A detector for an imaging system

Abstract

The embodiment of the present specification provides a kind of for the detector of imaging system, comprising: reference detector module, for determining the data processing parameter of signal detector, the data processing parameter of signal detector is determined by obtaining the reference data output by the reference detector module, and analyzing the reference data.Wherein, the reference detector module includes at least one pre-filter, the filter includes two or more filter materials, for cooperating with at least one reference detector in the reference detector module, corrects the nonlinear response of the signal detector under the condition of preset incident photon.

Description

Technical Field

[0001] This specification relates to the field of medical devices, and in particular to a detector for use in imaging systems. Background Technology

[0002] CT (Computed Tomography) imaging equipment uses X-ray beams to scan a slice of the human body of a certain thickness. The CT detector receives the X-rays that pass through this slice, converts them into visible light, then converts them into electrical signals via photoelectric conversion, and finally into digital signals via an analog-to-digital converter. This digital signal is then processed by a computer to form an image, providing doctors with a scientific basis for determining whether there are lesions in the patient's tissues. High-quality CT images depend not only on the setting of the scanning parameter set but also on the selection of data processing parameters during reconstruction, correction, and post-processing.

[0003] Therefore, it is hoped that a detector for imaging systems can be proposed that can provide a reference standard for signal detectors and help determine more reasonable and accurate data processing parameters. Summary of the Invention

[0004] This specification provides, in one aspect, a detector for an imaging system. The detector includes: a reference detector module for determining data processing parameters of a signal detector; the data processing parameters of the signal detector are determined by acquiring reference data output from the reference detector module and analyzing the reference data; wherein the reference detector module includes at least one pre-filter, the filter comprising two or more filter materials for use with at least one reference detector in the reference detector module.

[0005] In some embodiments, the reference detector module includes at least two reference detectors, one of which is used to correct the nonlinear response of the signal detector under preset incident conditions.

[0006] In some embodiments, the reference detector module includes at least one photon counting reference detector.

[0007] In some embodiments, the signal detector includes a photon counting detector; the filter is configured to filter out rays that have not passed through the subject before being received by the reference detector, such that the difference between the output data of the reference detector for the received rays and the output data of the signal detector for the received rays that have passed through the subject is less than a preset threshold.

[0008] In some embodiments, the current filter material of the filter is determined according to a scanning protocol, and / or the filter thickness of the filter is determined according to information about the subject.

[0009] In some embodiments, the energy detection range of the photon counting reference detector and the energy detection range of the signal detector meet preset conditions.

[0010] In some embodiments, the reference detector module further includes at least one energy integration reference detector, which is used to correct the unstable response of the signal detector caused by the unstable output of the X-ray source.

[0011] In some embodiments, the energy integration reference detector is further configured to calibrate the photon counting reference detector to obtain a correction factor for correcting the spectral response of the signal detector.

[0012] In some embodiments, the data processing parameters are determined by analyzing the reference data using a trained machine learning model, or by iteratively calculating the reference data using a preset algorithm.

[0013] In some embodiments, the data processing parameters include at least one of the following: detector output data processing parameters, image reconstruction parameters, and image post-processing parameters. Attached Figure Description

[0014] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0015] Figure 1 These are schematic diagrams illustrating application scenarios of exemplary imaging systems according to some embodiments of this specification;

[0016] Figure 2 This is a schematic diagram of an exemplary detector for an imaging system according to some embodiments of this specification;

[0017] Figure 3 This is a schematic diagram of an exemplary detector for an imaging system according to other embodiments of this specification;

[0018] Figure 4 This is a three-dimensional structural schematic diagram of an exemplary reference detector module according to some embodiments of this specification;

[0019] Figure 5 This is a schematic diagram of the structure of an exemplary pre-filter according to some embodiments of this specification;

[0020] Figure 6 This is a schematic diagram of a module of an exemplary detector output data processing system according to some embodiments of this specification;

[0021] Figure 7 This is a flowchart illustrating an exemplary detector output data processing method according to some embodiments of this specification. Detailed Implementation

[0022] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0023] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0024] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0025] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. The related descriptions are provided to aid in a better understanding of the medical imaging methods and / or systems. It should be understood that preceding or subsequent operations are not necessarily performed precisely in sequence. Instead, steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0026] Figure 1 This is a schematic diagram illustrating an application scenario of an exemplary imaging system according to some embodiments of this specification.

[0027] like Figure 1 As shown, the imaging system 100 may include an imaging device 110, a processing device 120, one or more terminals 130, a storage device 140, and a network 150. The components in the imaging system 100 may be connected in one or more of various ways. This is merely an example. Figure 1As shown, imaging device 110 can be connected to processing device 120 via network 150. As another example, imaging device 110 can be directly connected to processing device 120, as indicated by the dotted double-headed arrows in the figure. As yet another example, storage device 140 can be directly connected to processing device 120. Figure 1 (Not shown in the diagram) or connected via network 150. As another example, one or more terminals 130 may be directly connected to processing device 120 (as shown by the dashed double-headed arrows connecting terminal 130 and processing device 120) or connected via network 150.

[0028] Imaging device 110 can be used to scan a target object within a detection area to obtain scan data of the target object. In some embodiments, the target object may include biological and / or non-biological objects. For example, the target object may include specific parts of the body, such as the head, chest, abdomen, etc., or combinations thereof. As another example, the target object may be a living or non-living organic and / or inorganic material. In some embodiments, the scan data related to the target object may include projection data of the target object, one or more scan images, etc.

[0029] In some embodiments, imaging device 110 may include a non-invasive bioimaging device for disease diagnosis or research purposes. For example, imaging device 110 may include a single-modal scanner and / or a multimodal scanner. A single-modal scanner may include, for example, an ultrasound scanner, an X-ray scanner, a computed tomography (CT) scanner, a magnetic resonance imaging (MRI) scanner, an ultrasound examination device, a positron emission tomography (PET) scanner, an optical coherence tomography (OCT) scanner, an ultrasound (US) scanner, an intravascular ultrasound (IVUS) scanner, a near-infrared spectroscopy (NIRS) scanner, a far-infrared (FIR) scanner, etc. A multimodal scanner may include, for example, an X-ray imaging-magnetic resonance imaging (X-ray-MRI) scanner, a positron emission tomography-X-ray imaging (PET-X-ray) scanner, a single-photon emission computed tomography-magnetic resonance imaging (SPECT-MRI) scanner, a positron emission tomography-computed tomography (PET-CT) scanner, a digital subtraction angiography-magnetic resonance imaging (DSA-MRI) scanner, etc. The scanners described above are for illustrative purposes only and are not intended to limit the scope of this specification. As used herein, the term “imaging modality” or “modality” broadly refers to imaging methods or techniques for collecting, generating, processing, and / or analyzing imaging information of a target object.

[0030] In some embodiments, the imaging device 110 may include modules and / or components for performing imaging and / or related analyses. In some embodiments, the imaging device 110 may include a radiation generating device, auxiliary devices, and an imaging device. A radiation generating device refers to a device that generates and controls radiation (e.g., X-rays). Radiation auxiliary devices refer to various facilities designed to complement the radiation generating device to meet the needs of clinical diagnosis and treatment; for example, they may include mechanical equipment such as examination beds, diagnostic beds, catheterization beds, radiography beds, etc., various support and suspension devices, braking devices, grids, holding devices, and shielding devices. In some embodiments, the radiation imaging device may take many forms; for example, a digital imaging device may include a detector, computer system, and image processing software; other imaging devices may include a fluorescent screen, film cassette, image intensifier, or video conferencing device.

[0031] This specification will primarily describe an imaging device, including a digital imaging apparatus, as an example in its embodiments. The detector can be used to convert the acquired optical signals into electrical signals.

[0032] In some embodiments, the imaging device 110 may include a reference detector and a signal detector. The reference detector can be used to measure the energy intensity of the raw radiation (i.e., radiation that has not passed through the subject) before it enters the specimen. The signal detector can be used to receive the radiation that has passed through the specimen (target object) to obtain relevant data about the target object. Typically, the energy data of the radiation (e.g., X-rays) measured by the reference detector is used as reference correction data for the radiation intensity before it enters the specimen. This allows for correction of the signal detector response under different operating conditions (e.g., nonlinear response between the output and input count rates caused by pulse stacking, polarization effects, pre-conditions, etc.), thereby improving the quality of the imaging image.

[0033] In some embodiments, the imaging device 110 may include one or more reference detectors, which form a reference detector module. In some embodiments, the imaging device 110 may include one or more signal detectors, which form a signal detector module.

[0034] In some embodiments, the detector (e.g., a reference detector, a signal detector) may include a photosensitive module and a readout circuit. The photosensitive module can be used to acquire photon signals from incident rays and convert the acquired photon signals into electrical signals. The readout circuit can be used to read the electrical signals collected in the photosensitive module and convert them into digital data for use in generating medical images, etc. In some embodiments, the detector (e.g., a reference detector, a signal detector) may include semiconductor detectors, photovoltaic detectors, etc., and this specification does not limit this to these.

[0035] In some embodiments, data acquired by imaging device 110 (e.g., medical images of the target object, detector output data, etc.) may be transmitted to processing device 120 for further analysis. Additionally or alternatively, data acquired by imaging device 110 may be sent to terminal device (e.g., terminal 130) for display and / or to storage device (e.g., storage device 140) for storage.

[0036] The processing device 120 can process data and / or information acquired and / or extracted from the imaging device 110, the terminal 130, the storage device 140, and / or other storage devices. For example, the processing device 120 can acquire reference data output from a reference detector module and analyze the reference data to determine data processing parameters for the signal detector.

[0037] In some embodiments, processing device 120 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processing device 120 may be local or remote. In some embodiments, processing device 120 may be implemented on a cloud platform. By way of example only, a cloud platform may include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, internal cloud, multi-tiered cloud, etc., or any combination thereof. In some embodiments, processing device 120 may be implemented on a computing device. In some embodiments, processing device 120 may be implemented on a terminal (e.g., terminal 130). In some embodiments, processing device 120 may be implemented on an imaging device (e.g., imaging device 110). For example, processing device 120 may be integrated into terminal 130 and / or imaging device 110.

[0038] Terminal 130 can be connected to imaging device 110 and / or processing device 120 for inputting / outputting information and / or data. For example, a user can interact with imaging device 110 through terminal 130 to control one or more components of imaging device 110. As another example, imaging device 110 can output generated medical images to terminal 130 for display to the user.

[0039] In some embodiments, terminal 130 may include mobile device 131, tablet computer 132, laptop computer 133, etc., or any combination thereof. In some embodiments, mobile device 131 may include smart home device, wearable device, smart mobile device, virtual reality device, augmented reality device, etc., or any combination thereof.

[0040] In some embodiments, one or more terminals 130 can remotely operate the imaging device 110. In some embodiments, the terminal 130 can operate the imaging device 110 via a wireless connection. In some embodiments, one or more terminals 130 may be part of the processing device 120. In some embodiments, the terminal 130 may be omitted.

[0041] Storage device 140 may store data and / or instructions. In some embodiments, storage device 140 may store data acquired from terminal 130 and / or processing device 120. For example, storage device 140 may store reference data output by a reference detector, detection data output by a signal detector, etc. In some embodiments, storage device 140 may store data and / or instructions, and processing device 120 may execute or use the data and / or instructions to perform the exemplary methods described in this application.

[0042] In some embodiments, storage device 140 may include mass storage devices, removable storage devices, volatile read-write memory, read-only memory (ROM), and any combination thereof. Exemplary mass storage devices may include disks, optical disks, solid-state drives, etc. Exemplary removable storage devices may include flash drives, floppy disks, optical disks, memory cards, compact disks, magnetic tapes, etc. Exemplary volatile read-write memory may include random access memory (RAM). In some embodiments, storage device 140 may be implemented on a cloud platform. In some embodiments, storage device 140 may be part of processing device 120.

[0043] Network 150 may include any suitable network that can facilitate the exchange of information and / or data between imaging system 100. In some embodiments, one or more components of imaging system 100 (e.g., imaging device 110, one or more terminals 130, processing device 120, or storage device 140) may communicate with one or more other components of imaging system 100 to transmit information and / or data. In some embodiments, network 150 may be any type of wired or wireless network or a combination thereof. For example, network 150 may be and / or include public networks (e.g., the Internet), private networks (e.g., local area networks (LANs), wide area networks (WANs), etc.), wired networks (e.g., Ethernet), wireless networks (e.g., 802.11 networks, Wi-Fi networks, etc.), cellular networks (e.g., LTE networks), Frame Relay networks, virtual private networks (“VPNs”), satellite networks, telephone networks, routers, hubs, switches, server computers, and / or any combination thereof. In some embodiments, network 150 may include one or more network access points.

[0044] It should be noted that the above description of the imaging system 100 is for illustrative purposes only and is not intended to limit the scope of this specification. Various modifications and variations can be made based on this specification by those skilled in the art. However, these changes and modifications do not depart from the scope of this specification. For example, the imaging device 110, processing device 120, and terminal 130 may share a single storage device 140, or they may each have their own storage devices.

[0045] In some embodiments, the detector may include a photon counting detector (PCD) and an energy integrating detector (EID).

[0046] When a ray enters a semiconductor detector and is deposited in a pixel, the corresponding photon generates an electron-hole pair. Under high voltage (e.g., a bias voltage of 100-150V), these electron-hole pairs separate and drift to the corresponding electrode, generating an induced charge. The detector can collect this induced charge and output photon counts or charge integrals for different energy ranges. A detector that outputs photon counts (i.e., ray counts) for different energy ranges is called a photon-counting detector, while one that outputs charge integrals for different energy ranges is called an energy-integrating detector. For example, a photon-counting detector may include a counting integrated circuit consisting of a preamplifier circuit, a shaping and filtering circuit, a pulse comparator, and a digital signal output circuit. By comparing the pulses of the shaped and filtered signal, it outputs photon counts for different energy ranges. Similarly, an energy-integrating detector may include an integrating integrated circuit consisting of a shaping and filtering circuit and a charge-integrating circuit. By integrating the shaped and filtered photocurrent (i.e., the current signal generated by photon conversion), it achieves charge integration of the photogenerated charge.

[0047] CT imaging systems based on photon-counting detectors have advantages such as enabling material composition analysis, reducing patient radiation dose, improving the accuracy of quantitative CT analysis, and achieving ultra-high spatial resolution. Therefore, photon-counting computed tomography (PCCT) has been widely used in medical imaging.

[0048] For energy-integrating detectors, the output count rate maintains a good linear response to the input count rate over a wide range, with minimal differences in multiple counts, resulting in good long-term stability. However, in PCCT systems, the output characteristics of photon counting detectors are strongly influenced by operating conditions, leading to significant differences in counts across multiple counts and poor long-term stability. Furthermore, depending on the detector manufacturing process, various factors can contribute to the nonlinear response between the X-ray output and the input count value, including pulse buildup, charge sharing, failure of the detector data readout circuit's leakage current protection mechanism, defects in the detector crystal itself, polarization effects, and pre-conditioning.

[0049] In some embodiments, the polarization effect caused by polarization in PCCT systems can be addressed by real-time monitoring of detector characteristics (e.g., photon counting threshold, leakage current, etc.) using fixed reference detectors uniformly distributed at 360°. In some embodiments, reference detectors can be placed outside at least two imaging optical paths to address problems caused by rapid energy switching and other variations in PCCT systems. However, in PCCT systems, there is still no solution to the nonlinear response problem of photon counting detectors under different incident energies (related to X-ray tube voltage), different incident count rates (related to X-ray tube current, scanning location, patient characteristics, real-time scanning angle, etc.), and different operating conditions (e.g., the presence of pre-conditioning, detector module temperature changes, etc.).

[0050] This specification provides a detector for an imaging system, including a signal detector module and a reference detector module. In some embodiments, the reference detector module may include at least one pre-filter. The filter may include two or more filter materials for use in conjunction with at least one reference detector in the reference detector module to correct the nonlinear response of the signal detector under preset incident photon conditions.

[0051] Figure 2 This is a schematic diagram of an exemplary detector for an imaging system according to some embodiments of this specification.

[0052] like Figure 2 As shown, in some embodiments, the imaging system 200 (imaging device 110) may include an X-ray source 210, a reference detector module 220, and a signal detector module 230.

[0053] The radiation source 210 can be used to emit radiation, such as X-rays. In some embodiments, the radiation source 210 may include an X-ray tube.

[0054] The reference detector module 220 can be used to measure radiation passing before the subject to correct the measurement data of the signal detector module 230. In some embodiments, the reference detector module 220 may include at least one reference detector. In some embodiments, the reference detector module 220 may include at least one photon-counting reference detector. In some embodiments, the reference detector module 220 may include at least one energy-integrating reference detector. In some embodiments, the reference detector module 220 may include at least two reference detectors. One of the reference detectors can be used to output reference data and / or correct the nonlinear response of the signal detector under preset incident conditions. In some embodiments, the reference detector module 220 may include a photon-counting reference detector and an energy-integrating reference detector.

[0055] The signal detector module 230 can be used to measure rays passing through a subject for acquiring a scanned image of the subject. In some embodiments, the signal detector module 230 may include at least one signal detector. In some embodiments, the signal detector may include a photon counting detector.

[0056] In some embodiments, the energy detection range of the photon-counting reference detector may meet preset conditions with the energy detection range of the photon-counting signal detector. In some embodiments, the preset conditions may include the same energy range and / or the same energy threshold (also known as bin threshold) for the energy range. For example, both the signal detector module and the reference detector module are used to receive rays in four energy ranges: 0keV to 40keV, 40keV to 60keV, and 60keV to the maximum value, respectively, where 40keV and 60keV are the energy thresholds for the energy ranges.

[0057] By ensuring that the energy detection range of the reference detector and the energy detection range of the signal detector meet preset conditions, the data measured by the reference detector can be made consistent or substantially consistent with the data measured by the signal detector, thereby improving the accuracy of the signal detector calibration.

[0058] In some embodiments, the reference detector module 220 can be used to correct the detector response of the signal detector module 230.

[0059] Figure 3 This is a schematic diagram of an exemplary detector for an imaging system according to other embodiments of this specification. For example... Figure 3 As shown, in some embodiments, the reference detector module 220 may include at least one pre-filter 223.

[0060] In some embodiments, at least one pre-filter of the reference detector module 220 may cooperate with at least one reference detector in the reference detector module 220 to correct the nonlinear response of the signal detector (e.g., the detector in the signal detector module 230) under preset incident photon conditions. In some embodiments, the pre-filter may cooperate with a photon-counting reference detector. For example... Figure 4 As shown, the reference detector module 220 may include a PCD reference detector 225 located below the filter 223. The filter 223 cooperates with the PCD reference detector 225 to filter out the rays that have not passed through the subject before being received by the PCD reference detector 225, so as to correct the nonlinear response of the signal detector in the signal detector module 230 under the preset incident photon conditions.

[0061] Preset incident photon conditions can reflect relevant parameters when the signal detector measures X-rays passing through the subject. For example, preset incident photon conditions may include energy ranges, energy thresholds for each range, X-ray tube voltage, tube current, and X-ray incident angle. In some embodiments, preset incident photon conditions can be determined based on the scanning protocol and / or information about the subject. For example, bin number, bin threshold, X-ray tube voltage, and tube current can be determined based on information about the subject. Taking iodine as an example, due to its k-edge absorption characteristics, X-rays with energy values ​​greater than 33 keV are difficult to pass through, easily leading to photon counts in the corresponding energy range being much lower than in other energy ranges or even zero. Therefore, for iodine, specific bin thresholds can be set. For example, energy range 1 corresponds to 30 keV to 50 keV, which includes a value of 33 keV, and energy range 2 corresponds to a bin threshold greater than 50 keV.

[0062] In some embodiments, filter 223 can be configured to filter rays that have not passed through the subject before being received by PCD reference detector 225, such that the difference between the output data (e.g., count value) of the received rays by PCD reference detector 225 and the output data of the received rays that have passed through the subject by signal detector is less than a preset threshold. Accordingly, in this case, signal detector module 230 may include a photon counting detector. The preset threshold can be any reasonable value, such as 1, 3, 5, 7, 10, etc., and this specification does not limit this. In some embodiments, filter 223 can filter rays that have not passed through the subject before being received by PCD reference detector 225, such that the count value of the received rays by PCD reference detector 225 is consistent with the count value of the received rays that have passed through the subject by signal detector.

[0063] In some embodiments, the current filter material of filter 223 can be determined according to a scanning protocol. In some embodiments, the current filter material of the filter can be determined by extracting the contrast agent, matrix pair type, and / or bin threshold from the scanning protocol. For example, when the contrast agent is iodine, the current filter material of filter 223 can be determined to be iodine.

[0064] In some embodiments, the filter may include two or more filter materials. This is merely an example. Figure 5 As shown in (a), the pre-filter 223 corresponding to the PCD reference detector 225 may include multiple filter materials such as A1-A8 (e.g., A1 is iodine, A2 is sodium, A3 is magnesium, etc.). In some embodiments, two or more filter materials of the filter can be switched. For example, the filter material can be selected based on the attenuation characteristics of the contrast agent or target tissue at the current bin threshold setting. Figure 5 (a) shows one of the filter materials A1-A8 as the current filter material.

[0065] In some embodiments, the filtration thickness of the filter can be determined based on information about the subject. The filtration thickness of the filter can reflect the thickness of the filter in the optical path of the reference detector. For example, the thickness of the filter in the optical path of the reference detector can be changed by means of rotation, translation, or stacking. In some embodiments, the information about the subject can reflect the 3D information of the subject. For example, the information about the subject may include localization images (e.g., CT images, MR images, PET images, etc.) or camera data (e.g., images of the subject captured by a camera).

[0066] Different materials attenuate / filter radiation to varying degrees at different thicknesses. For example, for the same material, the thicker the material, the greater the attenuation of radiation.

[0067] In some embodiments, the conversion relationship between different filter materials and the attenuation coefficient of the human body for radiation (e.g., X-rays) at different filtration thicknesses can be determined. For example, the conversion relationship can be determined through data statistics, simulation, or other methods. In some embodiments, based on the information of the subject, the attenuation coefficient (absorption capacity) of the subject (target object) for radiation can be determined, and based on the conversion relationship, this attenuation coefficient can be converted into the thickness corresponding to the current filter material to determine the filtration thickness of the filter.

[0068] In some embodiments, the filter may include two or more filtration thicknesses, which can be switched between. For example... Figure 5As shown in (b), filter 223 may include multiple filtration thicknesses such as B1-B8. After selecting the current filtration material, the corresponding filtration thickness can be further selected from B1-B8 based on the information of the subject to cooperate with PCD reference detector 225, so that the radiation received by PCD reference detector 225 that has not passed through the subject 240 is attenuated, thereby simulating and feeding back the count value of radiation reaching the signal detector after being filtered and absorbed by the patient in real time.

[0069] In some embodiments, the filter material and / or filter thickness of the filter can be determined based on the filtration parameters of the signal detector module 230. For example, the same filter material and filter thickness can be selected for the filter 223 in the reference detector module 220 based on the filter material and filter thickness of the pre-filter of the signal detector. In some embodiments, the filter material and / or filter thickness of the filter can be determined based on the scanning protocol, the information of the subject, and the filtration parameters of the signal detector module.

[0070] By setting up reference detector modules with pre-filters of different materials and filtration thicknesses, it is possible to: 1) make the output data of each bin of the PCD reference detector comparable to the output data of each bin of the PCD signal detector, thus allowing the nonlinear response of the PCD to be simultaneously and equally manifested at both the PCD reference detector and the PCD signal detector ends; 2) since the pre-attenuation of the PCD reference detector does not change with the rotation of the CT gantry, the short-term (e.g., within 15 minutes) radiation history of the PCD detector will have a significant impact on the current output data, and the "detector settling time"—a certain duration from the start of operation to output stabilization for each radiation scan—can be directly and clearly manifested. Because the PCD reference detector and the PCD signal detector have similar or identical performance, the correction method based on the PCD reference detector response can significantly improve the correction accuracy of the PCD signal detector.

[0071] In some embodiments, the filter may include a butterfly filter. In some embodiments, the filter may include two rotating disks, one corresponding to a different filter material and the other to a different filtration thickness. By rotating one of the rotating disks, different filter materials or filtration thicknesses can be selected for the filter (e.g., filter 223) to cooperate with a reference detector (e.g., reference detector 225). As an example only, after determining the current filter material based on the scanning protocol and the filtration thickness based on the localization image of the subject, rotation can be used... Figure 5 (b) The small disk in the diagram selects the appropriate filter material, and the large disk is rotated to select the appropriate filter thickness, so that the current filter material and the corresponding filter thickness are aligned with the X-rays to filter the X-rays that have not passed through the subject.

[0072] Understandable. Figure 5 The structures, quantities of materials, and thicknesses shown are for illustrative purposes only. In some embodiments, the structure corresponding to the filter material and / or the structure corresponding to the filter thickness can be of other shapes and sizes. The filter can include any number of filter materials and / or filter thicknesses, and this specification does not limit this. For example, the diameter of the disk corresponding to the filter material and the disk corresponding to the filter thickness can be the same. Furthermore, multiple filter materials and / or filter thicknesses can be configured using fan-shaped, rectangular, or other structures.

[0073] In some embodiments, the structure corresponding to the filter material can be located close to the X-ray source, for example, near the X-ray tube. In some embodiments, the structure corresponding to the filter thickness can be located close to the reference detector.

[0074] By selecting the current filter material and filter thickness of the filter according to the scanning protocol and the information of the subject, and filtering the rays that have not passed through the subject based on the filter (e.g., filter 223), the attenuation of the rays received by the reference detector (e.g., PCD reference detector 225) corresponding to the filter can be consistent or substantially consistent with that of the rays that have passed through the subject and received by the signal detector. This allows the reference detector module to simulate and provide feedback in real time on the photon count value of the rays that have been filtered and absorbed by the subject before reaching the detector, thereby correcting the nonlinear changes in the photon count value in different energy ranges under different milliamperes and different tube currents, and improving the calibration accuracy of the signal detector.

[0075] For example only, such as Figure 3 As shown, under preset incident photon conditions, after selecting the filter material and filter thickness of filter 223 based on relevant information, PCD reference detector 225 receives the radiation emitted by radiation source 210 that has not passed through the test object 240 but has been filtered by filter 223, and outputs the corresponding photon count value (i.e., the radiation count value); simultaneously, the signal detector in signal detector module 230 receives the radiation emitted by radiation source 210 that has passed through the test object 240, and outputs the corresponding photon count value. Further, a detector response correction curve is determined based on the photon count value output by the detector, and the measurement results of the signal detector are corrected based on this curve to correct the nonlinear response of the signal detector under preset incident photon conditions.

[0076] like Figure 3As shown, in some embodiments, the reference detector module 220 may include an EID reference detector 227 for correcting the unstable response of the signal detector module 230 caused by unstable X-ray source output. For example, a detector response correction curve can be determined based on the energy spectrum corresponding to the measurement data of the EID reference detector 227 and the energy spectrum corresponding to the measurement data of the signal detector module 230 under the same bin number and bin threshold, and the measurement data of the signal detector can be corrected based on the correction curve.

[0077] In some embodiments, under different preset conditions, corresponding detector calibration curves can be obtained to calibrate the signal detector. For example, for a given kvp energy spectrum and an indefinite photon density input (i.e., incident count rate), and for a given photon density input and an indefinite kvp energy spectrum, corresponding detector response calibration curves can be determined respectively (e.g., calibration curves with energy (keV) on the horizontal axis and signal strength / incident count rate on the vertical axis).

[0078] As an example, the output data of the EID detector and the input X-ray value under typical CT operating conditions (e.g., 10keV–140keV) exhibit a very good linear positive correlation. Therefore, before the initial use of the CT equipment, a linear relationship curve between the tube current of the X-ray tube and the output data of the EID detector can be measured. When using the CT equipment, the actual X-ray output value of the X-ray tube of the current CT equipment can be determined based on the output data of the EID reference detector to correct the measurement data of the signal detector. The tube current determines the X-ray output value; tube aging or other abnormal conditions will cause changes in the X-ray output value emitted by the tube under the original tube current. For example, the output data value of the EID reference detector 227 under the current tube current can be used as a benchmark to obtain the actual X-ray output value of the X-ray tube. This output value can then be processed by scanning object attenuation, filtering attenuation, and bin threshold division schemes to obtain the expected output value of each bin of the PCD signal detector. Then, using prior formulas, the actual output values ​​of each bin of the PCD signal detector are fitted and corrected in order to bring the actual output values ​​of the PCD signal detector closer to the desired output values.

[0079] In some embodiments, the EID reference detector 227 may be further configured to calibrate the PCD reference detector 225 to obtain a correction factor for correcting the spectral response of the signal detector. For example, the above-described calibration method for the signal detector can be used, taking the output data value of the EID reference detector 227 at the current tube current as a reference to obtain the actual X-ray output value of the X-ray tube, and determining the desired output value of the PCD reference detector 225 based on this output value, so that the actual output value of the PCD reference detector 225 is consistent with or nearly consistent with the desired output value, thereby obtaining a correction factor for correcting the spectral response of the signal detector.

[0080] In some embodiments, a correction factor for correcting the spectral response of the signal detector can be determined based on the signal intensity value (e.g., energy integral value) of the EID reference detector 227 and the signal output value (e.g., photon count value) of the PCD reference detector 225. As an example only, the signal intensity value output by the EID reference detector 227 can be used as the total number of photon counts, and then converted with the current tube voltage and tube current of the X-ray tube to simulate the spectral intensity of the X-ray at different energies. This spectrum can then be used as input to correct the photon count value output by the PCD reference detector 225 to obtain the correction factor for correcting the spectral response of the signal detector.

[0081] By using the output data of the EID reference detector to correct the output data of the PCD reference detector, a correction result unaffected by attenuation interference from the scanned object can be obtained. Applying this correction result to the PCD signal detector further corrects its output, thereby improving the accuracy of the PCD signal detector correction.

[0082] In some embodiments, the reference detector module 220 can be used to determine the data processing parameters of the signal detector. In some embodiments, the data processing parameters of the signal detector can be determined by acquiring reference data output by the reference detector module 220 and analyzing the reference data. More information on determining the data processing parameters can be found in [link to relevant documentation]. Figure 7 The details and related descriptions will not be repeated here.

[0083] In some embodiments, the rays can enter from the edge or surface of the detector. For example, X-rays emitted from a x-ray tube can enter from... Figure 4 The black arrows shown are pointing perpendicularly into the reference detector module and / or the signal detector module.

[0084] It should be noted that the above Figures 2-5The descriptions of the imaging system and / or its detectors are for illustrative purposes only and do not limit the scope of this specification. Those skilled in the art can make various modifications and changes to the structure of the imaging system and / or its detectors based on the guidance of this specification. For example, the imaging system 200 may include a collimator for adjusting the direction, shape, etc., of the X-ray beam. As another example... Figure 4 The multiple sets of black rectangles representing electrode strips in the detector shown can be replaced with coplanar grid structure electrodes or drift-type structure electrodes. For example, Figure 3 The intermediate reference detector module 220 may include multiple filters 223 and corresponding PCD reference detectors 225, or the reference detector module 220 may include two or more EID reference detectors 227. However, these modifications and changes are still within the scope of this specification.

[0085] Spectral CT refers to an imaging method that utilizes multi-spectral information to improve image quality or provide new image information. The image quality of spectral CT images depends on the operator's selection of post-processing parameters (e.g., data correction parameters, image reconstruction parameters, reconstructed image post-processing parameters, etc.). Different choices of post-processing parameters can provide the operator with CT images that meet clinical needs. In some embodiments, the entire dataset can be iteratively processed using trained machine learning or other intelligent optimization schemes to output the optimal data processing parameters for post-processing. However, the massive amount of photon count data often poses challenges to the iterative process.

[0086] This specification provides a method for processing detector output data in some embodiments, which involves obtaining reference data output from a reference detector module and analyzing the reference data to determine the data processing parameters for subsequent processing of the signal detector.

[0087] Figure 6 This is a schematic diagram of a module of an exemplary detector output data processing system according to some embodiments of this specification. Figure 6 As shown, this specification provides a system for processing detector output data in some embodiments. In some embodiments, the data processing system 600 may include a first acquisition module 610, a second acquisition module 620, a data analysis module 630, and a data processing module 640.

[0088] The first acquisition module 610 can be used to acquire reference data output by the reference detector module. For example, the first acquisition module 610 can be used to acquire reference data such as photon count values ​​and energy integral values ​​output by the reference detector module 220.

[0089] The second acquisition module 620 can be used to acquire detection data output by the signal detector. For example, the second acquisition module 620 can be used to acquire detection data such as photon count values ​​output by the signal detector module 230.

[0090] The data analysis module 630 can be used to analyze reference data to determine data processing parameters. In some embodiments, the data analysis module 630 can determine the data processing parameters by analyzing the reference data using a trained machine learning model. In some embodiments, the data analysis module 630 can determine the data processing parameters by iteratively calculating the reference data using a preset algorithm.

[0091] The data processing module 640 can be used to process the probe data based on data processing parameters.

[0092] It should be noted that the above description of the data processing system 600 and its modules is for convenience only and should not be construed as limiting this specification to the scope of the embodiments described. It is understood that those skilled in the art, after understanding the principles of the system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from these principles. However, such modifications and changes are still within the scope of this specification.

[0093] Figure 7 This is a schematic flowchart illustrating an exemplary detector output data processing method according to some embodiments of this specification. In some embodiments, the data processing method 700 may be executed by the imaging device 110 or the processing device 120. For example, the data processing method 700 may be stored in a storage device (such as storage device 140) in the form of a program or instructions, which can be implemented when the imaging device 110 or the processing device 120 executes the program or instructions. In some embodiments, the data processing method 700 may be executed by the data processing system 600.

[0094] Step 710: Acquire reference data output by the reference detector module. In some embodiments, step 710 may be performed by the first acquisition module 610.

[0095] Reference data can refer to the measurement data of received radiation that has not passed through the subject, output by a reference detector. In some embodiments, the reference detector module 220 can acquire the measurement data of received radiation that has not passed through the subject.

[0096] Step 720: Acquire the detection data output by the signal detector. In some embodiments, step 720 may be performed by the second acquisition module 620.

[0097] The detection data can refer to the measurement data of the received rays passing through the object being inspected, output by the signal detector. In some embodiments, the detection data output by the signal detector in the signal detector module 230 can be acquired.

[0098] Step 730 involves analyzing the reference data to determine data processing parameters. In some embodiments, step 730 may be performed by the data analysis module 630.

[0099] In some embodiments, data processing parameters may include one or more of detector output data processing parameters, image reconstruction parameters, and reconstructed image post-processing parameters. In some embodiments, data processing parameters may include at least one of the following: weight values ​​corresponding to each energy range of the signal detector, the type of denoising algorithm used in image reconstruction, denoising level, reconstructed image layer thickness, filtering function, reconstructed field of view, size of the reconstruction matrix, and weight values ​​of each base material image, image value (e.g., CT value, grayscale value, etc.) extraction / removal methods, etc.

[0100] In some embodiments, a set of data processing parameters that achieves a predetermined image metric with optimal CNR (Contrast-to-Noise Ratio) can be output by analyzing reference data. In some embodiments, data processing parameters can be determined by analyzing the reference data using a trained machine learning model. In some embodiments, data processing parameters can be determined by iteratively calculating the reference data using a preset algorithm. As an example only, reference data can be input into a trained machine learning model to obtain the weight values ​​corresponding to each energy range output by the machine learning model.

[0101] In some embodiments, the machine learning model for determining the data processing parameters of the signal detector can be trained based on the detector's data acquisition settings and the data processing parameters used in subsequent processing. As an example only, conventional image reconstruction and post-processing can be performed based on reference data output by a reference detector and detection data output by the signal detector to obtain a reference image and a signal image with the same characteristics (e.g., optimal CNR or low contrast enhancement). Then, data processing parameters 1 used in image reconstruction and post-processing of the reference data and data processing parameters 2 used in image reconstruction and post-processing of the detection data are extracted, and the settings parameters 1 and 2 of the reference detector and signal detector during data acquisition are obtained from the parameter configuration module. Further, data processing parameters 1 and 2, the settings parameters 1 and 2 of the reference detector, and the settings parameters 2 of the signal detector are used as sample data to train the initial model, obtaining a trained machine learning model for determining the data processing parameters of the signal detector.

[0102] Step 740: Process the probe data based on data processing parameters. In some embodiments, step 740 may be performed by the data processing module 640.

[0103] In some embodiments, the number of detectors can be processed based on determined data processing parameters to obtain spectral CT images with better image quality. For example, the detector data can be calculated based on the weight values ​​corresponding to each energy range of the signal detectors, and / or the detector data can be iteratively reconstructed using a determined noise reduction algorithm to obtain spectral CT images.

[0104] Processing the detection data based on the weighted values ​​corresponding to each energy range makes the distinction between contrast-enhanced and non-contrast-enhanced areas in the obtained images clearer, thereby improving the accuracy of diagnostic results. Contrast-enhanced areas refer to regions in the examined body where contrast agent has been added, while non-contrast-enhanced areas reflect regions without contrast agent. Taking scanning with iodine contrast agent as an example, because iodine significantly absorbs radiation with energies greater than 33keV, the measured data in the 30keV–45keV energy range will be much smaller than those in other energy ranges. In this case, if the weighted value of this energy range is made greater than that of other energy ranges, the CT values ​​or grayscale values ​​of this energy range will be clearly distinguishable from those of other energy ranges. This helps doctors more clearly identify the location of the contrast-enhanced area and its difference from other areas, thereby improving diagnostic efficiency and accuracy.

[0105] It should be noted that the above description of method 700 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to method 700 under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0106] Another aspect of this specification provides an imaging device including a processor and a memory for storing instructions that, when executed by the processor, implement the detector output data processing method as described above.

[0107] Another aspect of this specification provides a computer-readable storage medium for storing computer instructions, which, when read by a computer, execute the detector output data processing method described above.

[0108] The beneficial effects that the embodiments in this specification may bring include, but are not limited to: (1) by adding a pre-filter to the reference detector module, the reference detector can better simulate the nonlinear changes in photon count values ​​in different energy ranges under different tube currents; (2) by using the filter added before the reference detector to filter the rays entering the reference detector, correction can be achieved under flexible clinical scanning protocols, expanding the clinical application range of photon counting technology; (3) by making the energy detection range, photon count value, and attenuation degree of the received rays the same for the reference detector and the signal detector, the correction is real-time and equivalent, thereby better correcting the power density of the photon counting detector over a long period of time. (3) After scanning or multiple intensive scans, the detector reaches a new quasi-stable state, which improves the quality of the imaging image; (4) Based on the reference detector module containing energy integration type and photon counting type reference detector, the nonlinearity, inconsistency and instability of the detector response caused by the instability of the X-ray source output and the change of detector working conditions can be corrected at the same time; (5) Based on the measurement data of the reference detector, the optimal data processing parameters of the signal detector can be determined, which can reduce the amount of iterative calculation, improve the efficiency of data post-processing, and improve the image quality of the energy spectrum CT image; (6) By using machine learning models or iterative algorithms to analyze the reference data, the processing efficiency can be improved and the impact of the amount of calculation can be reduced.

[0109] It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects may be any one or a combination of the above, or any other possible beneficial effects.

[0110] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0111] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0112] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0113] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0114] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0115] For each patent, patent application, patent application publication, and other material, such as articles, books, specifications, publications, and documents, referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0116] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A detector for an imaging system, characterized in that, include: Reference detector module, used to determine the data processing parameters of the signal detector; The data processing parameters of the signal detector are determined by acquiring reference data output by the reference detector module and analyzing the reference data. The reference detector module includes at least one pre-filter, which includes two or more selectable filter materials and two or more selectable filter thicknesses, for use in conjunction with at least one reference detector in the reference detector module to correct the nonlinear responsivity of the signal detector under preset incident photon conditions; the filter includes multiple first sub-filters and multiple second sub-filters, the multiple first sub-filters being configured with different filter materials and the multiple second sub-filters being configured with different filter thicknesses; Based on the scanning protocol, one of the two or more filter materials is determined as the current filter material of the at least one reference detector. Based on the positioning image of the subject, one of the two or more filter thicknesses is determined as the current filter thickness. By switching the first sub-filter to select the corresponding filter material and by switching the second sub-filter to select the corresponding filter thickness, the current filter material and the current filter thickness are aligned with the X-rays to filter the X-rays that have not passed through the subject.

2. The detector according to claim 1, characterized in that, The reference detector module includes at least two reference detectors, one of which is used to correct the nonlinear response of the signal detector under preset incident conditions.

3. The detector according to claim 1, characterized in that, The reference detector module includes at least one photon counting reference detector.

4. The detector according to claim 3, characterized in that, The signal detector includes a photon counting detector; The filter is configured to filter out rays that have not passed through the subject before being received by the reference detector, such that the difference between the output data of the reference detector for the received rays and the output data of the signal detector for the received rays that have passed through the subject is less than a preset threshold.

5. The detector according to claim 3, characterized in that, The energy detection range of the photon counting reference detector and the energy detection range of the signal detector meet preset conditions.

6. The detector according to claim 3, characterized in that, The reference detector module further includes at least one energy integration type reference detector, which is used to correct the unstable response of the signal detector caused by the instability of the X-ray source output, and / or to calibrate the photon counting type reference detector to obtain a correction factor for correcting the spectral response of the signal detector.

7. The detector according to claim 1, characterized in that, The data processing parameters are determined by analyzing the reference data using a trained machine learning model, or by iteratively calculating the reference data using a preset algorithm.

8. The detector according to claim 1, characterized in that, The data processing parameters include at least one of the following: detector output data processing parameters, image reconstruction parameters, and image post-processing parameters.

Images