Index-based data management for X-ray imaging systems.

Abstract

The X-ray imaging system has a gantry including a moving part and a stationary part. The moving part and the stationary part are communicatively coupled through a data communication system. The moving part includes an X-ray source emitting X-rays, an X-ray detector configured to generate detector data, and a processing circuit of the gantry moving part. The processing circuit of the gantry moving part is configured to determine, for each partial data set of a plurality of partial data sets of generated detector data, an index value of at least one index, the index value being convertible into a type of data management for the partial data set from among at least two different types of data management. The processing circuit of the gantry moving part is further configured to determine, for each partial data set, how the partial data set should be treated based on the determined index value of the at least one index and to selectively perform data management according to the corresponding type of data management.

Description

[Technical field]

[0001] This application claims priority to U.S. Application No. 17 / 697,390, filed March 17, 2022, the disclosure of which is incorporated by reference in its entirety herein.

[0002] The proposed technology relates to X-ray technology and X-ray imaging and corresponding data management and data processing tasks. In particular, the proposed technology relates to X-ray imaging systems (such as CT imaging systems), methods of operating such X-ray imaging systems, and corresponding computer programs and computer program products for improving data management. [Background technology]

[0003] Radiation imaging, such as computed tomography (CT) imaging systems and other general x-ray imaging systems, has been used in medical applications, such as medical diagnosis and treatment, for many years.

[0004] Typically, an X-ray imaging system (such as a CT imaging system) includes an X-ray source and an X-ray detector array, which consists of multiple detectors, each containing one or many detector elements, and can independently measure X-ray intensity. The X-ray source emits X-rays, which pass through the subject or object to be imaged and are received by the detector array. The X-ray source and detector array are typically arranged to rotate around the subject or object on a rotating member of a gantry. The emitted X-rays are attenuated as they pass through the subject or object, and the resulting transmitted X-rays are measured by the detector. Using the measured data, an image of the subject or object can be reconstructed.

[0005] With reference to FIG. 1A, it is useful to provide a brief overview of an exemplary general X-ray imaging system according to the prior art. In this exemplary embodiment, the X-ray imaging system 1 includes an X-ray source 10, an X-ray detector system 20, and an associated image processing system or device 30. In general, the X-ray detector system 20 is configured to record radiation from the X-ray source 10, which is optionally focused by an X-ray optic or collimator and passes through an object, subject, or part of the object or subject. The X-ray detector system 20 can be connected to the image processing system 30 through suitable analog readout electronics, which are at least partially integrated in the X-ray detector system 20, enabling image processing and / or image reconstruction to be performed by the image processing system 30.

[0006] By the way, a conventional CT imaging system includes an X-ray source and an X-ray detector arranged to obtain projection images of a subject or object at different view angles covering a range of at least 180 degrees. This is most commonly achieved by mounting the source and the detector on a support (e.g., a rotating member of a gantry) that can rotate around the subject or object. An image including projections recorded on different detector elements for different view angles is called a sinogram. In the following, even if the detector is two-dimensional, a collection of projections recorded on different detector elements for different view angles is called a sinogram, and the sinogram is a three-dimensional image.

[0007] FIG. 1B is a schematic diagram of an example of a prior art X-ray imaging system configuration, showing a projection line from an X-ray source through an object to an X-ray detector.

[0008] A further development of X-ray imaging is energy-resolved X-ray imaging, also known as spectral X-ray imaging, in which the transmission of X-rays is measured for several different energy levels. This can be achieved by rapidly switching the X-ray source between two different emission spectra, by using two or more X-ray sources emitting different X-ray spectra, or by using an energy-discriminating detector that measures the incident radiation at two or more energy levels. One example of such a detector is the multi-bin photon-counting detector, in which each recorded photon generates a current pulse that is compared to a set of thresholds, thereby counting the number of photons incident on each of several energy bins.

[0009] Spectral X-ray projection measurements provide projection images for each energy level, which can be weighted together to optimize the contrast-to-noise ratio (CNR) for a particular imaging task, as described in “SNR and DQE analysis of broad spectrum X-ray imaging”, Tapiovaara and Wagner, Phys. Med.Biol.30, 519.

[0010] Another technique enabled by energy-resolved X-ray imaging is reference material decomposition, which exploits the fact that all materials composed of elements with low atomic numbers (such as human tissue) have linear attenuation coefficients whose energy dependence can be approximately well represented as a linear combination of two (or more) basis functions, i.e. μ(E)=a1f1(E)+a2f2(E)

[0011] where f1 and f2 are basis functions, and a1 and a2 are the corresponding basis coefficients. More generally, f i is the basis function, a iare the corresponding basis coefficients, where i=1,...,N, and N is the total number of basis functions. If there are one or more elements with high atomic numbers in the imaged volume, and their K-edges are high enough to appear in the energy range used for imaging, then one basis function needs to be added for each such element. In the field of medical imaging, such K-edge elements can typically be iodine or gadolinium, which are substances used as contrast agents.

[0012] Reference material decomposition is described in "Energy-selective reconstructions in X-ray computerized tomography", Alvarez, Macovski, Phys Med Biol. 1976; 21(5):733-744. In reference material decomposition, the integral of each basis coefficient, expressed as follows, is estimated from each measurement data of each projection line l from the source to the detector element:

number

number

[0013] Here, λ i is the predicted count value in energy bin i, E is the energy, and S i is the response function, which depends on the spectral shape incident on the object being imaged, the quantum efficiency of the detector, and the sensitivity of energy bin i to X-rays of energy E. Although the term "energy bin" is most commonly used for photon-counting detectors, this equation can also describe other energy-resolving X-ray imaging systems (such as multi-layer detectors or kVp switching sources).

[0014] Next, under the assumption that the counts of each bin are Poisson-distributed random variables, we use the maximum likelihood method to find A i can be estimated. This is accomplished by minimizing the negative log-likelihood function (see, e.g., “K-edge imaging in X-ray computed tomography using multi-bin photon counting detectors”, Roessl and Proksa, Phys. Med.Biol. 52 (2007), 4679-4696).

number

[0015] where m i is the measured count value for energy bin i, and M b is the number of energy bins.

[0016] The resulting estimated basis coefficient line integrals for each projection line

number

[0017] CT imaging systems that have a rotating part (such as a rotating member of a gantry) typically transmit all acquired data from the rotating part through a data slip ring to a stationary computer, where the data is post-processed to reconstruct an image of the subject or object.

[0018] Advances in the field of CT imaging have made it increasingly possible to achieve faster gantry rotation speeds and higher spatial resolution detectors, with a corresponding increase in the demand for handling large amounts of data.

[0019] As the amount of data generated increases, it places a great strain on conventional CT imaging systems that are not designed to handle the increased data flow. Thus, the system is limited in its ability to process and transfer large amounts of data through slip rings fast enough, resulting in, for example, a bottleneck effect that limits the use of the CT imaging system. This is also true for similar x-ray imaging systems that require large amounts of data to be transferred from a moving part or member of a gantry to a stationary part or member of the gantry.

[0020] Therefore, there remains a need for general improvements regarding data management in X-ray imaging systems (such as CT systems). [Prior art documents] [Patent documents]

[0021] [Patent Document 1] European Patent Application Publication No. 0514968 Summary of the Invention

[0022] The objective is to mitigate, alleviate or eliminate one or more of the above identified deficiencies and shortcomings in the art singly or in any combination, or at least to solve the above problems.

[0023] It is an object of the present invention to provide an improved X-ray imaging system.

[0024] It is also an object of the present invention to provide a method of operating an X-ray imaging system.

[0025] A further object is to provide a corresponding computer program and a computer program product.

[0026] These and other objects are achieved by one or more embodiments of the present invention as defined by the claims.

[0027] According to a first aspect, there is provided an X-ray imaging system including a gantry including a movable part on a movable side and a stationary part on a stationary side, the movable part and the stationary part being communicatively coupled through a data communication system, the movable part including an X-ray source configured to emit X-rays, an X-ray detector configured to generate detector data, and processing circuitry for the gantry movable part.

[0028] The processing circuitry of the gantry movable part is configured to determine an index value of at least one index for each partial data set of a plurality of partial data sets of generated detector data, the index value being convertible to a type of data management for the partial data set from among at least two different types of data management.

[0029] A processing circuit of the gantry moving part is configured to determine for each partial data set how the partial data set should be treated depending on the determined index value of the at least one index and to selectively perform data management in accordance with a corresponding type of data management.

[0030] Thus, the proposed technique shows how to build a high-performance X-ray imaging system within practical constraints, based on a novel differential data processing strategy.

[0031] In other words, efficient data management decisions can be made using the metrics to, for example, enable efficient handling of large amounts of detector data and / or mitigate potential bottleneck effects in conventional X-ray imaging systems.

[0032] The term "moving" refers to movable members / parts / segments, i.e., members / parts / segments that can be moved or made to move relative to stationary members / parts / segments of the overall gantry.

[0033] The expression "on-moving-gantry" refers to the commonly used term "on-gantry", but is more specifically defined as relating to the moving part of the gantry. More specifically, the expression "on-moving-gantry processing circuitry" refers to processing circuitry provided or located on the moving part of the gantry.

[0034] According to a second aspect, there is provided a method of operating an X-ray imaging system, the X-ray imaging system including a gantry including a movable part on a movable side and a stationary part on a stationary side, the movable part and the stationary part being communicatively coupled through a data communication system, the movable part including an X-ray source configured to emit X-rays, an X-ray detector configured to generate detector data, and a processing circuit of a gantry moving part, the method including: the X-ray detector generating detector data; the processing circuit of the gantry moving part determining, for each partial data set of a plurality of partial data sets of the generated detector data, an index value of at least one index based on the detector data of the partial data set; the processing circuit of the gantry moving part assigning, depending on the determined index value, a type of data management for the partial data set from among at least two different types of data management; and the processing circuit of the gantry moving part selectively implementing data management for the partial data set according to the assigned type of data management.

[0035] According to a third aspect, there is provided a computer program product including a non-volatile computer readable storage medium having a computer program stored thereon, the computer program comprising instructions, when executed by a processing circuit disposed in a movable part of an X-ray imaging system, that cause the processing circuit to determine, for each partial data set of a plurality of partial data sets of detector data generated by an X-ray detector of the X-ray imaging system, an index value of at least one index based on the detector data of the partial data set, assigning a type of data management for the partial data set from among at least two different types of data management in dependence on the determined index value, and selectively performing data management of the partial data set in accordance with the assigned type of data management. [Brief description of the drawings]

[0036] The present embodiments, together with further objects and advantages, may best be understood by reference to the following detailed description taken in conjunction with the drawings, in which: [Figure 1A] FIG. 1 is a schematic diagram showing an example of an entire X-ray imaging system. [Figure 1B] FIG. 1 is a schematic diagram showing an example of an entire X-ray imaging system. [Diagram 2] FIG. 2 is a schematic diagram illustrating another example of an X-ray imaging system (such as a CT imaging system). [Diagram 3] FIG. 1 is a schematic block diagram of a CT imaging system, which is an example of an X-ray imaging system. [Figure 4] FIG. 2 is a schematic diagram illustrating another example of relevant components of an X-ray imaging system (such as a CT imaging system). [Diagram 5] 1 is a schematic diagram of a photon count value circuit and / or device according to the prior art; [Figure 6] FIG. 2 is a schematic diagram illustrating an example of a solid-state detector sub-module in accordance with an exemplary embodiment. [Figure 7]FIG. 13 is a schematic diagram illustrating an example of a solid-state detector sub-module according to another exemplary embodiment. [Figure 8A] FIG. 13 is a schematic diagram illustrating an example of a solid-state detector sub-module according to yet another exemplary embodiment. [Figure 8B] FIG. 1 is a schematic diagram illustrating an example of a set of tiled detector sub-modules, each of which is a depth-segmented detector sub-module, with an application specific integrated circuit (ASIC) or corresponding circuitry located below the detector element when viewed from the direction of incident X-rays. [Figure 9] FIG. 1 is a schematic diagram showing an example of a CT imaging system. [Figure 10] 1 illustrates a schematic diagram of a CT imaging system according to an exemplary embodiment. [Figure 11] 2 illustrates a schematic diagram of a CT imaging system according to another exemplary embodiment. [Figure 12] 2 illustrates a schematic diagram of a CT imaging system according to yet another exemplary embodiment; [Figure 13] 2 illustrates a schematic diagram of a CT imaging system according to yet another exemplary embodiment; [Figure 14] 2 illustrates a schematic diagram of a CT imaging system according to yet another exemplary embodiment; [Figure 15] 1 is a schematic flow diagram illustrating an example method of operation of a CT imaging system. [Figure 16] FIG. 1 is a schematic diagram illustrating an example of a computer implementation according to one embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0037] For a further understanding, it is helpful to follow with an introductory description of a non-limiting example overall X-ray imaging system in which data processing and transfer in accordance with the concepts of the present invention may be implemented.

[0038] 2 is a schematic diagram showing an example of an X-ray imaging system 1. The X-ray imaging system 1 (such as a CT imaging system) includes an X-ray source 10 that emits X-rays, an X-ray detector system 20 having an X-ray detector that detects the X-rays after passing through an object, an analog processing circuit 25 that processes and digitizes raw electrical signals from the X-ray detector, a digital processing circuit 40 that can perform other processing operations on the measured data (such as applying corrections, temporarily storing the measured data, filtering, etc.), and a computer 50 that can store the processed data and perform other post-processing and / or image reconstruction. According to an exemplary embodiment, all or part of the analog processing circuit 25 can be implemented in the X-ray detector system 20. The X-ray source and the X-ray detector can be coupled to a rotating member of a gantry 15 of the CT imaging system 1.

[0039] The entire X-ray detector may be considered as the X-ray detector system 20, or may be considered as the X-ray detector system 20 in combination with associated analog processing circuitry 25.

[0040] An image processing system 30 in communication with and electrically coupled to the analog processing circuit 25 may include a digital processing circuit 40 and / or a computer 50 and may be configured to perform image reconstruction based on image data from the x-ray detector. Thus, the image processing system 30 may be viewed as the computer 50, or as a combined system of the digital processing circuit 40 and the computer 50, or as the digital processing circuit 40 itself, where the digital processing circuit is further dedicated to image processing and / or image reconstruction.

[0041] One example of a commonly used X-ray imaging system is a CT imaging system, which may include an X-ray source or tube that produces a fan or cone beam of X-rays and an opposing X-ray detector array that measures the X-rays that pass through a patient or object. The X-ray source or tube and detector array are mounted on a gantry 15 that rotates around the object being imaged.

[0042] FIG. 3 shows a schematic diagram of a CT imaging system 1 as an example of an X-ray imaging system. The CT imaging system includes a computer 50 that receives commands and scanning parameters from an operator by way of an operator console 60, which may have a display 62 and a form of operator interface (e.g., keyboard, mouse, joystick, touch screen or other input device). The commands and parameters provided by the operator are used by the computer 50 to provide control signals to an X-ray controller 41, a gantry controller 42 and a table controller 43. In particular, the X-ray controller 41 provides power and timing signals to the X-ray source 10 to control the emission of X-rays to an object or patient lying on a table 12. The gantry controller 42 controls the rotational speed and position of the gantry 11, which includes the X-ray source 10 and the X-ray detector 20. By way of example, the X-ray detector 20 may be a photon counting type X-ray detector. The table controller 43 controls and determines the position of the patient table 12 and the scan range of the patient. Also included is a detector controller 44 configured to control and / or receive data from the X-ray detector 20 .

[0043] In one embodiment, computer 50 also performs image reconstruction and post-processing of image data output from x-ray detector 20. In this case, computer 50 corresponds to image processing system 30 as shown in Figures 1 and 2. An associated display 62 allows an operator to view reconstructed images and other data from computer 50.

[0044] An X-ray source 10 disposed on a gantry 11 emits X-rays. An X-ray detector 20, which may be in the form of a photon-counting X-ray detector, detects the X-rays after passing through an object or patient. The X-ray detector 20 may be formed, for example, by a number of pixels (also called sensors or detector elements) and associated processing circuitry (such as an application specific integrated circuit (ASIC)) arranged with detector modules. Part of the analog processing is implemented in the pixels, and the remaining processing is implemented, for example, in the ASIC. In one embodiment, the processing circuitry (ASIC) digitizes the analog signals from the pixels. The processing circuitry (ASIC) may also include a digital processing unit, which may perform further processing operations on the measurement data, such as making corrections, temporarily storing the corrected data, and / or filtering. During a scan to acquire X-ray projection data, the gantry and the components mounted thereon rotate about an isocenter 13.

[0045] Modern X-ray detectors usually require the conversion of incident X-rays into electrons. This conversion is typically achieved by the photoelectric effect 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 an applied electric field.

[0046] There are detectors that operate in an energy-integrating mode, which provide a signal integrated from many x-rays, with the output signal being proportional to the total energy deposited by the detected x-rays.

[0047] X-ray detectors with photon counting capability and energy resolution have become commonplace in medical X-ray applications. Photon counting detectors have the advantage that, in principle, the energy of each X-ray can be measured, providing additional information about the composition of the object. This information can be used to improve image quality and / or reduce radiation dose.

[0048] Typically, photon counting X-ray detectors determine the energy of a photon by comparing the height of an electrical pulse generated by the interaction of the photon with the detector material to a set of comparator voltages. These comparator voltages are also called energy thresholds. Typically, the analog voltage of the comparator is set by a digital-to-analog converter (DAC). The DAC converts the digital setting sent by the controller into an analog voltage that can be compared to the height of the photon pulse.

[0049] Photon counting detectors count the number of photons that interact within the detector during a measurement time. A new photon is typically identified by the fact that the height of the electrical pulse exceeds the comparator voltage of at least one comparator. Once a photon is identified, the event is stored by incrementing a digital counter associated with that channel.

[0050] When several different thresholds are used, so-called energy-discriminating photon-counting detectors are obtained, in which the detected photons can be separated into energy bins corresponding to various thresholds. This kind of photon-counting detector is sometimes called a multi-bin detector. In general, the energy information allows the creation of a new kind of image, where new information is available and where the image artifacts inherent in the prior art can be eliminated. In other words, in an energy-discriminating photon-counting detector, the pulse height is varied by several comparator-programmable thresholds (T1-T N) and classified according to the pulse height, which is proportional to the energy. In other words, a photon counting detector that includes two or more comparators is referred to herein as a multi-bin photon counting detector. For a multi-bin photon counting detector, the photon count values ​​are stored in a set of counters, typically one counter for each energy threshold. For example, a counter can be assigned to correspond to the highest energy threshold that the photon pulse crossed. In another example, a counter records the number of times that the photon pulse crosses each energy threshold.

[0051] As an example, edge-on is a non-limiting specific design of a photon counting detector in which the x-ray sensors (such as x-ray detecting elements or pixels) are oriented to be edge-on to the incident x-rays.

[0052] For example, such a photon counting detector may have pixels in at least two directions, where one of the at least two directions of the edge-on photon counting detector has a component in the direction of the x-rays. Such an edge-on photon counting detector may be referred to as a depth-segment photon counting detector, having pixels in two or more depth segments in the direction of the incident x-rays.

[0053] Alternatively, the pixels may be arranged in an array (an array that is not segmented in depth) in a direction substantially perpendicular to the direction of the incident x-rays, and each pixel of the plurality of pixels may be oriented edge-on with respect to the incident x-rays. In other words, the photon-counting detector may be arranged edge-on with respect to the incident x-rays, but not segmented in depth.

[0054] The absorption efficiency can be increased by placing the edge-on photon counting detector on edge, in which case the absorption depth can be chosen to be any length, and the edge-on photon counting detector can be fully depleted without requiring very high voltages.

[0055] The conventional mechanism for detecting X-ray photons directly by semiconductor detectors basically works as follows: the energy of the X-ray interaction with the detector material is converted into electron-hole pairs inside the semiconductor detector, where the number of electron-hole pairs is generally proportional to the photon energy. The electrons and holes drift towards the electrodes and backside of the detector (or vice versa). During this drift, the electrons and holes induce a current in the electrodes, and this current can be measured.

[0056] As shown in FIG. 4, signals are sent 26 from the detector elements 22 of the X-ray detector to the input of a parallel processing circuit (e.g., ASIC) 25. It should be understood that the term application specific integrated circuit (ASIC) should be broadly interpreted as a general circuit used and configured for a specific application. The ASIC processes the charge generated from each X-ray and converts it into digital data. The digital data can be used to obtain measurement data (such as photon count and / or estimated energy). The ASIC is configured to be connected to the digital data processing circuit so that the digital data is sent to other digital data processing units 40 and / or one or more memory circuits or components 45, and finally the data becomes the input of the image processing unit 30 / 50, where a reconstructed image is generated.

[0057] The number of electrons and holes generated from an X-ray event is proportional to the energy of the X-ray photon, and therefore the total charge of one induced current pulse is proportional to said energy. After a filtering process is performed in the ASIC, the pulse amplitude is proportional to the total charge of the current pulse and thus to the X-ray energy. The pulse amplitude can be measured by comparing its amplitude value with one or more thresholds (THR) of one or more comparators (COMP), and a counter is introduced to record the number of times the pulse is greater than the threshold. In this way, it is possible to count and / or record the number of X-ray photons detected within a certain time and having an energy greater than the energy corresponding to the respective threshold (THR).

[0058] The ASIC typically samples the analog photon pulse once per clock cycle and records the output of the comparators. The comparators (thresholds) output a 1 or 0 depending on whether the analog signal is above or below the comparator voltage. The information available at each sample is, for example, a 1 or 0 for each comparator, representing whether the comparator was triggered (the photon pulse was greater than the threshold) or not.

[0059] Photon counting detectors typically have a photon counting logic that determines if a new photon has been recorded and records the photon in a counter. In the case of a multi-bin photon counting detector, there are typically multiple counters, e.g., one counter for each comparator, and the photon count value is recorded in the counter according to an estimate of the photon energy. This logic can be implemented in several different ways. The two most common categories of photon counting logic are the so-called non-paralyzed counting mode and paralyzed counting mode. Other photon counting logic includes, for example, maximum detection, which counts detected maximums in a voltage pulse and possibly also records the height of that pulse.

[0060] Photon counting detectors have many advantages, including but not limited to higher spatial resolution, lower sensitivity to electronic noise, better energy resolution, and material separation (spectral imaging). However, energy integrating detectors have the advantage of higher count rate tolerance. Count rate tolerance is based on the fact / realization that the output signal will always increase (within reasonable limits) with one additional photon, regardless of the amount of photons currently registered by the detector, since the total energy of the photons is measured. This advantage is one of the main reasons why energy integrating detectors are the standard in medical CT today.

[0061] FIG. 5 shows a schematic diagram illustrating a photon counting circuit and / or device according to the prior art.

[0062] When photons interact in the semiconductor material, a cloud of electron-hole pairs is generated. When an electric field is applied to the detector material, the charge carriers are collected by electrodes formed in the detector material. Signals are sent from the detector elements to the input of a parallel processing circuit (such as an ASIC). It should be understood that the term application specific integrated circuit (ASIC) should be interpreted broadly as a general circuit used and configured for a specific application. The ASIC processes the charge generated from each X-ray and converts it into digital data. The digital data can be used to obtain measurement data (such as photon counts and / or estimated energy). In one example, the ASIC can process the charge such that a voltage pulse is generated having a maximum height proportional to the amount of energy deposited by the photon in the detector material.

[0063] The ASIC may include a set of comparators 302, each of which compares the magnitude of the voltage pulse to a reference voltage. The comparator output is typically zero or one (0 / 1) depending on which of the two voltages compared is greater. Here, if the voltage pulse is higher than the reference voltage, the comparator output is one, and if the reference voltage is higher than the voltage pulse, the comparator output is zero. A digital-to-analog converter (DAC) 301 may be used to convert a digital setting, which may be provided by a user or a control program, into a reference voltage that may be used by the comparators 302. If the height of the voltage pulse exceeds the reference voltage of a particular comparator, that comparator will be said to be triggered. Each comparator is typically associated with a digital counter 303, which is incremented based on the comparator output according to a photon counting logic.

[0064] As mentioned before, for each projection line, the resulting estimated basis coefficient line integral values

number

[0065] It will be understood that the mechanisms and configurations described herein can be implemented, combined, and rearranged in various ways.

[0066] For example, the embodiments may be implemented in hardware, or at least partially implemented in software executable by suitable processing circuitry, or a combination of both.

[0067] The processes, functions, procedures, and / or blocks described herein can be implemented in hardware using conventional techniques, such as discrete or integrated circuit techniques, including both general-purpose electronic circuitry and application-specific circuitry.

[0068] Alternatively, or as a complement, at least some of the steps, functions, procedures and / or blocks described herein may be implemented in software, such as a computer program, which may be executed by suitable processing circuitry (such as one or more processors or processing units).

[0069] Non-limiting examples of specific detector modules are described below. More specifically, these examples represent edge-on oriented detector modules and depth-segmented detector modules. Other types of detectors and detector modules are possible.

[0070] 6 is a schematic diagram of an example of a semiconductor detector submodule according to an exemplary embodiment. This is an example of a semiconductor detector submodule in which a semiconductor sensor 21 is divided into multiple detector elements or pixels 22, each of which typically consists primarily of a diode with a charge collection electrode. X-rays enter from the edge of the semiconductor sensor.

[0071] 7 is a schematic diagram of an example of a semiconductor detector sub-module according to another exemplary embodiment, in which the semiconductor sensor 21 is also divided in depth direction into a number of so-called depth segments or detector elements 22, with X-rays incident from the edge.

[0072] Typically, a detector element is an individual X-ray sensitive sub-element of the detector. In general, photon interactions occur within the detector element and the charge thus generated is collected by a corresponding electrode of the detector element.

[0073] Each detector element typically measures the incident x-ray flux as a series of frames, where a frame is a specified time interval of measurement data called the frame time.

[0074] Depending on the detector topology, a detector element may correspond to a pixel, especially if the detector is a flat panel detector. 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 depth segment is associated with its own separate charge collection electrode.

[0075] The detector strips of a depth-segmented detector typically correspond to the pixels of a regular flat panel detector and are therefore sometimes called pixel strips, however, a depth-segmented detector can also be considered as a three-dimensional pixel array, where each pixel (sometimes called a voxel) corresponds to a separate depth segment / detector element.

[0076] The semiconductor sensor can be implemented as a so-called multi-chip module (MCM), in the sense that it is used as a base substrate for electrical wiring and further for several ASICs, which are preferably attached by the so-called flip-chip technique. The wiring includes connections for the signals from each pixel or detector element to the inputs of the ASIC and connections from the ASIC to an external memory and / or a digital data processing unit. The power to the ASIC can be supplied through similar wiring, taking into account the increased cross-sectional area required for the high currents of these connections, but the power can also be supplied through separate connections. The ASICS can be placed next to the active sensor, which means that the ASIC can be protected from incident X-rays if an absorbing cover is placed on top, and also from scattered X-rays by placing an absorber in this direction for scattered X-rays from the side.

[0077] FIG. 8A is a schematic diagram showing a semiconductor detector submodule implemented as an MCM similar to the embodiment of US Pat. No. 8,183,535. In this example, it is illustrated how a semiconductor sensor 21 can have the function of the substrate of the MCM. Signals are sent by signal paths 23 from the detector elements or pixels 22 to the inputs of a parallel processing circuit 24 (e.g., ASIC) located next to the active sensor area. It should be understood that the term Application Specific Integrated Circuit (ASIC) should be interpreted broadly as a general integrated circuit used and configured for a specific application. The ASIC processes the charge generated from each X-ray and converts it into digital data that can be used to detect photons and / or estimate the energy of the photons. The ASIC can have its own digital processing circuitry and memory for small tasks. The ASIC can then be configured to connect to digital processing and / or memory circuits or components located outside the MCM, and finally the data is used as input to reconstruct the image.

[0078] However, depth segmentation poses two notable challenges for silicon-based photon-counting detectors. First, a large number of ASIC channels must be employed to process the data provided by the associated detector segments. The small pixel size and depth segmentation increase the number of channels, and the data size is further increased due to multi-energy bins. Second, since a given X-ray input count value is split into small pixels, segments, and energy bins, each of which has a very low signal, detector calibration / correction requires orders of magnitude larger calibration data to minimize statistical uncertainty.

[0079] Naturally, as data sizes increase by several orders of magnitude, both data processing and preprocessing become slower, in addition to requiring larger computational resources, hard disks, memory, central processing units (CPUs) / graphics processing units (GPUs). For example, as data sizes increase from 10 megabytes to 10 gigabytes, data processing times for reading and writing increase by 1000 times.

[0080] A problem with counting type X-ray photon detectors is the so-called pile-up problem. At high flux rates of X-ray photons there is a problem distinguishing between two subsequent charge pulses. As mentioned before, the pulse length after filtering depends on the shaping time. If this pulse length is longer than the time between two charge pulses induced by an X-ray photon, the two pulses may merge and the two photons cannot be distinguished and are 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.

[0081] To generate the pile-up calibration vector, the pile-up calibration data needs to be pre-processed for spit correction. For material decomposition vector generation, the material decomposition data needs pre-processing for both spit correction and pile-up correction. For patient scan data, the data needs to be pre-processed for spit, pile-up, and material decomposition before image reconstruction takes place. These are simplified examples to explain "pre-processing," and the actual pre-processing steps may include several other calibration steps (such as fiducial normalization and air calibration) as needed. The term "processing" can refer only to the final step in each calibration vector generation or patient scan, but is sometimes used interchangeably.

[0082] FIG. 8B is a schematic diagram showing an example of a set of arrayed detector sub-modules, each of which is a depth-segmented detector sub-module, with the ASIC or corresponding circuitry 24 positioned below the detector elements 22 as viewed from the direction of incident x-rays, and capable of routing paths from the detector elements 22 to the ASIC 23 in the spaces between the detector elements.

[0083] The present invention relates to a novel system architecture and corresponding procedures for improving data management in X-ray imaging systems (such as CT systems).

[0084] According to a first aspect, there is provided an X-ray imaging system including a gantry including a movable part on a movable side and a stationary part on a stationary side, the movable part and the stationary part being communicatively coupled through a data communication system, the movable part including an X-ray source configured to emit X-rays, an X-ray detector configured to generate detector data, and processing circuitry for the gantry movable part.

[0085] The processing circuitry of the gantry moving part is configured to determine an index value of at least one index for each partial data set of a plurality of partial data sets of the generated detector data, the index value being convertible to a type of data management for the partial data set from among at least two different types of data management.

[0086] The processing circuitry of the gantry moving part is further configured to determine, for each partial data set, how said partial data set should be treated depending on the determined index value of said at least one index, and to selectively perform data management in accordance with a corresponding type of data management.

[0087] The proposed technique allows efficient data management decisions using efficient metrics, e.g., to efficiently handle large amounts of detector data and / or to mitigate possible bottleneck effects in conventional X-ray imaging systems.

[0088] In this way, the proposed technique makes it possible to more optimally exploit the superior imaging capabilities of modern X-ray detectors, such as high resolution, photon count values, interferometers (e.g. phase contrast imaging and dark field imaging), energy discriminating detectors and multi-segment detectors.

[0089] Thus, the proposed technique effectively addresses the trade-off between data fidelity and practical constraints related to computational resources, power, cooling, space, and / or data transfer bandwidth.

[0090] The term "moving" refers to movable members / parts / segments, i.e. members / parts / segments that can move or be made to move relative to stationary members / parts / segments of the overall gantry.

[0091] The expression "on-moving-gantry" refers to the commonly used term "on-gantry", but more specifically to the movement of the gantry. More specifically, the expression "processing circuitry on the moving gantry" refers to processing circuitry provided on or located on the moving part of the gantry.

[0092] By way of example, the X-ray imaging system may be a computed tomography (CT) system and the moving and stationary parts may be the rotating and stationary parts of a gantry of the CT system.

[0093] For example, the rotating part may be a rotating member / portion / segment of a CT gantry that is configured to rotate, for example, around a subject / object to be imaged. The stationary part may be defined as a stationary member / portion / segment of a CT gantry that is stationary on the stationary side, and the rotating part and stationary part may be communicatively connected through a data communication system (e.g., one or more slip rings). In the specific example of a CT system, the phrase "processing circuitry of the moving part of the gantry" refers to processing circuitry provided or located on the rotating part of the gantry.

[0094] The expression "off-moving-gantry data processing" means that the data processing is "off" the moving parts of the gantry and is performed on the stationary side by processing circuitry located or provided in the stationary part of the gantry as a whole.

[0095] 9 is a schematic diagram showing an example overview of a CT imaging system. In this schematic embodiment, CT system 100 generally includes a gantry 111 having a rotating portion 110 and a stationary portion 120. The CT system further includes a standard patient table 112 that can be inserted into an opening in gantry 111 during patient and / or calibration scans.

[0096] However, it should be understood that the moving and stationary parts of the gantry need not be part of the CT system and may, for example, be arranged and / or configured in other ways (e.g., for linear and / or translational relative movement without rotation). As an example, the X-ray source and detector combination may be moved in a linear and / or translational manner relative to the stationary parts of the entire gantry. For example, the X-ray source and detector may move together along the table axis (commonly called the z-axis) as a united assembly unit. Alternatively, the patient table moves while the X-ray source and detector combination is stationary. It is the relative movement that is important. This also includes the geometric system configuration in which the patient stands (e.g., so-called telephone booth type scanners).

[0097] In a particular example, the processing circuitry of the moving gantry part is configured to identify at least two different partial data sets of the generated detector data to which different types of data management are applied.

[0098] In this way, robust and efficient multi-modal partial data set management is achieved, allowing for advanced data management decisions to be made using metrics.

[0099] For example, the at least two different types of data management may include at least one of the following i), ii) and iii): i) performing data processing at the moving part of the gantry on the generated partial data set of detector data before transmitting the partial data set from the moving part to the stationary part, ii) not performing data processing at the moving part of the gantry on the generated partial data set of detector data before transmitting the partial data set from the moving part to the stationary part, and iii) not transmitting the generated partial data set of detector data.

[0100] In certain examples, the processing circuitry of the gantry moving part may be further configured to perform data processing at the gantry moving part having different levels of computational complexity for different part data sets.

[0101] As an example, the processing circuitry of the gantry moving part can be configured to determine based on the determined index value of the at least one index for the first partial data set that data processing at the moving part of the gantry should be applied to the first partial data set before it is transmitted from the moving part to the stationary part, and the processing circuitry of the gantry moving part can be configured to determine based on the determined index value of the at least one index for the second partial data set that the second partial data set should be transmitted from the moving part to the stationary part without data processing at the moving part of the gantry or that data processing at the moving part of the gantry, which has a lower computational complexity than data processing for the first partial data set, should be applied to the second partial data set before it is transmitted from the moving part to the stationary part.

[0102] For example, the processing circuitry of the gantry moving part may be configured to perform data processing on the gantry moving part on the first partial data set so as to reduce the data, generate a data-reduced first partial data set, and transmit it from the moving part to the stationary part.

[0103] Optionally, the X-ray imaging system further includes an additional processing circuit connected to the stationary part, the additional processing circuit configured to perform a material decomposition procedure adapted to the data reduced first partial data set.

[0104] As another example, the processing circuitry of the gantry moving part may be configured to determine not to transmit a particular partial data set from the moving part to the stationary part based on a determined index value of at least one index for the particular partial data set.

[0105] In certain exemplary embodiments, the processing circuitry of the gantry moving part can be configured to determine to which of at least two non-overlapping time intervals a determined index value of at least one index belongs, each time interval being associated with a respective data management of at least two different types of data management, and the determined index value can be associated with a particular type of data management for the partial data set of interest.

[0106] It is clear that the measured detector data may be characterized or represented by one or more indices. The indices may be designed to represent one or more properties of the measured data. Non-limiting examples of indices include the signal-to-noise ratio of the measured data, the contrast-to-noise ratio of the measured data, the autocorrelation of the measured data, the cross-correlation of the measured data, the average value of the measured data, the estimated thickness of the part traveled by the x-rays that contributed to the measured data, the degree of pulse pile-up present in the measured data, the statistical distribution of the measured data, and the results of hypothesis tests on the data. As an example, the indices may be based on the frequency content of the projected measured data, both in time and space. For example, edge features may be detected and differentially processed to correct for detector crosstalk. The indices may be applied directly to the data or to linear or non-linear transformations of the data. The indices may take into account imaging parameters (kVp, tube current, etc.). The indices may take into account prior information about the object being imaged. For example, the indices may take into account models of the source (eg, spectrum, focal spot shape, focal spot size) and / or the detector (eg, energy response, pile-up response, crosstalk).

[0107] In a particular embodiment, the at least one index may include a pile-up index representative of an amount of pile-up of pulses in at least a portion of the partial data set for which the generated detector data is directed, and the processing circuitry of the gantry moving part may be configured to determine whether data processing for pile-up correction at the gantry moving part should be applied to the partial data set depending on the determined index value of the pile-up index, and to selectively perform data processing for pile-up correction at the gantry moving part on the partial data set to generate a corrected data set.

[0108] Optionally, additional data processing of the corrected data set for pile-up correction away from the moving gantry parts can be performed by processing circuitry in the stationary part.

[0109] For example, the processing circuitry of the gantry moving part may be configured to perform data processing for pile-up correction at the gantry moving part when the determined pile-up index value of the pile-up index indicates an amount of pile-up greater than zero but less than a first threshold value.

[0110] In an optional embodiment, the processing circuitry of the gantry moving part can be configured to determine that if the determined index value of the pile-up index indicates a pile-up amount greater than a second threshold level, the partial data set should be transmitted from the moving part to the stationary part without performing data processing for pile-up correction at the gantry moving part.

[0111] For example, data processing for pile-up correction away from the moving part of the gantry of the partial data sets can be performed by processing circuitry in the stationary part.

[0112] In certain embodiments, the processing circuitry of the on-gantry moving part is configured to determine the pile-up indicator based on a comparison between the estimated true photon count value and the measured photon count value. For example, the on-gantry processing circuitry can be configured to determine the pile-up indicator based on a ratio or difference between the estimated (true) photon count value and the measured photon count value. Such a ratio or difference can be determined, for example, for each detector pixel or for groups of detector pixels, for at least a subset of pixel subelements, and / or for at least a subset of energy bins. As an example, the estimate of the true photon count value can be determined as a weighted combination of the count values ​​under certain bias assumptions. Typically, a photon count value that should appear in a certain energy bin appears in a higher energy bin than that energy bin (biased towards higher energy bins). The dominant pile-up effect is usually the sum of the energies of multiple photons that apparently occur simultaneously. Thus, the measured energy is biased towards higher and the photon count value is biased towards lower values ​​relative to the truth (i.e., the true physical interactions that actually occur in the detector).

[0113] In another exemplary embodiment, the at least one index includes an X-ray propagation index or an X-ray attenuation index.

[0114] For example, the processing circuitry of the gantry moving part may be configured to identify a partial data set where the detector data corresponds to X-rays traveling only through air from the X-ray source to the X-ray detector based on the X-ray propagation indicator or the X-ray attenuation indicator, and the processing circuitry of the gantry moving part may then be configured to determine that the identified partial data set should not be transmitted from the moving part to the stationary part.

[0115] Typically, each partial data set corresponds to a batch of generated detector data relating to an X-ray measurement or a group of X-ray measurements.

[0116] Optionally, the data communication system is configured to transmit, for at least one partial data set, a representation of the corresponding determined index value, or an identifier representative of the type of data management applied, from the mobile part to the stationary part in association with the partial data set.

[0117] For example, the identifier may indicate whether gantry moving part data processing has been performed on the partial data set.

[0118] As an example, the data communication system may include a first data communication unit provided in the moving part of the moving side and a second data communication unit provided in the stationary part of the stationary side, which may be, for example, one or more slip rings for a CT system.

[0119] Further, the movable part may include a data storage unit of the gantry movable part associated with the processing circuitry of the gantry movable part for storing the detector data in processed and / or unprocessed form, as exemplified below.

[0120] As an example, the X-ray detector is a photon counting detector.

[0121] As explained above, the X-ray imaging system can be a computed tomography (CT) system, and the moving and stationary parts can be, for example, the rotating and stationary parts of a gantry of a CT system, as shown diagrammatically in FIG. 9. However, the proposed technology is not limited thereto. Alternatively, or complementary, the moving and stationary parts of the gantry can be arranged and / or configured in other ways, for example to allow linear and / or translational relative movement. For example, the X-ray source and detector can move together as a whole assembly unit along a table axis, commonly called the z-axis, without rotation. Alternatively, the patient table moves. In other words, an array of one or more source and detector combinations can be scanned along a horizontally arranged table top or vertically along a standing object.

[0122] For better understanding, the proposed technique will now be described in more detail with reference to Figures 10 to 14, which show non-limiting examples of data processing and data transfer according to the invention. In these particular examples, a CT architecture is illustrated, but as mentioned above, the invention is not limited to the CT architecture.

[0123] 10 is a schematic diagram of a CT imaging system according to an exemplary embodiment. In general, the CT system 100 includes a gantry having a moving / rotating part 110 on a moving / rotating side and a stationary part 120 on a stationary side. The moving / rotating part 110 includes an x-ray source 112 and an x-ray detector 114, as well as processing circuitry 116, referred to as the gantry moving part processing circuitry.

[0124] The moving / rotating part 110 and the stationary part 120 are communicatively coupled through a data communication system 130. In this example, the data communication system 130 includes a first data communication unit 130-1 provided in the moving / rotating part on the moving / rotating side, and a second data communication unit 130-2 provided in the stationary part on the stationary side.

[0125] The processing circuit 116 of the gantry moving part is configured to determine an index value of at least one index for each partial data set of a plurality of partial data sets of the generated detector data, and the index value is convertible from among at least two different types of data management to a type of data management for the partial data set.

[0126] The processing circuitry 116 of the gantry moving part is further configured to determine, for each partial data set, how the partial data set should be processed depending on the determined index value of the at least one index and to selectively perform data management according to a corresponding type of data management.

[0127] As an example, the gantry moving part processing circuitry 116 may be configured to identify at least two different partial data sets of the generated detector data to which different types of data management are applied.

[0128] For example, different types of data management may include i) performing data processing (such as data reduction) at the moving part of the gantry on the partial data set of generated detector data before transmitting the partial data set from the moving part to the stationary part, ii) not performing data processing at the moving part of the gantry on the partial data set of generated detector data before transmitting the partial data set from the moving part to the stationary part, and / or iii) not transmitting the partial data set of generated detector data.

[0129] Optionally, the stationary portion 120 includes additional processing circuitry 122 for performing various processing operations (such as filtering operations, calibration, pile-up correction, material decomposition and / or image reconstruction).

[0130] Fig. 11 shows a schematic diagram of a CT imaging system according to another exemplary embodiment. Fig. 11 is similar to Fig. 10, but illustrates an index determination module and a data management determination module in the processing circuitry 116 of the gantry moving part. For example, these modules can be implemented as software modules for performing the functions and / or operations described herein. Alternatively, the modules can be implemented as specialized hardware circuits (e.g., FPGAs or ASICs) that can be defined as part of the overall processing circuitry 116 of the gantry moving part.

[0131] Fig. 12 shows a schematic diagram of a CT imaging system according to yet another exemplary embodiment. Fig. 12 is similar to Fig. 10, except for an additional data storage unit 118 provided in the moving / rotating part 110. The data storage unit 118 is connectable to the processing circuitry 116 of the moving gantry part for use during data processing operations.

[0132] For example, data storage unit 118 may include dedicated mass memory (e.g., non-volatile memory express (NVMe)). Data storage unit 118 may additionally or alternatively include temporary memory (e.g., ASIC, field programmable gate array (FPGA) registers or memory, etc.) required during continuous data processing. Data storage unit 118 may additionally or alternatively include RAM (random access memory). It should also be understood that a set of transient registers, typically defined as part of processing circuitry 116, may be present when configured as a conventional processor.

[0133] Fig. 13 shows a schematic diagram of a CT imaging system according to yet another exemplary embodiment. Fig. 13 is similar to Fig. 12, but with the addition of an optional data path directly from the X-ray detector 114 to the data storage unit 118, and an optional data path from the data storage unit 118 to the data communication system 130. This means that the detector data from the X-ray detector 114 can be transferred directly to the data storage unit 118, if desired. The processing circuitry 116 and the data storage unit 118 can then communicate for the exchange of data to be processed and / or analyzed. This also means that the processed and / or unprocessed data stored in the data storage unit 118 can be transferred directly to the data communication unit 130-1 of the moving / rotating part 110 and then to the data communication unit 130-2 of the stationary part 120.

[0134] 14 is a schematic diagram of a CT imaging system according to yet another exemplary embodiment. In this particular example, the data storage unit 118 is directly connected to the X-ray detector 114 for receiving and at least temporarily storing the detector data. The data storage unit 118 and the processing circuitry 116 are interconnected to allow exchange of detector data for processing and / or analysis by the processing circuitry 116, and / or exchange of processed data for returning the processed data from the processing circuitry 116 to the data storage unit 118. The data in processed and / or unprocessed form can then be selectively transferred from the data storage unit 118 to the data communication unit 130-1 of the moving / rotating part 110 and to the data communication unit 130-2 of the stationary part 120, for example, under the control of the processing circuitry 116.

[0135] The proposed technique will now be described with reference to a non-limiting example relating to pulse pile-up processing. As will be apparent, the proposed technique is not limited to this particular application but is generally applicable to differential data management using indices.

[0136] As mentioned above, in photon-counting X-ray detectors, pulse pile-up occurs when more than one photon hits the detector within a time set by the pulse width (so-called dead time) of the electronics. Pile-up can reduce the count value because two or more photons collapse into only one pulse. Pile-up can also distort the spectrum because a pulse within the dead time will have a larger pulse height and be interpreted as a single photon with higher energy, and the pulse will become a wide pulse with a tail that can be detected as a second, lower-energy pulse that can pile up with the following pulse.

[0137] The effects of pile-up on radiological images include: 1) reduced contrast-to-noise ratio, because at high count rates, the greater reduction in count values ​​reduces contrast between regions with different count rates (e.g., radiological targets); 2) bias in material decomposition images, because the detector's spectral response changes with count rate, and if the x-ray tube current is different from that at calibration, the detector's spectral response will differ from the calibrated spectral response; and reduced efficiency of standard x-ray imaging correction processes (e.g., scatter correction) and data reduction operations (e.g., pixel or depth segment binning), because these processes and operations typically assume a linear detector response.

[0138] In modalities such as photon-counting computed tomography (PCCT), pulse pile-up leads to loss of linearity in detector response as a function of incident radiation flux. However, high order pile-up can be avoided in most pixels of the detector, for example, by bow-tie filters and by careful protocol design and patient positioning. However, the large degree of pile-up of x-rays passing through thin materials can make it difficult to correct for the pile-up of the corresponding detector pixels. Also, in off-center anatomical structures, bow-tie filters do not work well in minimizing pile-up.

[0139] The main advantage offered by photon counting imaging techniques is the high resolution due to the use of small pixels. Small pixels also help to reduce pile-ups occurring per pixel. Dividing each pixel into multiple depth segments can further reduce pile-ups. However, when the number of pixels becomes huge and / or there are multiple depth segments per pixel and / or there are multiple energy bins per pixel, the amount of data to be processed challenges the limits of modern computing and data transmission technologies. For example, when the data processing of incident events is performed in the moving / rotating parts of the gantry, there are limited physical space, power, cooling, and available computational resources. When the processing is performed outside the stationary parts of the gantry, the data transmission bandwidth of the gantry slip ring becomes a limiting factor.

[0140] In certain exemplary embodiments, the raw data can be analyzed at the moving / rotating part of the gantry to determine one or more indices that estimate the amount of pile-up for each measurement (or group of measurements). The indices can also be estimated from past images, preliminary images, pre-scan data, or a patient model.

[0141] Depending on the pile-up estimate, different processing can be applied, e.g. no correction or a computationally less expensive correction, to data from detector elements with no pile-up or from detector elements with less pile-up, respectively. Ideally, this correction is performed at the gantry rotation and the output data is dimensionally reduced by a pile-up correction process. Dimensionality reduction, also called data reduction, can be performed by methods such as detector segment sums, weighted detector segment sums, principal component analysis, and representation in a reduced-dimensional mathematical basis.

[0142] More sophisticated (and perhaps computationally expensive) pile-up correction can be provided for pixels that score high on the pile-up index and are therefore difficult to correct. Because step (a) increases the transmission bandwidth available for these measurements, these measurements can be transmitted without being compressed, summed, or expressed in terms of another mathematical base. And, sophisticated pile-up correction algorithms can be performed away from the rotating gantry, where more computational resources, space, power, and cooling are available.

[0143] Measurements corresponding to X-rays traveling only through air can be identified using appropriate indices estimated at the rotating part of the gantry and completely excluded from any transmission.

[0144] The identifier may contain one or more bits of information and may identify the transmitted data indicating whether the measurement should be treated as case (a) or case (b). Similarly, more bits may be used to identify if there are more than two types to be treated. For example, two bits of information may code {high pileup, medium pileup, low pileup, no pileup}.

[0145] In photon counting systems, pile-up correction is often followed by a material discrimination (MD) operation that represents the data in terms of two or more material basis functions. Data from case (a) can be applied to an MD algorithm configured to operate on lower dimensional data than an MD algorithm configured to process data from case (b). This can achieve significant savings in computational cost while maintaining the fidelity of MD for the challenging discrimination problem posed by data from case (b). By "distributing" we mean any of the algorithm design, optimization, covariance matrix estimation, calibration, and / or spatial aggregation of detector data.

[0146] For more information on pile-up and pile-up correction, see: Pile-up response of photon-counting detectors can be classified into two main categories, paralyzing operation and non-paralyzing operation, as described, for example, in "Radiation Detection and Measurement" by Glenn F. Knoll, 3rd Edition, published by John Wiley & Sons Inc, pages 632-642.

[0147] Since paralyzed detectors have a dead time that is reset for each new event, if the incidence rate is high enough, the dead time becomes infinitely long. As a result, the detected count rate reaches a maximum at a certain incidence rate, after which the detected count rate starts to decrease. Therefore, the detected count rate as a function of incidence rate is not an injective and invertible function, and it is difficult to compensate for the lost counts.

[0148] Nonparallel detectors, on the other hand, have a nonextending (or semiextending) dead time, so that the detected count rate increases monotonically (generally reversibly) as a function of the incident count rate. The detected count rate plateaus at a maximum count rate that is determined by the inverse of the dead time.

[0149] For non-paralyzable photon-counting detectors without energy discrimination, well-established models are available that describe the loss of counts due to pile-up with high accuracy. See, for example, "Radiation Detection and Measurement" by Glenn F. Knoll (3rd ed., John Wiley & Sons Inc, pp. 632-642) and "Count statistics of non-paralyzable photon-counting detectors with nonzero pulse length" by Gronberg F, Danielsson M, Sjolin M. (Med Phys. 2018;45(8):3800-3811). These models can be inverted to correct for the lost counts.

[0150] In photon-counting detectors capable of energy discrimination, it is desirable to also compensate for spectral distortions, i.e., shifts in count values ​​between energy bins. In that case, the correction problem becomes even more complicated. This is especially true because the bin response function is generally not a projection function of the true bin count rate, even in non-parallel detectors. In low energy bins, count values ​​are lost to high energy bins at a faster rate than the bin count rate increases, reaching a maximum count rate and then dropping off at a higher rate. This behavior makes it difficult to determine the inverse, since there is no one-to-one correspondence between the detected count rate and the true count rate.

[0151] One approach to so-called spectral pile-up correction is to analytically model the pile-up process. See for example “First principles pulse pile-up balance equation and fast deterministic solution”, Sabbatucci L, Fernandez JE., Radiat Phys Chem.2017;137:12-17 and “Evaluation of models of spectral distortion in photon-counting detectors”, Cammin J, Kappler S, Weidinger T, Taguchi K. J Med Imaging.2016;3(2). To correct the pile-up effect, the model can be inverted analytically or iteratively. The drawback of this approach is that it requires detailed system knowledge (e.g. incident spectrum, pulse shape), which is not always available.

[0152] Another approach is to use data-driven methods based on neural networks or machine learning. See, for example, “Neural-networks-based Photon-Counting Data Correction: Pulse Pileup Effect”, Feng R, Rundle D, Wang G, In: IEEE.; 2018:1-14 and “Near optimal neural network estimator for spectral X-ray photon counting data with pileup”, Alvarez, ArXiv.2017:1-11. This approach does not require advanced system knowledge.

[0153] A more advanced and efficient procedure of pile-up correction is proposed in US Patent No. 11,166,683, which discloses a method and corresponding system for pile-up correction in a non-parallel energy discriminating photon counting X-ray detector operating based on several energy bins. The method includes adding a correction term to the detection signal of the energy bin for each of several energy bins, the correction term being a product of two separable parameter functions, each parameter function of the two separable parameter functions including at least one parameter, a first parameter function depending on a weighted sum of the detection signals in the entire energy bin, and a second parameter function depending on the detection signals in one or more energy bins.

[0154] FIG. 15 is a schematic flow diagram illustrating an example method of operation of a CT imaging system.

[0155] According to a second aspect, there is provided a method of operating an X-ray imaging system having a gantry including a movable part on a movable side and a stationary part on a stationary side, the movable part and the stationary part being communicatively coupled through a data communication system, the movable part including an X-ray source configured to emit X-rays, an X-ray detector configured to generate detector data, and processing circuitry of the gantry movable part.

[0156] Basically, the method comprises the following steps: S1 - the X-ray detector generating detector data, S2 - a processing circuit of the gantry moving part determining, for each partial data set of several partial data sets of the generated detector data, an index value of at least one index based on the detector data of the partial data set, S3 - a processing circuit of the gantry moving part assigning a type of data management for the partial data set from among at least two different types of data management depending on the determined index value, and S4 - a processing circuit of the gantry moving part selectively performing data management for the partial data set according to the assigned type of data management.

[0157] As mentioned above, at least some of the steps, functions, procedures, and / or blocks described herein may be implemented in software (e.g., a computer program) for execution by suitable processing circuitry (e.g., one or more processors or processing units).

[0158] According to a third aspect, there is provided a computer program product including a non-volatile computer readable storage medium having a computer program stored thereon, the computer program including instructions which, when executed by a processing circuit arranged on a movable part of a gantry of an X-ray imaging system, cause the processing circuit to determine, for each partial data set of a plurality of partial data sets of detector data generated by an X-ray detector of the X-ray imaging system, an index value of at least one index based on the detector data of the partial data set, assign a type of data management for the partial data set from among at least two different types of data management in dependence on the determined index value, and selectively perform data management of the partial data set in accordance with the assigned type of data management.

[0159] 16 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 including instructions executable by the processor, thereby operative to perform the steps and / or operations described herein. The instructions are typically configured as computer programs 225; 235 and may be pre-loaded in the memory 220 or downloaded from an external memory device 230. Optionally, the system 200 includes an input / output interface 240 that may be connected to the processor 210 and / or the memory 220 to allow relevant data (such as input parameters and / or resulting output parameters) to be input and / or output.

[0160] In particular embodiments, memory 220 includes a set of instructions executable by a processor, such that the processor is operable to perform the steps and / or operations described herein.

[0161] The term "processor" should be construed in a general sense as a system or device capable of executing program code or computer program instructions to perform specific processing, decision-making, or computational tasks.

[0162] Thus, processing circuitry, including one or more processors, when executing computer programs is configured to perform well-defined processing tasks as described herein.

[0163] The processing circuitry need not be specialized solely to perform the steps, functions, procedures and / or blocks described above, but may perform other tasks.

[0164] The present technology also provides a computer program product including a computer readable medium 220; 230 having a computer program stored thereon.

[0165] As an example, the software or computer program 225;235 may be realized as a computer program product, which is typically stored or stored on a computer-readable medium 220;230 (particularly a non-volatile medium). The computer-readable medium may include, but is not limited to, one or more removable or non-removable memory devices, including 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 program may be loaded into the operating memory of a computer or equivalent processing device and executed by its processing circuitry.

[0166] The flow of the method can be considered as a flow of computer operations when executed by one or more processors. The corresponding apparatus, system and / or machine can 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 by the processor. Thus, the apparatus, system and / or machine may alternatively be defined as a group of functional modules, where the functional modules are implemented as computer programs executed by at least one processor.

[0167] Thus, the computer programs resident in the memory may be organized as appropriate functional modules configured to perform at least a portion of the steps and / or tasks described herein when executed by the processor.

[0168] Alternatively, most of the modules may be implemented as hardware modules or may be substituted with hardware - software or hardware is purely an implementation choice.

[0169] It should be understood that the above-described embodiments are given by way of example only, and the proposed technology is not limited thereto. It is understood that a person skilled in the art can make various modifications, combinations, and variations to the embodiments without departing from the scope of the present invention defined by the claims.

[0170] It is further to be noted that the inventive concept relates to all possible combinations of features, unless expressly stated otherwise, and in particular different part solutions in the different embodiments can be combined in other configurations, if technically possible. [Explanation of symbols]

[0171] 10 X-ray source 11 Gantry 12 Patient Table 13 Isocenter 15 Gantry 20 X-ray detector 21 Semiconductor Sensor 23 Signal Path 24 Parallel Processing Circuit 25 Analog Processing Circuit 25 ASIC 26 Send 30 Image Processing System 40 Digital Processing Circuit 41 X-ray controller 42 Gantry Controller 43 Table Controller 44 Detector Controller 45 Components 50 Computer 60 Operator Console 62 Display 100 CT System 110 Rotating section 111 Gantry 114 X-ray detector 116 Processing Circuit 118 Data Storage Unit 120 Stationary part 122 Processing circuit 130 Data Communication Systems 301 Digital-to-Analog Converter (DAC) 302 Comparator 303 Digital Counter

Claims

1. 1. An x-ray imaging system comprising: the x-ray imaging system includes a gantry including a movable part on a movable side and a stationary part on a stationary side, the movable part and the stationary part being communicatively coupled through a data communication system; The movable part is an x-ray source configured to emit x-rays; an x-ray detector configured to generate detector data; and Processing circuit for the moving parts of the gantry Including, the processing circuitry of the gantry moving part is configured to determine, for each partial data set of a plurality of partial data sets of generated detector data, an index value of at least one index, the index value being convertible into a type of data management for the partial data set from among at least two different types of data management; a processing circuit of the gantry moving part configured to determine, for each partial data set, how the partial data set should be treated depending on the determined index value of the at least one index, and to selectively perform data management in accordance with a corresponding type of data management.

2. 2. The x-ray imaging system of claim 1, wherein the x-ray imaging system is a computed tomography (CT) imaging system, and the moving and stationary parts are the rotating and stationary parts of a gantry of the CT system.

3. 2. The X-ray imaging system of claim 1, wherein the processing circuitry of the gantry moving part is configured to identify at least two different partial data sets of the generated detector data to which different types of data management should be applied.

4. The at least two different types of data management include: performing data processing on the moving gantry part on the generated partial data set of detector data before transmitting the generated partial data set of detector data from the moving part to the stationary part; no data processing is performed on the generated partial data set of detector data at the moving part of the gantry before transmitting the generated partial data set of detector data from the moving part to the stationary part; and Omitting transmission of a partial data set of the generated detector data. The x-ray imaging system of claim 1 , comprising at least one of:

5. 2. The X-ray imaging system of claim 1, wherein the processing circuitry of the gantry moving part is configured to determine, based on a determined index value of the at least one index for a first partial data set, that data processing at the moving part of the gantry should be applied to the first partial data set before it is transmitted from the moving part to the stationary part, and the processing circuitry of the gantry moving part is configured to determine, based on a determined index value of the at least one index for a second partial data set, that the second partial data set should be transmitted from the moving part to the stationary part without data processing at the moving part of the gantry being performed, or that data processing at the moving part of the gantry, which has a lower computational complexity than data processing for the first partial data set, should be applied to the second partial data set before it is transmitted from the moving part to the stationary part.

6. 6. The X-ray imaging system of claim 5, wherein the processing circuitry of the gantry moving part is configured to perform data processing on the first partial data set at the gantry moving part so as to reduce the data, generate a data-reduced first partial data set, and transmit the data-reduced first partial data set from the moving part to the stationary part.

7. 7. The x-ray imaging system of claim 6, further comprising additional processing circuitry in the stationary portion, the additional processing circuitry configured to perform a material decomposition procedure adapted to the data reduced first partial data set.

8. 13. The X-ray imaging system of claim 12, wherein the processing circuitry of the gantry moving part is configured to determine to which of at least two non-overlapping time intervals the determined index value of the at least one index belongs, each time interval being associated with a respective data management of the at least two different types of data management, and wherein the determined index value can be associated with a particular type of data management for the partial data set of interest.

9. 2. The X-ray imaging system of claim 1, wherein the at least one index includes a pile-up index representing an amount of pile-up of pulses in at least a portion of a target partial data set of the generated detector data, and the processing circuitry of the gantry moving part is configured to determine whether data processing for pile-up correction at the gantry moving part should be applied to the partial data set depending on a determined index value of the pile-up index, and to selectively perform data processing for pile-up correction at the gantry moving part on the partial data set to generate a corrected data set.

10. 10. The x-ray imaging system of claim 9, wherein additional gantry off-moving part pile-up correction data processing of the corrected data set is performed by processing circuitry in the stationary part.

11. 10. The X-ray imaging system of claim 9, wherein the processing circuitry of the gantry moving part is configured to perform data processing for pile-up correction at the gantry moving part when the determined index value of the pile-up index indicates an amount of pile-up greater than zero but less than a first threshold level.

12. 2. The X-ray imaging system of claim 1, wherein the data communication system is configured to transmit, for at least one partial data set, a representation of a corresponding determined index value or an identifier representative of an applied type of data management from the moving part to the stationary part in association with the partial data set.

13. 2. The X-ray imaging system of claim 1, wherein the movable part includes a data storage unit of the gantry movable part connected to processing circuitry of the gantry movable part for storing detector data in processed and / or unprocessed form.

14. 1. A method of operating an X-ray imaging system, the X-ray imaging system including a gantry including a movable part on a movable side and a stationary part on a stationary side, the movable part and the stationary part being communicatively coupled through a data communication system, the movable part including an X-ray source configured to emit X-rays, an X-ray detector configured to generate detector data, and processing circuitry for a gantry movable part, the method comprising: the x-ray detector generating detector data; a processing circuit of the gantry moving part determining, for each partial data set of a plurality of partial data sets of the generated detector data, an index value of at least one index based on the detector data of the partial data set; a processing circuit of the gantry moving part assigning a type of data management to the partial data set from among at least two different types of data management depending on the determined index value; and a processing circuit of the gantry moving part selectively performing data management of the partial data sets in accordance with an assigned type of data management. A method comprising:

15. 1. A computer program product including a non-volatile computer readable storage medium having a computer program stored thereon, the computer program, when executed by a processing circuit disposed in a moving part of an x-ray imaging system, causing the processing circuit to: for each partial data set of a plurality of partial data sets of detector data generated by an x-ray detector of the x-ray imaging system, determining an index value of at least one index based on the detector data of the partial data set; assigning a type of data management to the partial data set from among at least two different types of data management depending on the determined index value; and selectively performing data management of the partial data sets according to the assigned types of data management; A computer program product comprising instructions for causing a computer to execute the steps of:

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