A multi-nuclide imaging method and device based on image domain separation

Abstract

The present invention discloses a multi-nuclide imaging method based on image domain separation, comprising: obtaining the original data of multi-nuclide gamma photons; wherein the multi-nuclide includes a pure positron nuclide and several different impure positron nuclides; processing the original data of the multi-nuclide gamma photons using the three-coincidence technology to obtain a set of double-coincidence data and several sets of three-coincidence data of impure positron nuclides; performing low-dose imaging on the annihilation photon data in the three-coincidence data of several sets of impure positron nuclides respectively, and obtaining several corresponding impure positron nuclide distribution maps; performing image reconstruction on the double-coincidence data to obtain a mixed distribution map of multiple nuclides, and using the mixed distribution map to sequentially separate and process several impure positron nuclide distribution maps, and obtaining corresponding pure positron nuclide distribution maps. The defect that conventional PET cannot distinguish between pure positron nuclides and impure positron nuclides that produce instantaneous photons with a lower probability is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of biomedical imaging, and in particular relates to a multi-nuclide imaging method and device based on image domain separation. Background Art

[0002] PET (Positron Emission Tomography) is a non-invasive in vivo functional imaging technology that can obtain biological function and molecular imaging information using radionuclide labeling. This technology plays an increasingly important role in life science research. 18 F-FDG PET imaging, but 18 F-FDG can only image glucose metabolism, providing only a single piece of information, and failing to fully realize the potential of PET. If multiple radionuclides can be used to simultaneously label and image organisms / tumors, the functional morphology of organisms can be described in many aspects, giving PET imaging a broad application prospect.

[0003] Currently, PET imaging mainly detects positrons (β + ) are produced after the annihilation of a pair of gamma photons with the same energy (511 keV) and opposite movement directions for imaging, but the gamma photons produced by the positron decay of different isotopes have no difference in energy, so different radionuclide markers cannot be distinguished.

[0004] In addition, the isotopes commonly used in PET imaging can be divided into two categories according to the differences in their positron emission processes: the first category is pure positron-emitting isotopes, and the other category is impure positron-emitting isotopes. The first category of isotopes emits only one positron (β + ), the positron combines with the electrons in the surrounding matter and annihilates to produce a pair of gamma photons (γ) with the same energy (511keV) and opposite directions. 18 F belongs to this type of isotope. When the second type of impure positron-emitting isotopes undergo positron decay, in addition to emitting a positron, they also produce a single gamma photon. The time difference between the two is only on the order of picoseconds (ps), so this gamma photon is called a prompt gamma photon. The time coincidence mechanism of conventional PET systems assumes that each positron decay produces only two gamma photons. If three gamma photons are detected at the same time, they cannot be effectively identified, and may even cause imaging artifacts, thereby reducing the quality of PET reconstructed images.

[0005] In summary, existing PET imaging methods are difficult to image multiple radioactive isotopes simultaneously, and cannot distinguish between pure positron nuclides and impure positron nuclides, which limits the application of PET imaging technology. In order to conveniently and quickly achieve simultaneous imaging of multiple nuclides, it is urgent to explore new imaging and nuclide separation technologies. Summary of the invention

[0006] In order to solve the above problems existing in the prior art, the present invention provides a multi-nuclide imaging method based on image domain separation. The technical problem to be solved by the present invention is achieved by the following technical solutions:

[0007] In a first aspect, the present invention provides a multi-nuclide imaging method based on image domain separation, comprising:

[0008] S1: Acquiring raw data of multi-nuclide gamma photons; wherein the multi-nuclide includes a pure positron nuclide and several different impure positron nuclides;

[0009] S2: Processing the raw data of the multi-nuclide gamma photons using a triple coincidence technique to obtain a set of double coincidence data and several sets of triple coincidence data of impure positron nuclides;

[0010] S3: performing low-dose imaging on the annihilation photon data in the three-coincidence data of the plurality of groups of impure positron nuclides respectively, and obtaining a plurality of corresponding impure positron nuclide distribution maps;

[0011] S4: reconstructing the double coincidence data to obtain a mixed distribution map of multiple nuclides, and using the mixed distribution map to sequentially separate the plurality of impure positron nuclide distribution maps to obtain a corresponding pure positron nuclide distribution map.

[0012] In one embodiment of the present invention, step S2 comprises:

[0013] S21: sorting the raw data of the multi-nuclide gamma photons according to the photon arrival time;

[0014] S22: extracting double coincidence events and triple coincidence events from the sorted data;

[0015] S23: using a conventional positron energy window to remove part of the scattered data in the double coincidence event to obtain double coincidence data;

[0016] S24: using a conventional positron energy window to remove part of the scattered data in the triple coincidence event, and using different energy windows to perform secondary filtering on the remaining data according to the type of the impure positron nuclide, to obtain several groups of triple coincidence data of the impure positron nuclide.

[0017] In one embodiment of the present invention, step S22 includes:

[0018] A time window is set. For each photon event, if there is only one other gamma photon event within the time window, the two events are stored as a double coincidence event; if there are only two other gamma photon events within the time window, the three events are stored as a triple coincidence event.

[0019] In one embodiment of the present invention, step S23 includes:

[0020] The double coincidence events are filtered using a conventional positron energy window, data with both photon energies within the conventional positron energy window are retained, and other unsatisfactory data are discarded to obtain double coincidence data.

[0021] In one embodiment of the present invention, step S24 includes:

[0022] S24-1: Filter the three coincidence events using a conventional positron energy window, retain data with at least two photon energies within the conventional positron energy window, and remove other data that do not meet the requirements;

[0023] S24-2: According to the instantaneous photon energy of different impure positron nuclides, multiple specific energy windows near the energy are set; for the remaining data obtained in step S24-1, different specific energy windows are used for secondary filtering and classification, and the three-coincidence data with only one gamma photon energy satisfying a specific energy window are retained, and other data are eliminated, and the three-coincidence data satisfying the same specific energy window are classified into one category to obtain several groups of three-coincidence data of impure positron nuclides; among them, the gamma photons satisfying the specific energy window are considered to be instantaneous photons, and the remaining two photons are annihilation photons.

[0024] In one embodiment of the present invention, step S3 includes:

[0025] S31: Using image domain non-negative constraints and image gradient sparsity constraints, an unconstrained optimization model for low-dose imaging is constructed;

[0026] S32: using the annihilation photon data in the three-coincidence data of several groups of impure positron nuclides as input data of the unconstrained optimization model, introducing auxiliary variables, decomposing the optimization problem into multiple sub-problems, and iteratively solving the sub-problems in turn to obtain low-noise imaging results of several impure positron nuclides;

[0027] S33: performing image filtering and post-processing on the above imaging results to obtain a plurality of non-pure positron nuclide distribution maps.

[0028] In one embodiment of the present invention, in step S31, the expression of the unconstrained optimization model of low-dose imaging is:

[0029]

[0030] Where f represents the image to be reconstructed, g(f) is the data fidelity term of the objective function, represents the non-negative constraint in the image domain, R(f) is the 3D directional gradient L0 norm regularization term, expressed as and represents the directional gradient of the reconstructed image, ‖·‖0 represents the L0 norm, and ρ1, ρ2, and ρ3 represent the regularization strengths of different gradient directions.

[0031] In a second aspect, the present invention provides a multi-nuclide imaging device based on image domain separation, comprising:

[0032] A data acquisition module, used to acquire raw data of multi-nuclide gamma photons; wherein the multi-nuclide includes a pure positron nuclide and several different impure positron nuclides;

[0033] A coincidence extraction module is used to process the raw data of the multi-nuclide gamma photons using a three-coincidence technique to obtain a set of double-coincidence data and several sets of three-coincidence data of impure positron nuclides;

[0034] A low-dose imaging module is used to perform low-dose imaging on the annihilation photon data in the three-coincidence data of the plurality of groups of impure positron nuclides, and obtain a plurality of corresponding distribution maps of the impure positron nuclides;

[0035] The image reconstruction module is used to reconstruct the image of the double coincidence data to obtain a mixed distribution map of multiple nuclides, and use the mixed distribution map to sequentially separate the plurality of impure positron nuclide distribution maps to obtain a corresponding pure positron nuclide distribution map.

[0036] In a third aspect, the present invention provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0037] Memory, used to store computer programs;

[0038] The processor is used to implement the method steps described in the above embodiment when executing the program stored in the memory.

[0039] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps described in the above embodiments are implemented.

[0040] Beneficial effects of the present invention:

[0041] 1. The multi-nuclide imaging method based on image domain separation provided by the present invention retains the three-coincidence data for multi-nuclide imaging with low probability of instantaneous photons, extracts energy information and classifies the annihilation photon data in the three-coincidence data, and realizes low-noise imaging of impure positron nuclides using a low-dose reconstruction algorithm. Finally, the image domain separation method is used to realize simultaneous imaging and separation of multiple nuclides, which solves the defect that conventional PET cannot distinguish between pure positron nuclides and impure positron nuclides that produce instantaneous photons with a lower probability, and can realize simultaneous imaging of multiple radioactive isotopes, so that PET imaging technology has a broader application prospect;

[0042] 2. The present invention utilizes a low-dose reconstruction algorithm with sparse constraints of directional gradients in the image domain to achieve high signal-to-noise ratio imaging of non-pure positron nuclides; at the same time, due to the use of the 3D directional gradient L0 norm as a regularization term, the edge information of the nuclide distribution in the image is greatly protected, which is conducive to the localization of tumors that absorb non-pure positron nuclides.

[0043] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flow chart of a multi-nuclide imaging method based on image domain separation provided by an embodiment of the present invention;

[0045] Figure 2 is a detailed flow chart of the dual-nuclide imaging method provided by an embodiment of the present invention;

[0046] Figure 3 The embodiment of the present invention provides 18 F and 68 Schematic diagram of Ga binucleide mimic;

[0047] Figure 4 It is a binuclear separation imaging diagram obtained by using the imaging method of the present invention;

[0048] Figure 5 This is the reconstruction result image obtained by conventional PET imaging method;

[0049] Figure 6 It is a structural schematic diagram of a multi-nuclide imaging device based on image domain separation provided by an embodiment of the present invention;

[0050] Figure 7 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention;

[0051] Figure 8 It is a schematic diagram of the structure of a computer-readable storage medium provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0053] Embodiment 1

[0054] When the impure positron-emitting isotope in PET imaging decays with a positron, it emits a positron and a single gamma photon at the same time, and the time difference between the two is only in the order of picoseconds (ps). Therefore, the gamma photon is called a prompt gamma photon. The positron combines with the electron in the surrounding matter and annihilates to produce a pair of gamma photons (γ) with the same energy (511keV) and opposite directions, which are called annihilation photons. That is, the impure positron-emitting isotope will emit three gamma photons in PET imaging. The present invention utilizes the characteristic that the impure positron-emitting isotope emits three gamma photons at the same time to effectively distinguish it from the pure positron-emitting isotope, and further utilizes the energy difference of the prompt photons to achieve the distinction between multiple impure positron-emitting nuclides.

[0055] See also Figure 1 , Figure 1 : is a flow chart of a multi-nuclide imaging method based on image domain separation provided by an embodiment of the present invention, which specifically includes:

[0056] S1: Acquire raw data of multi-nuclide gamma photons; wherein the multi-nuclide includes one pure positron nuclide and several different impure positron nuclides.

[0057] In this embodiment, a pure positron nuclide and several other impure positron nuclides can be injected into the object to be imaged at the same time, and then the patient is scanned using a PET device to collect raw gamma photon data of a mixture of multiple nuclides, and the collection time is 10-15 minutes. The raw data can be a set of 16 bytes of data, including information such as the incident time, position and energy of the gamma photon.

[0058] It should be noted that the energies of the instantaneous photons of these impure positron nuclides need to be significantly different.

[0059] Specifically, the pure positron nuclide can be 18 F. 13 N. 11 C, etc., non-pure positron nuclides can be 68 Ga, 124 I. 22 Na etc.

[0060] S2: Processing the raw data of the multi-nuclide gamma photons using the triple coincidence technology to obtain a set of double coincidence data and several sets of triple coincidence data of impure positron nuclides; specifically including:

[0061] S21: Sort the original data of the multi-nuclide gamma photons according to the photon arrival time.

[0062] S22: Extract double coincidence events and triple coincidence events from the sorted data.

[0063] In this embodiment, a coincidence time window T is set. For each photon event s1, if there is only another gamma photon event s2 within this time window, then these two events s1 and s2 are stored as double coincidence events; if there are only two other gamma photon events s3 and s4 within this time window, then the three events s1, s3, and s4 are stored as triple coincidence events. In this embodiment, the time window T can be 3 - 10 ns.

[0064] For example, assume that i, j, and k are three adjacent gamma photon events after time sorting, and the times when the photons are received by the PET detector are t i , t j , t k (t i < t j < t k ), if t j - t i < T and t k - t i > T, then i and j form a pair of double coincidence events DC ij , if t k - t i < T, then i, j, and k form a pair of triple coincidence events TC ijk , otherwise they do not form coincidence events.

[0065] S23: Use a conventional positron energy window to剔除部分散射数据 from the double coincidence events to obtain double coincidence data.

[0066] In this embodiment, the conventional positron energy window is denoted as E r , its lower threshold is 350 keV - 450 keV, and its upper threshold is 550 keV - 650 keV.

[0067] Since only one positron (β+) is emitted when an isotope undergoes positron decay, this positron combines with an electron (β-) in the surrounding matter, and after annihilation, a pair of gamma photons (γ) with the same energy (511 keV) and opposite running directions are produced. Therefore, in this embodiment, it is preferred to use a conventional energy window near 511 keV to filter the double coincidence data, retain the data where the energies of both photons are within the conventional positron energy window range, and剔除 other data that do not meet the requirements to obtain double coincidence data.

[0068] Specifically, for the double coincidence event DC It should be noted that the Chinese expression "剔除部分散射数据" in the original text seems to be an incomplete or incorrect expression. I translated it as "剔除部分散射数据" as accurately as possible according to the context, but it may need to be further confirmed and corrected in the actual situation. Also, the expression "常规能量窗为511keV附近的能量窗对双符合数据进行滤波处理" is a bit ambiguous in Chinese, and the translation tries to convey the meaning as clearly as possible.ij , if the energy e of gamma photon event i i Meet the conventional energy window range E r And the energy of gamma photon event j is e j It also satisfies E r , then keep the double matching event if e i or j Not satisfied with E r , then the double matching event is eliminated.

[0069] In this embodiment, since the two gamma photons satisfying the double coincidence are both generated by positron annihilation, the double coincidence data is also the double coincidence annihilation photon data.

[0070] S24: using a conventional positron energy window to remove part of the scattered data in the triple coincidence event, and using different energy windows to perform secondary filtering on the remaining data according to the type of the impure positron nuclide, to obtain several groups of triple coincidence data of the impure positron nuclide.

[0071] S24-1: Use a conventional positron energy window to filter the three coincidence events, retain data with at least two photon energies within the conventional positron energy window, and eliminate other unsatisfactory data.

[0072] When a non-pure positron-emitting isotope decays, it emits a positron and a single gamma photon, which will also react with electrons (β - ) combine and annihilate to produce a pair of gamma photons (γ) with the same energy (511 keV) and opposite directions. Therefore, this embodiment still prefers to filter it using the conventional energy window near 511 keV.

[0073] Specifically, for the three matching events TC ijk , if e i , e j and e k At least two of them satisfy the conventional energy window range E r , then the three matching events are retained, otherwise the three matching events are eliminated.

[0074] S24-2: According to the instantaneous photon energy of different impure positron nuclides, multiple specific energy windows near the energy are set; for the remaining data obtained in step S24-1, different specific energy windows are used for secondary filtering and classification, and the three-coincidence data with only one gamma photon energy satisfying a specific energy window are retained, and other data are eliminated, and the three-coincidence data satisfying the same specific energy window are classified into one category, so as to obtain several groups of three-coincidence data of impure positron nuclides.

[0075] The specific energy windows in this embodiment are respectively denoted as E s1 、E s2 ……E sn , which can be set accordingly according to the instantaneous photon energy of different impure positron nuclides. For example, 68 For Ga nuclide, the threshold value under the specific energy window can be set to 800keV.

[0076] Specifically, for a certain impure positron nuclide, the specific energy window E s1 , the above three events meet TC ijk If e i , e j and e k There is only one gamma photon event with an energy satisfying E s1 , then the triple coincidence event is retained, and the gamma photon is a prompt photon, and the remaining two gamma photons are annihilation photons. Otherwise, the triple coincidence event is eliminated, thereby obtaining the triple coincidence data of the impure positron nuclide.

[0077] Correspondingly, the triple coincidence data are classified using other different specific energy windows to obtain several groups of triple coincidence data of impure positron nuclides.

[0078] It is understandable that in a triple coincidence event, the gamma photon that meets a specific energy window is considered to be a prompt photon, and the remaining two photons are annihilation photons. Thus, the obtained triple coincidence data includes prompt photon data and annihilation photon data.

[0079] S3: performing low-dose imaging on the annihilation photon data in the triple coincidence data of the plurality of groups of impure positron nuclides respectively, and obtaining a plurality of corresponding impure positron nuclide distribution maps.

[0080] Due to some impure positron nuclides, the probability of producing instantaneous photons is extremely low, e.g. 68 Ga, whose probability of producing instantaneous photons is only 1.2%, if reconstructed using conventional methods, its image will produce very strong noise. In addition, due to the non-negative constraints of conventional iterative reconstruction methods in the image domain, the reconstructed low-dose image will produce positive bias in the nuclide-free area, which will affect the final quantitative results and increase the difficulty of multi-nuclide separation. Therefore, this embodiment introduces a 3D directional gradient L0 norm regularization term in the image domain to achieve low-dose image reconstruction. Specifically including:

[0081] S31: Using image domain non-negativity constraints and image gradient sparsity constraints, an unconstrained optimization model for low-dose imaging is constructed.

[0082] First, a regularization term to suppress noise and image domain constraints to ensure the physical meaning of the reconstructed image are introduced, and a constrained optimization model for low-dose imaging is constructed as follows:

[0083]

[0084] Wherein, f represents the image to be reconstructed, g(f) is the objective function, which is set to a convex function, which can be a likelihood function, etc., f≥0 is a non-negative constraint in the image domain, and S represents the solution space that satisfies the 3D directional gradient sparsity.

[0085] Then, the 3D directional gradient sparsity constraint is introduced into the image domain, and the original problem is converted into an unconstrained optimization, and the unconstrained optimization model of low-dose imaging is obtained, which is expressed as:

[0086]

[0087] Where f represents the image to be reconstructed, g(f) is the data fidelity term of the objective function, which is set as a convex function. represents the non-negative constraint in the image domain, R(f) is the 3D directional gradient L0 norm regularization term, expressed as and represents the directional gradient of the reconstructed image, ‖·‖0 represents the L0 norm, and ρ1, ρ2, and ρ3 represent the regularization strengths of different gradient directions.

[0088] S32: using the annihilation photon data in the three-coincidence data of several groups of impure positron nuclides as input data of the unconstrained optimization model, and introducing auxiliary variables, decomposing the optimization problem into multiple sub-problems, and iteratively solving the sub-problems in turn, to obtain low-noise imaging results of several impure positron nuclides;

[0089] Specifically, in order to solve the above non-convex model, auxiliary variables are introduced to transform the above unconstrained optimization model into:

[0090]

[0091] Among them, v, p, q are auxiliary variables.

[0092] The above optimization problem is decomposed into two sub-problems related to the original variable and the auxiliary variable, where sub-problem 1 is related to the original variable f:

[0093]

[0094] Subproblem 2 is related to auxiliary variables v, p, q:

[0095]

[0096] The decomposed sub-problem 1 is a convex optimization problem, which can be solved using the convex optimization method. The decomposed sub-problem 2 classifies and discusses whether the auxiliary variables v, p, and q are 0. For each category, it is a convex optimization problem. The closed-form solution is obtained using the convex optimization method. The two sub-problems are iteratively updated in turn to obtain low-noise imaging results of several impure positron nuclides.

[0097] S33: performing image filtering and post-processing on the above imaging results to obtain a plurality of non-pure positron nuclide distribution maps.

[0098] S4: reconstructing the double coincidence data to obtain a mixed distribution map of multiple nuclides, and using the mixed distribution map to sequentially separate the plurality of impure positron nuclide distribution maps to obtain a corresponding pure positron nuclide distribution map.

[0099] First, the double coincidence data obtained in step S2 are reconstructed by MLEM (Maximum Likelihood Expectation Maximization) image reconstruction to obtain a mixed distribution map of multiple nuclides.

[0100] Then, the image is subtracted from the impure positron nuclide distribution map obtained in step S3 at a certain ratio to achieve separation of the two in the image domain and obtain the distribution of pure positron nuclides. The proportionality coefficient can be obtained through simulation or phantom experiment.

[0101] At this point, multi-nuclide imaging of low-probability occurrence of transient photons has been completed.

[0102] The multi-nuclide imaging method provided by the present invention retains the three-coincidence data for multi-nuclide imaging with low probability of instantaneous photons, extracts energy information and classifies annihilation photon data in the three-coincidence data, uses a low-dose reconstruction algorithm to achieve low-noise imaging of impure positron nuclides, and finally achieves simultaneous imaging and separation of multiple nuclides through an image domain separation method, thereby solving the defect that conventional PET cannot distinguish between pure positron nuclides and impure positron nuclides that produce instantaneous photons with low probability, and makes PET imaging technology have broader application prospects.

[0103] Furthermore, the present invention utilizes an image domain directional gradient sparse constraint algorithm to achieve high signal-to-noise ratio imaging of impure positron nuclides during low-dose reconstruction; at the same time, due to the use of the 3D directional gradient L0 norm as a regularization term, the edge information of the nuclide distribution in the image is greatly protected, which is beneficial to the tumor localization of the impure positron nuclides.

[0104] Embodiment 2

[0105] Based on the above-mentioned embodiment 1, this embodiment takes dual-nuclide imaging as an example to verify and illustrate the method and beneficial effects of the present invention. Figure 2 , Figure 2 Detailed flowchart of the dual-nuclide imaging method provided by an embodiment of the present invention. The specific steps of the dual-nuclide imaging method of this embodiment are as follows:

[0106] Step 1: Set relevant parameters.

[0107] Specifically, set the acquisition time to meet the time window T and the conventional energy window E r and specific energy window E s1 , where the acquisition time is set to 10 minutes, the time window T is 6 nanoseconds, and the conventional energy window E r The lower threshold is 350keV and the upper threshold is 650keV. 68 Ga nuclide, and 68 The Ga instantaneous photon energy is 1077keV, and a specific energy window E is set. s1 The lower threshold is 800keV.

[0108] Step 2: Acquire dual-nuclide gamma photon data.

[0109] Specifically, a pure positron nuclide and several other impure positron nuclides may be injected into the object to be imaged, and PET may be used for scanning. 18 F-FDG, impure positron nuclide 68 Ga. See Figure 3 , Figure 3 Schematic diagram of a dual-nuclide phantom provided in an embodiment of the present invention, wherein the light-colored area is a pure positron nuclide 18 F-FDG, dark areas are impure positron nuclides 68 The dual-nuclide phantom was scanned for 10 minutes using a PET device to collect dual-nuclide mixed gamma photon raw data.

[0110] Step 3: Using the time window, double and triple coincidence events are extracted from the gamma photon data.

[0111] Step 4: Use a regular energy window to eliminate scattering events from double- and triple-coincidence events.

[0112] Step 5: Extract the triple coincidence annihilation photon data using a specific energy window.

[0113] Step 6: The three-coincidence annihilation photon data is reconstructed at a low dose to obtain the impure positron nuclide distribution.

[0114] Step 7: Use the double coincidence annihilation photon data and the impure positron nuclide distribution to obtain the pure positron distribution.

[0115] In this embodiment, the specific implementation of steps 3-7 refers to the above-mentioned embodiment 1 and will not be described in detail here.

[0116] See also Figure 4 , Figure 4 The image of the binary nuclide separation obtained by the imaging method of the present invention is shown in the left image. 68 Ga lattice 3D reconstruction results, the right picture is a pure positron nuclide 18 F lattice three-dimensional reconstruction results.

[0117] As a comparison, this embodiment also uses conventional PET Figure 3 The binuclear analog shown was reconstructed, and the results are shown in Figure 5 shown.

[0118] from Figure 5 It can be seen that conventional PET can only reconstruct 18 F and 68 The Ga mixed dual-nuclides image cannot distinguish the two nuclides. Figure 5 For comparison, from Figure 4 It can be seen that 68 Ga and 18 The two nuclides F were effectively separated, indicating that the present invention overcomes the defect that conventional PET cannot distinguish between pure positron nuclides and impure positron nuclides that produce instantaneous photons with a lower probability, and can achieve simultaneous imaging of multiple radioactive isotopes.

[0119] Embodiment 3

[0120] Based on the above-mentioned embodiment 1, this embodiment provides a multi-nuclide imaging device based on image domain separation. Figure 6 , Figure 6 : is a schematic structural diagram of a multi-nuclide imaging device based on image domain separation provided by an embodiment of the present invention, which includes:

[0121] A data acquisition module 1 is used to acquire raw data of multi-nuclide gamma photons; wherein the multi-nuclide includes a pure positron nuclide and several different impure positron nuclides;

[0122] A coincidence extraction module 2 is used to process the raw data of the multi-nuclide gamma photons using a three-coincidence technique to obtain a set of double-coincidence data and several sets of three-coincidence data of impure positron nuclides;

[0123] A low-dose imaging module 3 is used to perform low-dose imaging on the annihilation photon data in the three-coincidence data of the plurality of groups of impure positron nuclides, and obtain a plurality of corresponding distribution maps of impure positron nuclides;

[0124] The image reconstruction module 4 is used to reconstruct the double coincidence data to obtain a mixed distribution map of multiple nuclides, and use the mixed distribution map to sequentially separate the plurality of impure positron nuclide distribution maps to obtain a corresponding pure positron nuclide distribution map.

[0125] In this embodiment, the data acquisition module 1 may include a PET imaging device, which may be a double-panel structure PET composed of several (preferably 20) detectors.

[0126] Furthermore, the data acquisition module also includes a parameter setting unit for setting information such as data acquisition time, time window, conventional energy window and specific energy window.

[0127] The multi-nuclide imaging device provided in this embodiment can be used to implement the method provided in the above-mentioned embodiment 1, and the detailed process will not be repeated here.

[0128] Therefore, the multi-nuclide imaging device based on image domain separation provided in this embodiment can also solve the defect that conventional PET cannot distinguish between pure positron nuclides and impure positron nuclides that produce instantaneous photons with a lower probability.

[0129] Embodiment 4

[0130] Based on the above embodiment 1, this embodiment provides an electronic device, see Figure 7 , Figure 7 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, which includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus;

[0131] Memory, used to store computer programs;

[0132] The processor is used to execute the program stored in the memory to implement the method steps provided in the above-mentioned embodiment 1. The implementation principle and technical effect are similar and will not be repeated here.

[0133] Embodiment 5

[0134] Based on the above implementation, please refer to Figure 8 , Figure 81 is a schematic diagram of the structure of a computer-readable storage medium provided in an embodiment of the present invention. This embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method steps provided in the first embodiment are implemented. The implementation principle and technical effect are similar and will not be repeated here.

[0135] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A multi-nuclide imaging method based on image domain separation, characterized in that: include: S1: Acquiring raw data of multi-nuclide gamma photons; wherein the multi-nuclide includes a pure positron nuclide and several different impure positron nuclides; S2: Processing the raw data of the multi-nuclide gamma photons using a triple coincidence technique to obtain a set of double coincidence data and several sets of triple coincidence data of impure positron nuclides; S3: performing low-dose imaging on the annihilation photon data in the three-coincidence data of the plurality of groups of impure positron nuclides respectively, and obtaining a plurality of corresponding impure positron nuclide distribution maps; S4: reconstructing the double coincidence data to obtain a mixed distribution map of multiple nuclides, and using the mixed distribution map to sequentially separate the plurality of impure positron nuclide distribution maps to obtain a corresponding pure positron nuclide distribution map; Wherein, the S2 includes: S21: sorting the raw data of the multi-nuclide gamma photons according to the photon arrival time; S22: extracting double coincidence events and triple coincidence events from the sorted data; S23: using a conventional positron energy window to remove part of the scattered data in the double coincidence event to obtain double coincidence data; S24: using a conventional positron energy window to remove part of the scattered data in the triple coincidence event, and using different energy windows to perform secondary filtering on the remaining data according to the type of the impure positron nuclide, to obtain several groups of triple coincidence data of the impure positron nuclide.

2. The multi-nuclide imaging method based on image domain separation according to claim 1, characterized in that: Step S22 includes: A time window is set. For each photon event, if there is only one other gamma photon event within the time window, the two events are stored as a double coincidence event; if there are only two other gamma photon events within the time window, the three events are stored as a triple coincidence event.

3. The multi-nuclide imaging method based on image domain separation according to claim 1, characterized in that: Step S23 includes: The double coincidence events are filtered using a conventional positron energy window, data with both photon energies within the conventional positron energy window are retained, and other unsatisfactory data are discarded to obtain double coincidence data.

4. The multi-nuclide imaging method based on image domain separation according to claim 1, characterized in that: Step S24 includes: S24-1: Filter the three coincidence events using a conventional positron energy window, retain data with at least two photon energies within the conventional positron energy window, and remove other data that do not meet the requirements; S24-2: According to the instantaneous photon energy of different impure positron nuclides, multiple specific energy windows near the energy are set; for the remaining data obtained in step S24-1, different specific energy windows are used for secondary filtering and classification, and the three-coincidence data with only one gamma photon energy satisfying a specific energy window are retained, and other data are eliminated, and the three-coincidence data satisfying the same specific energy window are classified into one category to obtain several groups of three-coincidence data of impure positron nuclides; among them, the gamma photons satisfying the specific energy window are considered to be instantaneous photons, and the remaining two photons are annihilation photons.

5. The multi-nuclide imaging method based on image domain separation according to claim 1, characterized in that: Step S3 includes: S31: Using image domain non-negative constraints and image gradient sparsity constraints, an unconstrained optimization model for low-dose imaging is constructed; S32: using the annihilation photon data in the three-coincidence data of several groups of impure positron nuclides as input data of the unconstrained optimization model, introducing auxiliary variables, decomposing the optimization problem into multiple sub-problems, and iteratively solving the sub-problems in turn to obtain low-noise imaging results of several impure positron nuclides; S33: performing image filtering and post-processing on the above imaging results to obtain a plurality of non-pure positron nuclide distribution maps.

6. The multi-nuclide imaging method based on image domain separation according to claim 5, characterized in that: In step S31, the expression of the unconstrained optimization model of low-dose imaging is: Where f represents the image to be reconstructed, g(f) is the data fidelity term of the objective function, represents the non-negative constraint in the image domain, R(f) is the 3D directional gradient L0 norm regularization term, expressed as and represents the directional gradient of the reconstructed image, ‖·‖0 represents the L0 norm, and ρ1, ρ2, and ρ3 represent the regularization strengths of different gradient directions.

7. A multi-nuclide imaging device based on image domain separation, characterized in that: include: A data acquisition module, used to acquire raw data of multi-nuclide gamma photons; wherein the multi-nuclide includes a pure positron nuclide and several different impure positron nuclides; The coincidence extraction module is used to process the raw data of the multi-nuclide gamma photons using the triple coincidence technology to obtain a set of double coincidence data and several sets of triple coincidence data of impure positron nuclides; specifically, it includes: sorting the raw data of the multi-nuclide gamma photons according to the photon arrival time; Extracting double coincident events and triple coincident events from the sorted data; Using a conventional positron energy window to remove part of the scattered data in the double coincidence event, to obtain double coincidence data; Using a conventional positron energy window to remove part of the scattered data in the triple coincidence event, and using different energy windows to perform secondary filtering on the remaining data according to the type of impure positron nuclides, to obtain several groups of triple coincidence data of impure positron nuclides; A low-dose imaging module is used to perform low-dose imaging on the annihilation photon data in the three-coincidence data of the plurality of groups of impure positron nuclides, and obtain a plurality of corresponding distribution maps of the impure positron nuclides; The image reconstruction module is used to reconstruct the image of the double coincidence data to obtain a mixed distribution map of multiple nuclides, and use the mixed distribution map to sequentially separate the plurality of impure positron nuclide distribution maps to obtain a corresponding pure positron nuclide distribution map.

8. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, for implementing the method according to any one of claims 1 to 6 when executing a program stored in a memory.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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