rays, as shown in the figure. In this embodiment, the dead area of ​​the detector module is reduced by reducing the portion of the detector module used for the other processing circuitry. Furthermore, the other processing circuitry is protected from the incident X-rays by being located furthest from the incident edge.

[0219] FIG. 20 also shows a schematic representation of an active integrated pixel with a so-called detector diode (electrode) together with readout electronics and interconnects. Each such active integrated pixel typically has a size in the μm range. In one embodiment, the active integrated pixel is square, and typically all active integrated pixels in a detector module have the same shape and size. However, it is possible to use pixels of other shapes, such as rectangular, and / or to have active integrated pixels of different sizes and / or shapes in the same detector module, as shown in FIG. 21. In FIG. 21, the active integrated pixels have the same width, but different depth lengths. For example, the depth length of the active integrated pixels increases according to the distance to the edge of the detector module where the X-rays are incident, for different depth segments. This means that the active integrated pixels at the edge preferably have a smaller depth length compared to the active integrated pixels closest to the opposite edge. In such an embodiment, the detector module may include active integrated pixels with two or more different depths.

[0220] Different pixel depths, particularly pixel depths depending on the depth segment or the distance to the edge where the X-rays impinge on the detector module, can be used to adjust the probability or likelihood of detecting an event at the active integrated pixel.

[0221] According to certain aspects of the proposed technology, all or part of the analog signal processing (e.g. the analog processing illustrated in FIG. 4) can be integrated into the pixel, thereby forming a so-called actively integrated pixel.

[0222] As mentioned above, one aspect of the present invention relates to an edge-on photon counting detector that includes at least one detector module having an edge facing incident x-rays, the at least one detector module including a semiconductor substrate.

[0223] In a particular example, the edge-on photon counting detector also includes a plurality of active integrated pixels disposed on the semiconductor substrate.

[0224] In one embodiment, the edge-on photon counting detector includes multiple detector modules arranged side-by-side and / or stacked.

[0225] Edge-on photon counting detectors are typically fabricated using silicon as the semiconductor material of the detector module.

[0226] To compensate for the low stopping power of silicon, detector modules are typically placed in an edge-on geometry with their edge facing the x-ray source, which increases the absorbing thickness. To address the high photon flux in clinical CT, it is preferable to segment the active integrated pixel structure in depth, which is achieved by embedding individual active integrated pixels in depth segments of a silicon substrate.

[0227] In a particular embodiment, the semiconductor substrate is made of float zone (FZ) silicon. FZ silicon is high purity silicon obtained by vertical zone melting method. In the vertical configuration, the molten silicon has sufficient surface tension to prevent separation of the charged parts. Contamination of the silicon can be prevented because no containment vessel is required. Therefore, the concentration of light impurities in FZ silicon is very low. The diameter of FZ silicon wafers is generally not larger than 200 mm due to the surface tension limit during growth. A polycrystalline rod of ultra-high purity silicon for the electronics industry is inserted into an RF heating coil to form a local molten zone from which the crystal ingot is grown. A seed crystal is used at one end to start the growth of the crystal. All steps are performed in a vacuum chamber or in an inert gas purge. The molten zone carries impurities and therefore reduces the impurity concentration. Special doping techniques such as core doping, pill doping, gas doping, and neutron transmutation doping may be used to ensure a uniform concentration of impurities.

[0228] The semiconductor substrate, in one embodiment, is made of high resistivity silicon, such as high resistivity FZ silicon, where high resistivity silicon is defined herein as single crystal silicon having a bulk resistivity greater than 1 kΩcm.

[0229] The active integrated pixels may be implemented as an active integrated complementary metal oxide semiconductor (CMOS) pixel on a semiconductor substrate, and thus the analog circuitry of the active integrated pixel may be fabricated using CMOS technology.

[0230] Figures 22 to 25 show various embodiments of an active integrated pixel with different analog readout electronics within the pixel, in which the current generator of the pixel is shown as a diode outputting a current pulse or diode signal.

[0231] 22 is a diagram illustrating an embodiment of an active integrated pixel that includes an amplifier that generates an output signal based on the current pulses generated by the active integrated pixel or diode. In one embodiment, the amplifier is a charge sensitive amplifier (CSA) that integrates the current pulses into a voltage signal.

[0232] The output signal (e.g., a voltage signal) from the amplifier (preferably a CSA) is, in this embodiment, sent to external processing circuitry (e.g., in the form of one or more ASICs) located on the semiconductor substrate of the detector module (see READ-OUT, CTRL, and ADC in Figures 20 and 21).

[0233] As the number of active integrated pixels in a detector module increases, the number of counts per pixel decreases, and the noise requirements are also relaxed. This means that relatively low-power and low-bandwidth amplifiers can be used for the active integrated pixels. Furthermore, due to the nature of diodes, single-ended amplifiers are preferred. This allows the use of less complex amplifiers. The smaller the diode capacitance, the less dominates the reference input noise from the amplifier compared to using larger pixel sizes.

[0234] 23 shows another embodiment of an active integrated pixel, which in addition to the amplifier includes a pulse shaper (also called a shaping filter), which is configured to filter the output signal from the amplifier.

[0235] The current pulse from the diode is preferably integrated using a CSA, which typically produces a slow-moving voltage at the output of the CSA. To compensate for this behavior, a cancellation circuit (CC), such as a pole-zero cancellation circuit, is placed and connected to the CSA and the pulse shaper. This pole-zero CC cancels or at least suppresses the slow response of the CSA while maintaining the charge integration / current integration. Therefore, the time constant is instead determined by the shaper integration time of the pulse shaper.

[0236] The output signal from the pulse shaper, in this embodiment, is sent to external processing circuitry (such as in the form of one or more ASICs) located on the semiconductor substrate of the detector module (see READ-OUT, CTRL, and ADC in Figures 20 and 21).

[0237] Fig. 24 shows another embodiment of an active integrated pixel. This embodiment includes an analog storage connected to the pulse shaper and arranged downstream of the pulse shaper. This analog storage can be implemented in the active integrated pixel to at least temporarily store and save the output signal from the pulse shaper. This allows to control the readout of data from the active integrated pixel and the analog storage based on a control signal (ctrl) or at scheduled times (e.g. controlled based on a clock signal (clk)).

[0238] An analog storage unit as shown in Figure 24 can also be used in an embodiment as shown in Figure 22 (i.e., an embodiment without a pulse shaper) in which case the analog storage unit is connected to the amplifier (CSA) or connected to the amplifier (CSA) through a pole-zero CC.

[0239] In yet another embodiment as shown in Figure 25, the pixel includes an event detector, represented in this figure as a comparator, which detects photon events by comparing the pulse amplitude of the output signal from the pulse shaper with a threshold (in this figure, a noise threshold).

[0240] In certain embodiments, the event detector generates a trigger signal based on comparing the pulse amplitude to a threshold, preferably generating the trigger signal if the pulse amplitude is equal to or exceeds the threshold.

[0241] In this embodiment, the readout of the analog storage can be controlled by a trigger signal output by the event detector, and thus the readout of the analog storage data preferably occurs only when the event detector determines that the active integrated pixel has detected a photon event having a pulse amplitude above (or equal to) the noise floor represented by the noise threshold.

[0242] In other words, the comparator acting as an event detector can be used to send a signal to a readout circuit, typically located outside the active integrated pixel (see READ-OUT in Fig. 20 and Fig. 21). This readout circuit reads out the data from the analog storage based on a trigger signal from the event detector. The readout data is then compared with a threshold value (T1-T N ) (see FIG. 4) and / or digitized in an ADC (see FIGS. 20 and 21).

[0243] When the analog storage unit is not being read, the data can be continuously flushed, for example by operating in a first-in, first-out (FIFO) manner, allowing data to be read from the analog storage unit asynchronously, thereby reducing power consumption during reads.

[0244] A trigger signal from the event detector may also be provided to adjacent active integrated pixels of the detector module to trigger them to store data which may then be read out for further processing, allowing characteristics of the data to be detected without exceeding a noise threshold.

[0245] In another embodiment, the readout of the analogue store is performed not only by a trigger signal from the event detector of the active integrated pixel, but also by respective trigger signals from at least one adjacent active integrated pixel of the detector module.

[0246] By implementing an active integrated pixel, the size of the pixel can be reduced compared to conventional solutions. By reducing the active integrated pixel size, multiple active integrated pixels of a detector sub-module can detect the charge cloud generated by a single X-ray photon. This makes it possible to determine an estimate of the charge diffusion resulting from a Compton interaction or an interaction due to a light effect associated with an X-ray photon in a particular detector sub-module of an edge-on photon counting detector, as described above, and to estimate an initial point of interaction of the X-ray photon in the thickness direction of the detector sub-module based at least in part on the determined estimate of the charge diffusion.

[0247] It will be understood that the methods and apparatus described herein can be combined or rearranged in various ways.

[0248] For example, certain functions may be implemented in hardware, or implemented in software and executed by suitable processing circuitry, or a combination thereof.

[0249] The processes, functions, procedures, modules and / or blocks described herein can be implemented in hardware using any conventional technology, such as semiconductor technology, discrete circuitry or integrated circuit technology, including both general purpose electronic circuitry and application specific circuitry.

[0250] Specific examples include one or more appropriately configured digital signal processors or other known electronic circuits, such as discrete logic gates or application specific integrated circuits (ASICs) interconnected to perform a specialized function.

[0251] Alternatively, at least some of the processes, functions, procedures, modules and / or blocks described herein may be implemented in software, such as a computer program executed by suitable processing circuitry, such as one or more processors or processing units.

[0252] Examples of processing circuitry include, but are not limited to, one or more microprocessors, one or more digital signal processors (DSPs), one or more central processing units (CPUs), video acceleration hardware, and / or any suitable programmable logic circuitry, such as one or more field programmable gate arrays (FPGAs) or one or more programmable logic controllers (PLCs).

[0253] It should also be understood that it is possible to reuse the general processing capabilities of conventional devices or units in which the proposed technology is implemented, and it is also possible to reuse existing software by reprogramming the existing software or by adding new software components.

[0254] According to another aspect, an X-ray imaging system is provided that includes an X-ray detector system and / or a coincidence detection system.

[0255] By way of example, the x-ray imaging device may be a computed tomography (CT) device.

[0256] In certain embodiments, the X-ray imaging system further comprises an associated image processor connected to the X-ray detector system for performing image reconstruction.

[0257] According to a fourth aspect, there is provided a corresponding computer program and computer program product.

[0258] In particular, a computer program is provided that includes instructions which, when executed by a processor, cause the processor to perform the methods described herein.

[0259] For example, a computer program product may also be provided that includes a non-transitory computer readable medium having such a computer program stored thereon.

[0260] FIG. 26 is a schematic diagram illustrating an example of a computer implementation according to an embodiment. In this particular example, the system 200 includes a processor 210 and a memory 220. The memory 220 includes instructions executable by the processor, thereby enabling the processor to perform the steps and / or operations described herein. The instructions are typically configured as computer programs 225 and 235. The instructions may be preconfigured in the memory 220 or may be downloaded from an external memory device 230. Optionally, the system 200 includes an input / output interface 240 that may be interconnected to the processor 210 and / or the memory 220 to allow for input and / or output of relevant data, such as input parameters and / or resulting output parameters.

[0261] In a particular embodiment, the memory includes a set of instructions executable by the processor, whereby the processor is operable to determine an estimate or measurement of charge spread and to estimate an initial point of interaction in the thickness direction of the detector sub-module based on the determined estimate of charge spread.

[0262] The term "processor" should be construed in a general sense as any system or device capable of executing program code or computer program instructions to perform specific processing, decision making, or computational tasks.

[0263] Thus, processing circuitry, including one or more processors, is configured to perform well-defined processing tasks as described herein when executing computer programs.

[0264] The processing circuitry need not be specialized solely to perform the steps, functions, procedures and / or blocks described above, but may perform other tasks.

[0265] The proposed technology also provides a computer program product including computer readable media 220 and 230 having a computer program stored thereon.

[0266] As an example, the software or computer programs 225 and 235 may be realized as computer program products, typically carried or stored on computer readable media 220 and 230, particularly non-volatile media. The computer readable media may include one or more removable or non-removable memory devices, including but not limited to read-only memory (ROM), random access memory (RAM), compact discs (CDs), digital versatile discs (DVDs), Blu-ray discs, universal serial bus (USB) memories, hard disk drive (HDD) storage devices, flash memories, magnetic tapes, or any other conventional memory devices. Thus, the computer programs can be loaded into the operating memory of a computer or equivalent processing device and executed by its processing circuitry.

[0267] A method flow can be considered as a computer operation flow when executed by one or more processors. The corresponding device, system and / or apparatus may be defined as a group of functional modules, where each step executed by a processor corresponds to a functional module. In this case, the functional modules are implemented as computer programs executed on a processor. Thus, the device, system and / or apparatus can alternatively be defined as a group of functional modules, where the functional modules are implemented as computer programs executed on at least one processor.

[0268] Thus, the computer programs resident in the memory may be configured as appropriate functional modules that, when executed by the processor, perform at least a portion of the steps and / or tasks described herein.

[0269] The modules may also be implemented primarily as hardware modules, or may be implemented in hardware as pure hardware logic. The proportion of software and hardware is simply a matter of implementation choice.

[0270] FIG. 27 is a schematic flow diagram illustrating an example of a method for obtaining or determining information about radiation incident on an X-ray detector.

[0271] Basically, the method includes the following steps:

[0272] S1: Using a photon-counting X-ray detector to detect X-rays, the photon-counting X-ray detector operating in a broad energy band of the X-ray spectrum having a maximum energy of less than 160 keV emitted from a localized X-ray source.

[0273] S2: Detecting timing information of photon interactions in the photon-counting X-ray detector.

[0274] S3: Obtaining or determining information about X-rays incident on the X-ray detector based on the timing information and information about the position of the X-ray source relative to the X-ray detector, the information including at least one expression of the number of incident photons in a specific area, the spatial distribution of the incident photons, and the energy distribution of the incident photons.

[0275] In a specific, non-limiting example, obtaining or determining information about the x-rays incident on the x-ray detector includes the following steps. identifying at least one set of photon interactions based on the likelihood of the set of lattice interactions resulting from a single photon incident on the X-ray detector, wherein detected timing information for the set of photon interactions corresponds to all photon interactions in the set resulting from a single incident photon; The likelihood is calculated based on the position of the X-ray source relative to the X-ray detector, At least one of the following: the Compton scattering equation, the Klein-Nishina equation, the Beer-Lambert law, the X-ray interaction cross section for the photoelectric effect, the Compton effect, or Rayleigh scattering, and a simulation of photon transport. The method is based on the steps of: Obtaining or determining information regarding at least one of the number of incident photons, the spatial distribution of incident photons, and the energy distribution of incident photons in a particular region based on the set or the likelihood of photon interactions.

[0276] Other exemplary and optional method steps have already been described in connection with the system description as corresponding functions, i.e., steps and / or actions performed by various systems and / or system components.

[0277] It should be understood that the above-mentioned embodiments are merely described as examples, and the proposed technology is not limited thereto. It is understood that those skilled in the art can make various modifications, combinations, and changes to the embodiments without departing from the scope of the present invention defined by the appended claims. In particular, different partial solutions in different embodiments can be combined in other configurations if technically possible. [Explanation of symbols]

[0278] 5 X-ray detector system 10 X-ray source 16 Compton interaction 20 X-ray detector 21 Detector submodule 21 Wafer 22 pixels 25 Analog Processing Circuit 30 Image processing device 30 Image Processing System 40 Digital Processing Circuit 50 Computer 60 Detection System 100 X-ray Imaging System 200 Systems 210 Processor 220 Computer-readable medium 225 Computer Programs 230 External Memory Device 240 Output Interface

Claims

1. An X-ray detector system (5), comprising: a photon-counting X-ray detector (20) for detecting X-rays from the X-ray source and sensing the energy and position of each photon interaction of a plurality of photon interactions to obtain a data set; A coincidence detection system (60), comprising: i) organizing the data set into a number of subsets, each subset representing interactions occurring at the detector during a window of time, also called a snapshot; and ii) determining, for each snapshot, information about X-rays incident on the X-ray detector, the information including at least one of a number of incident photons in a particular area, a spatial distribution of the incident photons, and an energy distribution of the incident photons; a coincidence detection system (60) configured to perform the coincidence detection based on a combination of information for each incident photon of a plurality of incident photons, the information corresponding to a chain of one or more Compton interactions and possible photoelectric interactions, information on the time or timing of the detected photon interactions within a set of photon interactions that are likely to have been generated by the incident photon through at least one Compton scattering of the X-ray detector, information on the position of the photon interactions, information on the energy imparted in the photon interactions at the X-ray detector, and information on the position of the X-ray source relative to the X-ray detector; Including, The coincidence detection system (60) is configured to, for each incident photon of a plurality of incident photons, identify and combine interactions that belong to the same incident photon.

2. 2. The x-ray detector system of claim 1, wherein the x-ray detector system is configured to operate with a broad energy band of the x-ray spectrum having a maximum energy less than 160 keV, the x-ray spectrum being emitted from the x-ray source, the x-ray source being a localized x-ray source that is within a range of less than 0.5 millisteradians from a point on the x-ray detector.

3. 3. The X-ray detector system of claim 1 or 2, wherein the coincidence detection system operates based on a photon scattering model by combining the photon scattering model with the information about the position of the X-ray source relative to the X-ray detector to determine and / or obtain the information about the X-rays.

4. 4. The X-ray detector system of claim 3, wherein the coincidence detection system combines the photon scattering model and prior information on the position of the X-ray source with prior information on probabilities of different incident X-ray energy distributions to determine and / or obtain the information on the X-rays.

5. 5. The X-ray detector system of claim 1, wherein the X-ray detector is a photon counting multi-bin X-ray detector capable of discriminating between different energies of photon interactions, and the coincidence detection system uses information about the energy of photon interactions to determine the information about the X-rays.

6. 6. The X-ray detector system of claim 1 , wherein the coincidence detection system determines and / or obtains the information about the X-rays based on measurements of time and / or timing of photon interactions.

7. 7. The X-ray detector system of claim 1, wherein the coincidence detection system determines and / or obtains the information about the X-rays incident on the detector based on identifying at least one set of photon interactions that can be generated by a single incident photon.

8. 8. The X-ray detector system of claim 7, wherein the coincidence detection system generates and / or obtains information about X-rays incident on the X-ray detector based on identifying at least two sets of photon interactions that are likely to have been generated by at least two different incident photons, wherein all photon interactions in each set are likely to have been generated by a single incident photon, and wherein the coincidence detection system identifies the at least two sets of photon interactions as likely to have been generated by at least two different incident photons based on comparing the at least two sets of photon interactions to at least one other possible set of photon interactions.

9. 9. The X-ray detector system of claim 1, wherein the coincidence detection system generates and / or obtains information about the X-rays incident on the X-ray detector based on combining information about the time of photon interaction with at least one angle defined by at least two positions of photon interaction and / or based on at least one angle defined by three positions of photon interaction and / or based on the incident radiation direction and at least one angle defined by two positions of photon interaction.

10. The X-ray detector system according to any one of claims 1 to 9, wherein the X-ray detector is a silicon detector.

11. The x-ray detector system of claim 10 , wherein the x-ray detector system discriminates between Compton and photoelectric interactions based on an energy threshold.

12. The X-ray detector system of any one of claims 1 to 11, wherein the X-ray detector system comprises a highly attenuating shield to reduce scattering within the X-ray detector.

13. The X-ray detector system according to any one of claims 1 to 12, wherein the X-ray detector system is configured to use a method for estimating a position of interaction based on an estimate of the amount of charge diffusion.

14. The X-ray detector system according to any one of claims 1 to 13, wherein the coincidence detection system operates based on a model of the X-ray detector.

15. 15. The X-ray detector system of any one of claims 1 to 14, wherein the coincidence detection system can be configured to operate based on a photon scattering model, the photon scattering model being based on at least one of the Compton scattering equation, the Klein-Nishina equation, the Beer-Lambert law, X-ray interaction cross sections for the photoelectric effect, the Compton effect, or Rayleigh scattering, and simulation of photon transport.

16. 16. The X-ray detector system of any one of claims 1 to 15, wherein the coincidence detection system can be configured to operate based on a photon scattering model, the photon scattering model including or excluding Rayleigh scattering.

17. 17. The X-ray detector system of claim 1, wherein the coincidence detection system processes photon interactions detected in the entire detector volume or in a sub-volume independent of at least one sub-volume within the detector.

18. 18. The X-ray detector system according to any one of claims 1 to 17, wherein the coincidence detection system acquires and / or determines the information about the incident X-rays based on at least one of a maximum likelihood method, a maximum a posteriori probability estimation method, a neural network, a support vector machine, or a decision tree method.

19. 19. The X-ray detector system of any one of claims 1 to 18, wherein the coincidence detection system obtains and / or determines the information regarding X-rays incident on the X-ray detector based on assigning at least one likelihood to at least one set of photon interactions, the likelihood being based on a probability of observing a photon interaction.

20. 20. The X-ray detector system of claim 1, wherein the coincidence detection system obtains and / or determines the information about X-rays incident on the X-ray detector based on optimizing a likelihood, the likelihood being based on a probability of observing a photon interaction.

21. 21. The X-ray detector system of claim 1, wherein the coincidence detection system obtains and / or determines the information about X-rays incident on the X-ray detector based on assigning at least one likelihood to at least one set of photon interactions, the likelihood being based on the probability of observing photon interactions if they all originate from a single incident photon.

22. 22. The X-ray detector system of claim 1, wherein the coincidence detection system assigns, for each of a plurality of photon interactions, the interaction to a set of photon interactions based on the at least one likelihood of observing the photon interaction from a single incident photon.

23. 23. The x-ray detector system of claim 22, wherein the coincidence detection system assigns the plurality of photon interactions into sets of photon interactions such that no interaction is assigned to more than one set.

24. 24. The X-ray detector system of claim 21, wherein the coincidence detection system assigns at least one interaction order to photon interactions in at least one of a plurality of sets based on the likelihood of the interaction order.

25. 25. The x-ray detector system of claim 24, wherein the coincidence detection system assigns an estimated position of photon incidence to at least one set of photon interactions based on a position of a first photon interaction in the set identified by the at least one interaction order.

26. 26. The X-ray detector system of any one of claims 21 to 25, wherein the X-ray detector system estimates the energy of at least one incident photon based on detected energies of photon interactions within at least one set of photon interactions likely to be attributable to a single incident photon.

27. 27. The X-ray detector system of claim 21, wherein the X-ray detector system estimates a number of photons incident on the X-ray detector or on at least one sub-volume of the X-ray detector in at least one time interval based on the at least one likelihood.

28. An X-ray detector system according to any one of claims 19 to 27, wherein the likelihood is calculated based on a prior probability distribution over a set of possible spectra incident on the X-ray detector.

29. 29. The X-ray detector system of claim 1, wherein the coincidence detection system is configured to be applied to measurement data prior to at least one of summing measured counts over a plurality of time intervals and reading out measured counts from the photon-counting X-ray detector.

30. 30. The X-ray detector system of any one of claims 1 to 29, wherein the X-ray detector system is configured to output the information relating to X-rays incident on the X-ray detector for use as input data for at least one of an image reconstruction algorithm, a reference material decomposition algorithm, a noise reduction algorithm, a deblurring algorithm, a pile-up correction algorithm, and a spectral distortion correction algorithm.

31. An X-ray imaging system comprising an X-ray detector system according to any one of the preceding claims.

32. 32. The x-ray imaging system of claim 31 , wherein the x-ray imaging system estimates the energy of the at least one incident photon based on detected energies of photon interactions within at least one set of photon interactions likely to be attributable to a single incident photon.

33. 1. A method for determining information regarding radiation incident on an x-ray detector, comprising: using a photon-counting X-ray detector to detect X-rays, the photon-counting X-ray detector operating in a broad energy band of the X-ray spectrum having a maximum energy less than 160 keV emitted from a localized X-ray source; detecting timing information of photon interactions, information about a position of the photon interactions, and information about energy deposited in the photon interactions at the photon-counting X-ray detector to obtain a data set; organizing the data set into a number of subsets, each subset representing interactions occurring at the X-ray detector during a time window also called a snapshot, and determining for each snapshot information about X-rays incident on the X-ray detector, the information including at least one of a number of incident photons in a particular area, a spatial distribution of the incident photons, and an energy distribution of the incident photons, based on a combination of information for each incident photon of a number of incident photons, the information corresponding to a chain of one or more Compton interactions and possible photoelectric interactions, a time or timing of a detected photon interaction within a set of photon interactions likely generated by the incident photon through at least one Compton scattering at the X-ray detector, information about the position of the photon interaction and the energy imparted in the photon interaction, and information about the position of the X-ray source relative to the X-ray detector. Including, The method of claim 1, wherein for each snapshot, determining information about the X-rays incident on the X-ray detector is based on, for each incident photon of the plurality of incident photons, identifying and combining photon interactions that belong to the same incident photon.

34. The step of obtaining or determining information regarding x-rays incident on the x-ray detector comprises: identifying at least one set of photon interactions based on a likelihood of the set of lattice interactions resulting from a single photon incident on the X-ray detector, wherein the detected timing information for the set of photon interactions corresponds to all photon interactions in the set resulting from a single incident photon, the likelihood being: a position of the X-ray source relative to the X-ray detector; and At least one of the following: the Compton scattering equation, the Klein-Nishina equation, the Beer-Lambert law, the X-ray interaction cross section for the photoelectric effect, the Compton effect, or the Rayleigh scattering, and a simulation of photon transport; and obtaining or determining information about radiation incident on the X-ray detector based on the set or the likelihood of photon interactions, the information relating to at least one of a number of incident photons in a particular area, a spatial distribution of incident photons, and an energy distribution of incident photons; 34. The method of claim 33, comprising:

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