An attenuation correction method, system, and storage medium

Abstract

This specification provides an attenuation correction method, system, and storage medium. The method includes: acquiring transmission data; acquiring radiometric coincidence event data of a target object; and performing attenuation correction and reconstruction on the radiometric image of the target object based on the transmission data and the radiometric coincidence event data to obtain an attenuated radiometric image. The attenuation correction system is used to implement the attenuation correction method and includes: a first acquisition module for acquiring transmission data; a second acquisition module for acquiring radiometric coincidence event data of the target object; and a reconstruction module for performing attenuation correction and reconstruction on the radiometric image of the target object based on the transmission data and the radiometric coincidence event data to obtain an attenuated radiometric image.

Description

Technical Field

[0001] This specification relates to the field of positron emission tomography (PET) technology, and in particular to an attenuation correction method, system, and storage medium. Background Technology

[0002] Attenuation correction is a crucial factor that needs to be compensated for in quantitative positron emission tomography (PET). Attenuation correction is typically achieved by fusing PET and computed tomography (CT) data. CT data provides tissue density information, which can be used to calculate photon attenuation coefficients. These attenuation coefficients are then applied to the PET data to eliminate the attenuation effect of photons within the tissue. However, attenuation maps (μ-maps) derived from CT data have certain limitations. For example, high radiation doses, metal artifacts, beam hardening artifacts, truncation in large patients, and patient movement between PET / CT scans can all affect the derived results.

[0003] Therefore, there is a need for an attenuation correction method, system, and storage medium that can provide accurate attenuation correction results. Summary of the Invention

[0004] This specification provides one or more embodiments of an attenuation correction method, the method comprising: acquiring transmission data; acquiring radiation coincidence event data of a target object; and performing attenuation correction and reconstruction on a radiation image of the target object based on the transmission data and the radiation coincidence event data to obtain an attenuated radiation image; wherein the transmission data includes backscattering coincidence event data of the target object.

[0005] In some embodiments, acquiring transmission data includes: acquiring single-event data of the target object; determining whether the energy and arrival time of the single-event data conform to a first preset rule; and, in response to the single-event data conforming to the first preset rule, determining the single-event data conforming to the first preset rule as the transmission data.

[0006] In some embodiments, obtaining radiation coincidence event data of a target object includes: obtaining single event data of the target object; determining whether the energy and arrival time of the single event data conform to a second preset rule; and, in response to the single event data conforming to the second preset rule, determining the single event data conforming to the second preset rule as the radiation coincidence event data.

[0007] In some embodiments, the step of performing attenuation correction and reconstruction on the radiation image of the target object based on the transmission data and the radiation coincidence event data to obtain the attenuation-corrected radiation image includes: initializing the attenuation image to obtain an initial attenuation image; initializing the radiation image to obtain an initial radiation image; and iteratively reconstructing the radiation image based on the initial attenuation image, the initial radiation image, the transmission data, and the radiation coincidence event data to obtain the attenuation-corrected radiation image.

[0008] In some embodiments, the iteration includes: obtaining a backscattering estimate, a blank scan estimate of the backscattering, and a scattering estimate of the emission based on the attenuation image and the emission image of the previous iteration; the attenuation image of the first iteration is the initial attenuation image, and the emission image of the first iteration is the initial emission image; obtaining the attenuation image of the current iteration based on the backscattering estimate, the blank scan estimate of the backscattering, and the transmission data; obtaining the emission image of the current iteration based on the attenuation image of the current iteration, the scattering estimate of the emission, and the emission coincidence event data; determining whether the iteration termination condition is met; if not, proceeding to the next iteration; if so, determining the emission image of the current iteration as the attenuation-corrected emission image.

[0009] In some embodiments, obtaining the backscattering estimation, the blank scan estimation of the backscattering, and the scattering estimation of the radiation based on the attenuation image and the radiation image from the previous iteration includes: processing the attenuation image and the radiation image from the previous iteration using a first processing method to obtain the backscattering estimation and the radiation estimation; and processing the attenuation image and the radiation image from the previous iteration using a second processing method to obtain the blank scan estimation of the backscattering; the second processing method includes at least one of the Monte Carlo method and the lookup table method.

[0010] In some embodiments, the backscattering coincidence event data is acquired by a positron emission tomography (PET) system, and the lookup table includes the probability distribution of backscattering events occurring on each response line of the PET system being detected on the remaining response lines. The lookup table method includes: acquiring the lookup table; simplifying the lookup table based on the symmetry of the PET system and / or the merging of the response lines; and determining a blank scan estimate of the backscattering based on the simplified lookup table and the scan data.

[0011] In some embodiments, the transmission data further includes lutetium background event data.

[0012] This specification provides one or more embodiments of an attenuation correction system for implementing an attenuation correction method. The system includes: a first acquisition module for acquiring transmission data; a second acquisition module for acquiring radiation coincidence event data of a target object; and a reconstruction module for performing attenuation correction and reconstruction on the radiation image of the target object based on the transmission data and the radiation coincidence event data to obtain an attenuated radiation image; wherein the transmission data includes backscattering coincidence event data of the target object.

[0013] This specification provides one or more embodiments of a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions from the storage medium, the computer executes the attenuation correction method. 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 the attenuation correction system according to some embodiments of this specification;

[0016] Figure 2 These are exemplary schematic diagrams of attenuation correction systems according to some embodiments of this specification;

[0017] Figure 3 This is an exemplary flowchart of an attenuation correction method according to some embodiments of this specification;

[0018] Figure 4 This is an exemplary schematic diagram illustrating the acquisition of radiation coincidence event data of a target object according to some embodiments of this specification;

[0019] Figure 5 This is an exemplary schematic diagram of a backscattering event according to some embodiments of this specification;

[0020] Figure 6 This is an exemplary schematic diagram of lutetium background events according to some embodiments of this specification;

[0021] Figure 7 These are exemplary schematic diagrams illustrating symmetry according to some embodiments of this specification;

[0022] Figure 8 These are exemplary schematic diagrams of attenuation images shown according to some embodiments of this specification;

[0023] Figure 9AThis is an exemplary flowchart illustrating the determination of attenuation-corrected radiographic images according to some embodiments of this specification;

[0024] Figure 9B This is an exemplary flowchart illustrating the determination of attenuation-corrected radiographic images according to other embodiments of this specification;

[0025] Figure 9C This is an exemplary flowchart illustrating the determination of attenuation-corrected radiographic images according to some embodiments of this specification. Detailed Implementation

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the 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.

[0030] Attenuation correction (AC) is an important step in PET imaging. During PET imaging, the emitted positrons interact with the surrounding tissue to produce 511 keV photons. These photons are attenuated to varying degrees as they pass through human tissue, and therefore, it is necessary to correct for this attenuation to obtain more accurate PET images.

[0031] In PET / CT imaging, attenuation correction is typically achieved by fusing PET and CT data. CT data provides tissue density information, which can be used to calculate photon attenuation coefficients. These attenuation coefficients are then applied to the PET data to eliminate the attenuation effect of photons within the tissue.

[0032] However, the attenuation map (μ-map) derived from CT data has certain limitations. For example, high radiation dose, metal artifacts, beam hardening artifacts, truncation of large patients, and patient movement between PET / CT scans can all affect the derived results.

[0033] Existing techniques perform attenuation correction by jointly reconstructing attenuation maps and activity maps, a method that can directly extract attenuation coefficient information from radiometric data. First, maximum likelihood estimates (MLAA) of the attenuation and activity maps are calculated. Then, maximum likelihood expectation-maximization (MLEM) and maximum likelihood transmission computed tomography (MLTR) algorithms are used to iteratively reconstruct PET and attenuation images. Similar to MLAA, some studies have proposed maximum likelihood estimation (MLACF) of activity maps and attenuation correction coefficients, where the attenuation factor is estimated after each update of the activity image or at each update of the activity image.

[0034] A potential problem with such algorithms is that, on the one hand, MLAA or MLACF may converge to a local optimum if the initial values ​​are not good enough. On the other hand, MLAA and MLACF use the same set of radiometric data to estimate the activity map and attenuation map, and crosstalk issues may also affect the convergence speed and the quality of the estimated image.

[0035] To address these issues, some studies have used external rotating sources to reconstruct attenuation maps, either directly for attenuation correction or as initial values ​​for attenuation maps in MLAA. The disadvantages of external source scanning are that it requires additional equipment, increasing the complexity of system design and user operation, as well as increasing the radiation dose received by the patient.

[0036] In some embodiments of this specification, an attenuation correction method is provided. This method involves acquiring transmission data and radiation coincidence event data of a target object, then reconstructing the radiation image of the target object using attenuation correction data to obtain an attenuated radiation image. The transmission data includes backscattering coincidence event data of the target object. This method estimates and corrects attenuated images or attenuation factors without relying on CT data, and without increasing system complexity, scan time, or patient radiation dose.

[0037] Figure 1 This is a schematic diagram illustrating an application scenario of an attenuation correction system according to some embodiments of this specification.

[0038] like Figure 1 As shown, in some embodiments, the application scenario 100 of the attenuation correction system may include a scanning device 110, a processing device 120, a storage device 130, a terminal 140, and a network 150.

[0039] Scanning device 110 refers to a medical device that uses various media to reproduce images of the internal structures of the human body. In some embodiments, scanning device 110 can be any medical device that uses radionuclides to image or treat designated body parts of a patient, such as positron emission tomography (PET) equipment, computed tomography (CT) equipment, PET-CT equipment, etc. The scanning device 110 described above is for illustrative purposes only and is not intended to limit its scope. The detector in scanning device 110 can receive radiation from a radiation source and measure the received radiation. The detector consists of multiple detector units arranged in one or more ring structures. In some embodiments, scanning device 110 can send data and information related to the detector, such as the energy value of the radiation photons received by the detector, the output value of the detector, etc., to processing device 120. In some embodiments, scanning device 110 can acquire transmission data, radiometric coincidence event data of the scanned target object, etc., and send them to processing device 120. More information about transmission data, target objects, and radiometric coincidence event data can be found in [link to relevant documentation]. Figure 3 And related descriptions. In some embodiments, the scanning device 110 can receive instructions sent by a doctor through the terminal 140, and perform related operations according to the instructions, such as imaging. In some embodiments, the scanning device 110 can exchange data and / or information with other components in the system 100 (e.g., processing device 120, storage device 130, terminal 140) through the network 150. In some embodiments, the scanning device 110 can be directly connected to other components in the application scenario 100 of the attenuation correction system. In some embodiments, one or more components in the application scenario 100 of the attenuation correction system (e.g., processing device 120, storage device 130) can be included within the scanning device 110.

[0040] Processing device 120 can process data and / or information obtained from other devices or system components, and perform the methods for correcting scanned images shown in some embodiments of this specification based on this data, information, and / or processing results to accomplish one or more functions described in some embodiments of this specification. For example, processing device 120 can perform attenuation correction and reconstruction on the radiographic image of a target object based on transmission data and radiometric coincidence event data acquired by scanning device 110 to obtain an attenuated radiographic image. In some embodiments, processing device 120 can retrieve pre-stored data and / or information from storage device 130, such as transmission data, radiometric coincidence event data, various calculation formulas, etc., for use in executing the attenuation correction methods shown in some embodiments of this specification.

[0041] In some embodiments, the processing device 120 may include one or more sub-processing devices (e.g., a single-core processing device or a multi-core multi-chip processing device). By way of example only, the processing device 120 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), a graphics processing unit (GPU), a digital signal processor (DSP), a field-programmable gate array (FPGA), a microcontroller unit (MCU), a reduced instruction set computer (RISC), a microprocessor, or any combination thereof.

[0042] Storage device 130 can store data or information generated by other devices. In some embodiments, storage device 130 can store data and / or information acquired by scanning device 110, such as transmission data, radiometric coincidence event data, etc. Storage device 130 may include one or more storage components, each of which may be a separate device or part of other devices. Storage devices may be local or implemented via the cloud. In some embodiments, one or more components of system 100 (e.g., scanning device 110, processing device 120, terminal 140) may include their own storage components.

[0043] Terminal 140 can control the operation of scanning device 110. Doctors can issue operating instructions to scanning device 110 via terminal 140 to enable it to perform specified operations, such as irradiating and imaging a specified body part of the patient. In some embodiments, terminal 140 can instruct processing device 120 to perform attenuation correction methods as shown in some embodiments of this specification. In some embodiments, terminal 140 can receive attenuated corrected radiographic images from processing device 120, allowing doctors to accurately assess the patient's condition and perform effective and targeted examinations and / or treatments. In some embodiments, terminal 140 can be one or any combination of mobile device 140-1, tablet computer 140-2, laptop computer 140-3, desktop computer, or other devices with input and / or output functions.

[0044] Network 150 can connect the various components of the system and / or connect the system to external resources. Network 150 enables communication between the components and with other parts outside the system, facilitating the exchange of data and / or information. In some embodiments, one or more components in system 100 (e.g., scanning device 110, processing device 120, storage device 130, terminal 140) can send data and / or information to other components via network 150. In some embodiments, network 150 can be any one or more of a wired network or a wireless network.

[0045] It should be noted that the above description is provided for illustrative purposes only and is not intended to limit the scope of this specification. Various changes and modifications can be made by those skilled in the art based on the content of this specification. Features, structures, methods, and other features of the exemplary embodiments described herein can be combined in various ways to obtain other and / or alternative exemplary embodiments. For example, the processing device 120 may be based on a cloud computing platform, such as a public cloud, private cloud, community cloud, and hybrid cloud. However, these changes and modifications will not depart from the scope of this specification.

[0046] Figure 2 This is an exemplary schematic diagram of an attenuation correction system according to some embodiments of this specification.

[0047] In some embodiments, the attenuation correction system 200 may include a first acquisition module 210, a second acquisition module 220, and a reconstruction module 230.

[0048] In some embodiments, the first acquisition module 210 can be used to acquire transmission data.

[0049] In some embodiments, the second acquisition module 220 can be used to acquire radiation coincidence event data of the target object.

[0050] In some embodiments, the reconstruction module 230 can be used to reconstruct the radiation image of the target object based on transmission data and radiation coincidence event data, thereby obtaining an attenuation-corrected radiation image; wherein, the transmission data may include the backscatter coincidence event data of the target object.

[0051] For more information on transmission data, target objects, radiometric coincidence event data, radiographic images, attenuation correction, and backscatter coincidence event data, please refer to [link to relevant documentation]. Figure 3 , Figure 4 And its related descriptions.

[0052] It should be noted that the above description of the attenuation correction system and its modules is for convenience only and should not be construed as limiting this specification to the embodiments described. It is understood that those skilled in the art, after understanding the principle of the system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from this principle. In some embodiments, Figure 2 The first acquisition module 210, the second acquisition module 220, and the reconstruction module 230 disclosed herein can be different modules within a single system, or a single module can implement the functions of two or more of the aforementioned modules. For example, the modules can share a single storage module, or each module can have its own separate storage module. Such variations are all within the scope of protection of this specification.

[0053] Figure 3 This is an exemplary flowchart illustrating an attenuation correction method according to some embodiments of this specification. Figure 3 As shown, process 300 includes the following steps. In some embodiments, process 300 may be executed by processing device 120.

[0054] Step 310: Obtain transmission data.

[0055] Transmission data refers to data transmitted through the target object. Examples include backscattered coincidence event data and lutetium background event data of the target object. The target object refers to the object to be scanned, such as a living organism or a phantom. A living organism can be a human or animal, and a phantom can be of various materials and shapes, such as a water phantom, a gel phantom, a cylinder, or a cuboid.

[0056] Before a PET scan, a tracer needs to be introduced into the target body. During the PET scan, the tracer emits positrons. The target body naturally contains a large number of negatively charged electrons. Positrons have the same mass as electrons but opposite charge. When a positron collides with an electron, annihilation occurs (also known as an "annihilation event" or "coincidence event"). Annihilation produces two gamma photons (or radiation rays) with energies of 511 keV in opposite directions. The line connecting the two gamma photons is called the Line of Response (LOR).

[0057] In a PET detector, two 511 keV gamma rays interact with matter, producing the photoelectric effect and Compton scattering. The photoelectric effect occurs when a gamma ray interacts with an electron in the matter and transfers all of its energy to an electron, causing the electron to detach from the atom. Compton scattering occurs when a gamma ray interacts with an electron in the matter, but only a portion of its energy is transferred to the electron, and the gamma ray changes direction.

[0058] This application focuses on the physical process of Compton scattering of gamma rays in a PET detector. One or two gamma rays undergo Compton scattering in the first crystal. Figure 5 As shown by the dashed line, some energy is transferred to electrons, and the gamma ray undergoes backscattering (backscattering refers to the phenomenon where waves, particles, or signals are reflected back from the direction they originated), penetrating back into the target object. Ultimately, this gamma ray is detected by another crystal on the other side (such as...). Figure 5 (As shown by the solid line in the middle). Detecting backscattering events can form a transmission response line, which can be used for transmission image estimation.

[0059] Backscatter coincidence event data refers to data related to backscatter coincidence events. Examples include backscatter coincidence event counts and trajectories.

[0060] In some embodiments, the transmission data may further include lutetium background event data.

[0061] like Figure 6 As shown, common PET systems use LSO or LYSO crystals as scintillation crystals, which contain the isotope Lu-176, which can generate spontaneous background radiation.

[0062] Lutene background event data are coincidence event data generated by the spontaneous background radiation of lutetium from the crystal in a scanning device. Examples include the count and trajectory of lutetium background events.

[0063] In some embodiments, the processing device 120 can acquire transmission data through the scanning device 110. For example, the processing device 120 can collect the background radiation signal of the scanning device to obtain lutetium background event data. As another example, the processing device 120 can scan a target object through the scanning device 110 to obtain backscatter coincidence event data.

[0064] In some embodiments, the processing device 120 may acquire single-event data of a target object; determine whether the energy and arrival time of the single-event data conform to a first preset rule; and, in response to the single-event data conforming to the first preset rule, determine that the single-event data conforming to the first preset rule is transmission data.

[0065] Single-event data refers to data related to a single event. For example, single-event data can include counts, trajectories, etc., of multiple single events.

[0066] Processing device 120 can acquire single-event data by scanning device 110.

[0067] Time to arrival refers to the time it takes for a detector to detect a single event.

[0068] The processing device 120 can scan the energy and arrival time of a single event by scanning the device 110.

[0069] The first preset rule can be set based on experience or requirements. In some embodiments, the first preset rule may include: if the energies of two different single events in single event data are respectively within a first preset energy window and a second preset energy window, and the difference in arrival times of the two different single events is within a first preset time window; then the data corresponding to the two different single events belongs to transmission data.

[0070] Understandably, the energy and time of arrival of transmission data possess certain characteristics. Taking backscattered coincidence event data as an example, backscattered coincidence events are signal events reflected back from an object, and their arrival time is longer than that of directly propagated signal events. Therefore, by setting an appropriate time of arrival threshold, it is possible to distinguish between directly propagated signal events and backscattered coincidence events. Correspondingly, energy is lost during reflection, and the energy of backscattered coincidence events is usually weaker than that of directly propagated signal events. Therefore, by setting an appropriate energy threshold, backscattered coincidence events can be filtered out. The same principle applies to lutetium background event data.

[0071] The first preset energy window is the energy range used to determine whether subsequent single-event data is transmission data. The second preset energy window is the energy range used to determine whether earlier single-event data is transmission data. The first and second preset energy windows can be set based on experience or requirements.

[0072] The first preset time window refers to the preset time interval for distinguishing whether single event data is transmission data. The first preset time window can be set based on experience or needs.

[0073] In some embodiments, the processing device 120 may pre-set parameters in a first preset rule (a first preset energy window, a second preset energy window, a first preset time window, etc.) to compare single-event data with the first preset rule. If the single-event data conforms to the first preset rule, it is determined as transmission data. Different transmission data (e.g., backscattering coincidence event data, lutetium background event data, etc.) can be filtered out by setting different parameters in the first preset rule (a first preset energy window, a second preset energy window, a first preset time window, etc.).

[0074] For example, the processing device 120 can be set with a first preset energy window of 250keV-380keV, a second preset energy window of 140keV-250keV, and a first preset time window of theoretical arrival time ±3σ. The theoretical arrival time is the time it takes for a single event to reach the detector, obtained based on the ratio of the flight distance of a single event (the distance between the annihilation location of the single event and the detection location) to the speed of light. σ is the standard deviation of the Gaussian time distribution of the system, σ = FWHM / 2.355, where FWHM represents the full width at half maximum (FWHM) of the Gaussian function. Two... There are two different single events, with single event 2 occurring before single event 1. The energy of single event 1 is compared with the first preset energy window, the energy of single event 2 is compared with the second preset energy window, and the difference in arrival time between single event 1 and single event 2 is compared with the first preset time window. If the energy of single event 1 is within the first preset energy window, the energy of single event 2 is within the second preset energy window, and the difference in arrival time between single event 1 and single event 2 is within the first preset time window, then the data corresponding to single event 1 and single event 2 are determined to belong to the backscatter coincidence event data in the transmission data.

[0075] For example, the processing device 120 can set a first preset energy window of 0keV-1000keV, a second preset energy window of 100keV-350keV, and a first preset time window of theoretical arrival time ±3σ. In the single event data, two different single events are selected, with single event 4 occurring before single event 3. The energy of single event 3 is compared with the first preset energy window, the energy of single event 4 is compared with the second preset energy window, and the difference in arrival time between single event 3 and single event 4 is compared with the first preset time window. If the energy of single event 3 is within the first preset energy window, the energy of single event 4 is within the second preset energy window, and the difference in arrival time between single event 3 and single event 4 is within the first preset time window, then it is determined that the data corresponding to single event 3 and single event 4 belong to the lutetium background event data in the transmission data.

[0076] In some embodiments, the processing device 120 can simultaneously collect single-event data and apply it to the judgment of backscatter coincidence event data and lutetium background event data in the transmission data, or it can collect single-event data separately and apply it to the judgment of backscatter coincidence event data and lutetium background event data in the transmission data respectively.

[0077] In some embodiments of this specification, by acquiring single-event data of the target object and determining single-event data that conforms to the first preset rule as transmission data, the single-event data can be comprehensively screened from two dimensions: energy and arrival time, eliminating noise and interference signals, and improving the accuracy and reliability of projection data identification.

[0078] Step 320: Obtain radiation coincidence event data of the target object.

[0079] Radiometric coincidence event data refers to data related to radiometric coincidence events. For example, the count and trajectory of radiometric coincidence events of a target object. A radiometric coincidence event, also known as an electron-positron annihilation coincidence event, is an event in which an electron and a positron collide and annihilate to produce a pair of gamma photons within the target object.

[0080] In some embodiments, the processing device 120 may acquire radiation coincidence event data of a target object through the scanning device 110.

[0081] In some embodiments, the processing device 120 may acquire single-event data of a target object; determine whether the energy and arrival time of the single-event data conform to a second preset rule; and, in response to the single-event data conforming to the second preset rule, determine that the single-event data conforming to the second preset rule is radiometric coincidence event data. For more information regarding the target object, single-event data, energy, and arrival time, please refer to the foregoing description.

[0082] The second preset rule can be set based on experience or requirements. In some embodiments, the second preset rule may include: if the energy of two different single events in the single event data is within a third preset energy window, and the difference in arrival time of the two different single events is within a second preset time window; then the data corresponding to the two different single events belongs to radiometric coincidence event data.

[0083] The third preset energy window is the energy range used to determine whether two single events are radiometric coincidence events.

[0084] The second preset time window refers to the preset time interval for distinguishing whether a single event is a radiometric event.

[0085] In some embodiments, the third preset energy window and the second preset time window can be determined in various ways. For example, they can be preset based on experience or requirements. Alternatively, they can be set according to scanning device parameters. Scanning device parameters can refer to data information related to the scanning device, such as the axial length and energy resolution of the scanning device. The processing device 120 can obtain the third preset energy window and the second preset time window by looking up a table, which includes different scanning device parameters and their corresponding third preset energy windows and second preset time windows. The table can be obtained through presets, historical data, etc.

[0086] In some embodiments, the processing device 120 may preset parameters in the second preset rule (such as the third preset energy window and the second preset time window), compare the single event data with the second preset rule, and if the single event data conforms to the second preset rule, then determine it as radiation coincidence event data.

[0087] For example, the processing device 120 can set a third preset energy window of 425keV-800keV and a second preset time window of 4.4ns based on PET scanning equipment, etc. In the single event data, two different single events are selected, with single event 6 occurring before single event 5. The energy of single event 5 and the energy of single event 6 are compared with the third preset energy window, and the difference between the arrival times of single event 5 and single event 6 is compared with the second preset time window. If the energy of single event 5 and the energy of single event 6 are within the third preset energy window, and the difference between the arrival times of single event 5 and single event 6 is within the second preset time window, then it is determined that the data corresponding to single event 5 and single event 6 belong to radiometric coincidence event data.

[0088] In some embodiments, single-event data can be acquired simultaneously and differentiated through different preset energy windows and preset time windows to obtain transmission data and radiation coincidence event data. In some embodiments, the scanning device 110 can use an extended energy window for single-event acquisition. It is understood that the extended energy window has a large window size and can detect multiple types of events (e.g., lutetium background radiation events, object scattering events, intercrystalline scattering events, etc.). The parameters of the extended energy window can be set based on experience or requirements. For example, the parameters of the extended energy window can be: Low Level Discriminator (LLD): 100keV; High Level Discriminator (ULD): 1024keV.

[0089] In some embodiments of this specification, by acquiring single-event data of the target object and determining single-event data that conforms to the second preset rule as radiometric coincidence event data, the single-event data can be comprehensively screened from two dimensions: energy and arrival time, eliminating noise and interference signals, thereby improving the accuracy and reliability of radiometric coincidence event data identification.

[0090] Step 330: Based on the transmission data and radiation coincidence event data, the radiation image of the target object is reconstructed by attenuation correction to obtain the attenuated radiation image.

[0091] Radiographic images refer to images obtained through medical radiology techniques used for the diagnosis and evaluation of diseases. Examples include PET images.

[0092] Attenuation correction refers to correcting errors in medical images caused by photon attenuation.

[0093] Understandably, during the imaging process of radiographic imaging, emitted positrons interact with surrounding tissues to produce photons. These photons are attenuated to varying degrees as they pass through human tissues, thus requiring correction for this attenuation to obtain a more accurate radiographic image. Attenuation correction can eliminate the attenuation effect of different tissues on photons, thereby obtaining a more accurate radiographic image.

[0094] In some embodiments, the processing device can reconstruct the attenuation-corrected radiographic image of the target object based on transmission data and radiometric coincidence event data using a preset attenuation correction method, thereby obtaining an attenuation-corrected radiographic image. The preset attenuation correction method can be set based on experience or requirements.

[0095] In some embodiments, the processing device 120 may initialize the attenuation image to obtain an initial attenuation image; initialize the radiation image to obtain an initial radiation image; and iteratively reconstruct the radiation image after attenuation correction based on the initial attenuation image, the initial radiation image, transmission data, and radiation coincidence event data.

[0096] A decay image is an image that reflects the decay characteristics of a target object. An initial decay image is the initially obtained decay image.

[0097] In some embodiments, the processing device 120 may assign an average value to each pixel value in a preset image (e.g., a mask image) to initialize the attenuation image and obtain an initial attenuation image. The average value may be preset based on experience or requirements. For example, the processing device 120 may assign a water attenuation number to each pixel value in the preset image to initialize the attenuation image and obtain an initial attenuation image.

[0098] In some embodiments, the processing device 120 may determine the boundary of a target object in a preset image based on transmission data, and then assign an average value to each pixel value within the boundary. For example, the processing device 120 may determine multiple data points associated with the boundary based on transmission data, and then assign a water attenuation coefficient to each pixel value within the boundary.

[0099] The initial radiographic image refers to the initially obtained radiographic image. More information about radiographic images can be found in the aforementioned descriptions.

[0100] In some embodiments, the processing device 120 may assign an average value to each pixel value in a preset image to initialize the radiometric image and obtain an initial radiometric image. The average value may be preset based on experience or requirements. In some embodiments, the processing device 120 may determine the boundary of the target object in the preset image based on radiometric coincidence event data, and then assign an average value to each pixel value within the boundary. For specific details, please refer to the aforementioned content on attenuation image initialization.

[0101] In some embodiments, the processing device 120 can perform iterative reconstruction based on an initial attenuation image, an initial radiation image, transmission data, and radiation coincidence event data using a preset algorithm to obtain an attenuation-corrected radiation image. The preset algorithm can be based on experience or requirements; for example, the preset algorithm may include the Monte Carlo method, etc.

[0102] Iteration refers to a process of repeated rounds, in which at least a portion of the output of each round is used as a portion of the input for the next round.

[0103] For example, in iterative reconstruction of attenuation-corrected radiometric images, initial attenuation and radiometric images are first obtained based on the attenuation and radiometric images, serving as the iterative input for the first iteration. In each iteration, parametric analysis is performed on the iterative input to reconstruct iterative attenuation and radiometric images, which can then be used to update the iterative input for the next iteration. For detailed instructions on iterative operations, please refer to [link to instructions]. Figure 4 Related content.

[0104] In some embodiments of this specification, by acquiring transmission data and radiation coincidence event data, attenuation correction and reconstruction are performed on the radiation image of the target object to obtain an attenuated radiation image. This allows for the acquisition of an accurate attenuated radiation image without the aid of CT images, avoiding the influence of artifacts and other errors in CT images on the correction results. Furthermore, this process does not increase system complexity, scan time, or patient radiation dose, taking into account both system design and user operation convenience, and avoiding any impact on the patient's health.

[0105] Figure 4 This is an exemplary schematic diagram illustrating the acquisition of radiation coincidence event data of a target object according to some embodiments of this specification.

[0106] In some embodiments, the iteration includes: obtaining a backscattering estimate 461, a backscattering blank scan estimate 463, and a radiation estimate 472 based on the attenuation image 430 and the radiation image 440 of the previous iteration; the attenuation image of the first iteration is the initial attenuation image 410, and the radiation image of the first iteration is the initial radiation image 420; obtaining an attenuation image 470 of the current iteration based on the backscattering estimate 461, the backscattering blank scan estimate 463, and the transmission data 464; obtaining a radiation image 480 of the current iteration based on the attenuation image 470, the radiation scattering estimate 472, and the radiation coincidence event data 471; determining whether the iteration termination condition 490 is met; if not, proceeding to the next iteration; if so, determining the radiation image 480 of the current iteration as the attenuation-corrected radiation image 4100.

[0107] Backscattering estimation 461 refers to the estimation of the distribution of scattering events present in backscattering coincidence event data.

[0108] Scan data refers to the data acquired in real time by the scanning equipment, used to reconstruct the attenuation-corrected radiographic image. Examples include the count of all events obtained while scanning the target object.

[0109] Blank scan estimation of backscattering 463 refers to the estimation of the distribution of backscattering events in the case that there is no target object during the backscattering process.

[0110] The scattering estimation of radiation 472 refers to the estimation of the distribution of coincidence events present in the scan data of the target object.

[0111] The backscattering estimation 461, the blank scan estimation of backscattering 463, and the scattering estimation of radiation 472 are represented in chord diagram form.

[0112] In some embodiments, the processing device 120 may obtain a backscattering estimate 461 based on the attenuation image 430 and the emission image 440 from the previous iteration using a preset algorithm. The preset algorithm may be based on experience or requirements; for example, the preset algorithm may include the Monte Carlo method, etc.

[0113] In some embodiments, the processing device 120 may process the attenuation image 430 and the radiation image 440 from the previous iteration using a first processing method 451 to obtain a backscattering estimate 461 and a radiation estimate 472; and process the attenuation image 430 and the radiation image 440 from the previous iteration using a second processing method 452 to obtain a blank scan estimate 463 for backscattering; the second processing method 452 includes at least one of the Monte Carlo method and the lookup table method.

[0114] The first processing method 451 refers to the processing method used to obtain the scattering estimate. In some embodiments, the first processing method 451 may include the Monte Carlo method, the conventional single scattering simulation (SSS) method, the energy-based scattering estimation (EBS) method, etc.

[0115] The second processing method 452 refers to a processing method for obtaining a blank scan estimate. In some embodiments, the second processing method 452 may include at least one of a Monte Carlo method and a lookup table method.

[0116] A lookup table is a data table that reflects the probability distribution of backscattering occurring on a response line. In some embodiments, the lookup table includes the probability distribution of backscattering events on each response line being detected on the remaining response lines. More information about response lines can be found at [link to relevant documentation]. Figure 3 And its related descriptions.

[0117] A lookup table can be represented as a matrix. For example, if there are M response lines, each corresponding to an M*1 chord graph, and the chord graph reflects the probability distribution of backscattering events on one response line being detected on the other response lines, then the lookup table is an M*M matrix containing M M*1 chord graphs. M is an integer.

[0118] In some embodiments, the lookup table method of processing device 120 may obtain a lookup table; simplify the lookup table based on the symmetry and / or merging of response lines of the positron emission tomography (PET) system; and determine a blank scan estimate 463 for backscattering based on the simplified lookup table and scan data.

[0119] In some embodiments, the processing device 120 can obtain a lookup table using a physical model, Monte Carlo method, or other mathematical modeling techniques. For example, the processing device 120 can simulate all probabilities of an emission event incident along a certain response line direction being detected by other response lines using a physical model (model parameters need to be set independently according to the actual scenario), Monte Carlo method, etc., fill them as a column of data in the lookup table, and traverse all response lines to construct the lookup table.

[0120] Understandably, positron emission tomography (PET) systems possess symmetry, which can include the symmetry of the detector's cross-sectional reflections (e.g., Figure 7 As shown in (a), the cross-section is rotationally symmetric (as shown in the middle). Figure 7 As shown in (b)), axially parallel and symmetrical (as shown in...) Figure 7 As shown in (c), axial reflection symmetry (as shown in...) Figure 7 (as shown in d).

[0121] In some embodiments, the processing device 120 can, based on the symmetry of the positron emission tomography (PET) system, retain only the data of any one response line (i.e., the probability distribution data of backscattering events on the response line being detected on the other response lines) in a lookup table among multiple response lines with symmetrical relationships, and delete the data of other response lines, thereby simplifying the lookup table.

[0122] Response lines can be merged by merging the detection units of the corresponding detectors. For example, response lines can be merged by merging four adjacent detection units, that is, merging the response lines detected by four adjacent detection units into one. Specific merging rules can be preset based on experience or requirements.

[0123] In some embodiments, the processing device 120 may merge multiple response lines into one response line based on the merging of response lines, and retain only the data of that response line in the lookup table, thereby simplifying the lookup table.

[0124] In some embodiments, the processing device 120 may calculate and determine a blank scan estimate 463 for backscattering based on a simplified lookup table and scan data. For example, the processing device 120 may calculate the sum of the product of the event count on each response line in the scan data and the probability distribution of the corresponding response line on other response lines in the simplified lookup table (i.e., the chord graph of the aforementioned response lines) to determine the blank scan estimate for backscattering.

[0125] In some embodiments of this specification, by constructing and simplifying a lookup table, the blank scan estimate 463 of backscattering is determined. The probability distribution of backscattering of events on the response line being detected on the other response lines can be obtained by simulation, thereby obtaining an accurate blank scan estimate of backscattering.

[0126] In some embodiments of this specification, the attenuation image 430 and the radiation image 440 from the previous iteration are processed by the first processing method 451 and the second processing method 452 to obtain the backscattering estimate 461, the radiation scattering estimate 472, and the backscattering blank scan estimate 463. This makes the determination process of the scattering estimate and the blank scan estimate efficient, accurate, and convenient, and facilitates the subsequent updating and reconstruction of the corresponding images.

[0127] In some embodiments, the processing device 120 may obtain the attenuation image 470 of the current iteration based on the backscattering estimation 461, the backscattering blank scan estimation 463, and the transmission data 464.

[0128] In some embodiments, such as Figure 8As shown in (a), when iterating the attenuation image based solely on the backscatter coincidence event data in the transmission data, the attenuation image can be iteratively calculated based on formula (1):

[0129] in, This represents the decay image for this iteration. This represents the decay image from the previous iteration. The blank scan estimate represents the backscattering, where H represents the system matrix, and y bs This indicates backscattering events in transmission data. The scattering estimate, r, represents the backscattering. bs This represents the random event estimation of backscattering. Random event estimation refers to the estimation of the distribution of random events present in backscattering coincidence event data, which can be obtained through methods such as the Delay Window Method and the Singles Rate. k represents the current iteration number.

[0130] In some embodiments, such as Figure 8 As shown in (b), when iterating the attenuation image based solely on lutetium background event data from the transmission data, the attenuation image can be iteratively calculated using formula (2):

[0131] in, This represents the decay image for this iteration. B represents the decay image from the previous iteration. Lu The blank scan represents the background event of lutetium, H represents the system matrix, and y Lu This indicates the lutetium background event in the transmission data. This represents the scattering estimation of lutetium background events. The scattering estimation of lutetium background events refers to the estimation of the distribution of scattering events present in lutetium background event data. r Lu This represents the random event estimation of the lutetium background event. Random event estimation refers to the estimation of the distribution of random events present in the lutetium background event data, which can be obtained through methods such as the Delay Window Method and the Singles Rate. k represents the current iteration number. Blank scans of the lutetium background events can be obtained using a scanning device 110 for air scanning. Air scanning refers to scanning directly on the air without any target objects such as humans or phantoms; in this case, the target object can be considered as air.

[0132] In some embodiments, such as Figure 8As shown in (c), when iterating the attenuation image based on the backscatter coincidence event data and lutetium background event data in the transmission data, the attenuation image can be iteratively calculated based on formula (3):

[0133] in, This represents the decay image for this iteration. This represents the decay image from the previous iteration. y all =y bs +y Lu , r all =r bs +r Lu .

[0134] In some embodiments, the processing device 120 can obtain the radiation image 480 of the current iteration based on the attenuation image 470, the radiation scattering estimate 472, and the radiation coincidence event data 471 of the current iteration. In some embodiments, the radiation image can be iteratively calculated based on formula (4):

[0135] Where, λ k+1 λ represents the radial image of this iteration. k Showing the radiographic image from the previous iteration, y emission This represents the radiometric coincidence event data, ss represents the scattering estimate of the radiometric event, which refers to the distribution estimate of the scattering events present in the radiometric coincidence event data, and rr represents the random event estimate of the radiometric event, which refers to the distribution estimate of the random events present in the radiometric coincidence event data, and can be obtained through methods such as the Delay Window Method and the Singles Rate. for or or

[0136] The iteration can stop and attenuation correction can end once the preset iteration conditions are met. These preset iteration conditions can include iteration convergence, reaching a pre-specified number of iterations, the difference between the radiographic images in two adjacent iterations being less than a certain threshold, and the difference between the attenuation effect chordograms in two adjacent iterations being less than a certain threshold. The attenuation effect chordogram refers to the forward projection of the attenuated image.

[0137] The attenuation-corrected radiographic image 4100 refers to the radiographic image after attenuation correction, which is the radiographic image output in the last iteration.

[0138] In some embodiments of this specification, backscattering estimation, backscattering blank scan estimation, and radiation estimation are obtained based on the attenuation image and radiation image of the previous iteration; then the attenuation image and radiation image of the current iteration are obtained; the iteration ends after the iteration termination condition is met. The attenuation image and radiation image can be updated and reconstructed based on real-time data, making the attenuation correction process more accurate and efficient.

[0139] Figure 9A This is an exemplary flowchart illustrating the determination of attenuation-corrected radiographic images according to some embodiments of this specification. Figure 9A As shown, process 900A includes the following steps. In some embodiments, process 900A may be executed by processing device 120.

[0140] Step 910A: Acquire backscatter coincidence event data. In some embodiments, the processing device 120 may acquire backscatter coincidence event data through various means such as the scanning device 110. For more information on how to acquire backscatter coincidence event data, please refer to the relevant description of step 310.

[0141] Step 920A: Initialize the attenuation image to obtain an initial attenuation image. For more information on how to initialize the attenuation image, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0142] Step 930A: Acquire radiation coincidence event data. In some embodiments, the processing device 120 may acquire radiation coincidence event data through various means such as the scanning device 110. For more information on how to acquire radiation coincidence event data, please refer to the relevant description of step 320.

[0143] Step 940A: Initialize the radiographic image and obtain an initial radiographic image. For more information on how to initialize a radiographic image, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0144] Step 950A: Obtain the backscattering estimate and the blank scan estimate of the backscattering. In some embodiments, the processing device 120 can obtain the backscattering estimate by processing the attenuation image and the radiation image from the previous iteration using a first processing method; and obtain the blank scan estimate of the backscattering by processing the attenuation image and the radiation image from the previous iteration using a second processing method. For details, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0145] Step 960A: Update the attenuation image. In some embodiments, the processing device 120 can obtain the attenuation image for the current iteration based on the backscattering estimation, the blank scan estimation of backscattering, and the transmission data. For details, please refer to... Figure 4 Related descriptions.

[0146] Step 970A: Obtain the scattering estimate of the radiation. In some embodiments, the processing device 120 can obtain the scattering estimate of the radiation by processing the attenuation image and the radiation image from the previous iteration using a first processing method. For details, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0147] Step 980A: Update the radiation image. In some embodiments, the processing device 120 can obtain the radiation image for the current iteration based on the attenuation image, radiation scattering estimation, and radiation coincidence event data. For details, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0148] Step 990A: Determine if the iteration termination condition is met. For more information on iteration termination conditions and their determination, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0149] Step 9100A: If yes, determine the attenuation-corrected radiographic image; if no, repeat steps 950A-990A. For more information on the attenuation-corrected radiographic image and its determination, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0150] Figure 9B This is an exemplary flowchart illustrating the determination of attenuation-corrected radiographic images according to other embodiments of this specification. Figure 9B As shown, process 900B includes the following steps. In some embodiments, process 900B may be executed by processing device 120.

[0151] Step 910B: Acquire lutetium background event data. In some embodiments, the processing device 120 may acquire lutetium background event data through various means such as the scanning device 110. For more information on how to acquire lutetium background event data, please refer to the relevant description of step 310.

[0152] Step 920B: Initialize the attenuation image to obtain an initial attenuation image. For more information on how to initialize the attenuation image, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0153] Step 930B: Acquire radiation coincidence event data. In some embodiments, the processing device 120 may acquire radiation coincidence event data through various means such as the scanning device 110. For more information on how to acquire radiation coincidence event data, please refer to the relevant description of step 320.

[0154] Step 940B: Initialize the radiographic image and obtain an initial radiographic image. For more information on how to initialize a radiographic image, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0155] Step 950B: Obtain the scattering estimate of the lutetium background event. In some embodiments, the processing device 120 can obtain the scattering estimate of the lutetium background event by processing the attenuation image and the radiation image from the previous iteration using a first processing method. Specific details can be found in [reference needed]. Figure 4 This section describes the relevant information for obtaining backscattering estimates.

[0156] Step 960B: Obtain a blank scan of the lutetium background event. In some embodiments, the processing device 120 may obtain a blank scan of the lutetium background event through various methods such as the scanning device 110; for details, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0157] Step 970B: Update the attenuation image. In some embodiments, the processing device 120 can obtain the attenuation image for the current iteration based on the scattering estimation of the lutetium background event, the blank scan of the lutetium background event, and the transmission data. For details, please refer to... Figure 4 Related descriptions.

[0158] Step 980B: Obtain the scattering estimate of the radiation. In some embodiments, the processing device 120 can obtain the scattering estimate of the radiation by processing the attenuation image and the radiation image from the previous iteration using a first processing method. For details, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0159] Step 990B: Update the radiation image. In some embodiments, the processing device 120 can obtain the radiation image for the current iteration based on the attenuation image, radiation scattering estimation, and radiation coincidence event data. For details, please refer to... Figure 4 Related descriptions.

[0160] Step 9100B: Determine if the iteration termination condition is met. For more information on iteration termination conditions and their determination, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0161] Step 9110B: If yes, determine the attenuation-corrected radiographic image; if no, repeat steps 950B-9100B. For more information on the attenuation-corrected radiographic image and its determination, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0162] Figure 9C This is an exemplary flowchart illustrating the determination of attenuation-corrected radiographic images according to some embodiments of this specification. Figure 9C As shown, process 900C includes the following steps. In some embodiments, process 900C may be executed by processing device 120.

[0163] Step 910C: Obtain backscatter coincidence event data and lutetium background event data. For more information on how to obtain backscatter coincidence event data and lutetium background event data, please refer to [link to relevant documentation]. Figure 9A , Figure 9B Related descriptions.

[0164] Step 920C: Initialize the attenuation image to obtain an initial attenuation image. For more information on how to initialize the attenuation image, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0165] Step 930C: Acquire radiation coincidence event data. In some embodiments, the processing device 120 may acquire radiation coincidence event data through various means such as the scanning device 110. For more information on how to acquire radiation coincidence event data, please refer to the relevant description of step 320.

[0166] Step 940C: Initialize the radiographic image and obtain an initial radiographic image. For more information on how to initialize a radiographic image, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0167] Step 950C: Obtain the backscattering estimate, the lutetium background event scattering estimate, and the blank scan estimate of the backscattering. For details, please refer to [link to relevant documentation]. Figure 9A , Figure 9B Related descriptions.

[0168] Step 960C: Obtain a blank scan of the lutetium background event. In some embodiments, the processing device 120 can obtain a blank scan of the lutetium background event through various methods such as the scanning device 110; for details, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0169] Step 970C: Update the attenuation image. In some embodiments, the processing device 120 can obtain the attenuation image for the current iteration based on backscattering estimation, lutetium background event scattering estimation, backscattering blank scan estimation, lutetium background event blank scan, and transmission data. For details, please refer to... Figure 4 Related descriptions.

[0170] Step 980C: Obtain the scattering estimate of the radiation. In some embodiments, the processing device 120 can obtain the scattering estimate of the radiation based on the attenuation image and the radiation image from the previous iteration using a first processing method. For details, please refer to... Figure 4 Related descriptions.

[0171] Step 990C: Update the radiation image. In some embodiments, the processing device 120 can obtain the radiation image for the current iteration based on the attenuation image, radiation scattering estimation, and radiation coincidence event data. For details, please refer to... Figure 4 Related descriptions.

[0172] Step 9100C: Determine if the iteration termination condition is met. For more information on iteration termination conditions and their determination, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0173] Step 9110C: If yes, determine the attenuation-corrected radiographic image; if no, repeat steps 950C-9100C. For more information on the attenuation-corrected radiographic image and its determination, please refer to [link to relevant documentation]. Figure 4 Related descriptions.

[0174] This specification also provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions from the storage medium, the computer executes the attenuation correction method as described in any of the above embodiments.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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. An attenuation correction method, characterized in that, The method includes: Acquire transmission data; Obtain radiation coincidence event data of the target object; Based on the transmission data and the radiation coincidence event data, the radiation image of the target object is reconstructed by attenuation correction to obtain the attenuated radiation image; wherein, the transmission data includes the backscattering coincidence event data of the target object.

2. The method according to claim 1, characterized in that, The acquisition of transmission data includes: Obtain single-event data of the target object; Determine whether the energy and arrival time of the single event data conform to the first preset rule; In response to the single event data conforming to the first preset rule, the single event data conforming to the first preset rule is determined to be the transmission data.

3. The method according to claim 1, characterized in that, The acquisition of radiation coincidence event data of the target object includes: Obtain single-event data of the target object; Determine whether the energy and arrival time of the single event data conform to the second preset rule; In response to the single event data conforming to the second preset rule, the single event data conforming to the second preset rule is determined to be the radiation conformity event data.

4. The method according to claim 1, characterized in that, The attenuation-corrected and reconstructed radiation image of the target object based on the transmission data and the radiation coincidence event data, to obtain the attenuation-corrected radiation image, includes: Perform attenuation image initialization to obtain the initial attenuation image; Perform radiographic image initialization to obtain the initial radiographic image; Based on the initial attenuation image, the initial radiation image, the transmission data, and the radiation coincidence event data, the radiation image after attenuation correction is obtained through iterative reconstruction.

5. The method according to claim 4, characterized in that, The iteration includes: Based on the attenuation image and the radiation image from the previous iteration, the backscattering estimation, the blank scan estimation of the backscattering, and the radiation scattering estimation are obtained; the attenuation image from the first iteration is the initial attenuation image, and the radiation image from the first iteration is the initial radiation image. Based on the backscattering estimation, the blank scan estimation of the backscattering, and the transmission data, the attenuation image for this iteration is obtained; Based on the attenuation image of this iteration, the scattering estimate of the radiation, and the radiation coincidence event data, the radiation image of this iteration is obtained; Determine whether the iteration termination condition is met. If not, proceed to the next iteration. If so, determine the radiographic image of this iteration as the attenuation-corrected radiographic image.

6. The method according to claim 5, characterized in that, The backscattering estimate, the blank scan estimate of the backscattering, and the scattering estimate of the radiation obtained based on the attenuation image and the radiation image from the previous iteration include: Based on the attenuation image and the radiation image from the previous iteration, the images are processed using the first processing method to obtain the backscattering estimate and the radiation scattering estimate. Based on the attenuation image and the radiation image from the previous iteration, the backscattering blank scan estimate is obtained by processing using a second processing method; the second processing method includes at least one of the Monte Carlo method and the lookup table method.

7. The method according to claim 6, characterized in that, The backscattering coincidence event data is acquired by a positron emission tomography (PET) system. The lookup table includes the probability distribution of backscattering events occurring on each response line of the PET system being detected on the remaining response lines. The lookup table method includes: Obtain the lookup table; simplify the lookup table based on the symmetry of the positron emission tomography (PET) system and / or the merging of the response lines; Based on the simplified lookup table and scan data, the blank scan estimate of the backscattering is determined.

8. The method according to claim 1, characterized in that, The transmission data further includes lutetium background event data.

9. An attenuation correction system, characterized in that, The system is used to implement the attenuation correction method, and the system includes: The first acquisition module is used to acquire transmission data; The second acquisition module is used to acquire radiation coincidence event data of the target object; The reconstruction module is used to reconstruct the radiation image of the target object by performing attenuation correction based on the transmission data and the radiation coincidence event data, so as to obtain the attenuation-corrected radiation image; wherein the transmission data includes the backscatter coincidence event data of the target object.

10. A computer-readable storage medium storing computer instructions, wherein when a computer reads the computer instructions in the storage medium, the computer executes the attenuation correction method as described in claim 1.

Images