Medical image construction method and device, computer equipment and storage medium

Abstract

The invention relates to a medical image construction method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a signal data set obtained by performing signal detection on a detection object by a detector array; the detector array is used for three-dimensionally surrounding a detection object and detecting a tracing signal sent by the detection object; determining a detection scene of the detector array for the detection object based on the data characteristics of the signal data set; under the condition that the detection scene is the target scene, determining an effective detection range of each detector in the detector array; wherein the effective detection ranges corresponding to the detector in different detection scenes are different; and extracting target signal data of each detector in the respective effective detection range from the signal data set, and constructing a medical detection map for the detected object based on the target signal data. By adopting the method, the construction efficiency of the medical image can be improved, and the accuracy and feasibility of construction of the medical image can be ensured.

Description

Technical Field

[0001] This application relates to the field of medical imaging technology, and particularly to a method for constructing a medical image, a device for constructing a medical image, a computer device, a storage medium, and a computer program product. Background Art

[0002] Positron Emission Tomography (PET) is a medical imaging technology used to observe the biological activities and functions inside a detection object. It injects a radioactive tracer (usually glucose labeled with a radioactive isotope) into the detection object's body, and then uses a PET scanner to detect and record the spatial distribution of the radioactive tracer in the body.

[0003] During the PET detection process, the radioactive tracer emits tracer signals (such as when a positron meets an electron in the body, annihilation occurs, generating two gamma-ray signals moving in opposite directions), and then the PET scanner detects and records these tracer signals. By analyzing and reconstructing the data of these tracer signals, tomographic images of the body are generated to observe and evaluate the metabolic activities, blood flow, brain functions, etc. of different tissues and organs.

[0004] However, in current PET systems, due to the increase in system sensitivity, both the data volume and the count rate will increase exponentially. In corresponding special scenarios (such as myocardial injection in clinical practice, dynamic scanning, etc. scenarios involving high-activity radiation sources), the PET system will capture a large number of tracer signals in a short period of time. These tracer signals will bring great pressure to the data processing, data storage, and reconstruction of the PET system, affecting the availability, correctness of the data, and the consistency of the reconstructed images. Summary of the Invention

[0005] Based on this, to address the above technical problems, it is necessary to provide a method for constructing a medical image, a device for constructing a medical image, a computer device, a storage medium, and a computer program product that can improve the availability and correctness of signal data.

[0006] In a first aspect, this application provides a method for constructing a medical image. The method includes:

[0007] Obtain a set of signal data obtained by a detector array for signal detection of a detection object; the detection object is a medical diagnosis and treatment object input with a radioactive tracer; the detector array is used to surround the detection object three-dimensionally and detect the tracer signals emitted by the detection object to obtain signal data;

[0008] Based on the data characteristics of the set of signal data, determine the detection scenario of the detector array for the detection object;

[0009] When the detection scenario is the target scenario, determine the effective detection ranges of the detectors in the detector array; wherein, the effective detection ranges corresponding to the detectors in different detection scenarios are different;

[0010] Extract the target signal data of each detector within its respective effective detection range from the signal data set, and construct a medical detection image for the detection object based on the target signal data.

[0011] In one embodiment, the determining the effective detection ranges of the detectors in the detector array includes:

[0012] Obtain the detection area of the detector array for the detection object;

[0013] Based on the detection area, determine the effective detection ranges corresponding to the detectors.

[0014] In one embodiment, the detection area includes a first planar area of the detection object within the axial field of view of the detector array and a second planar area within the circumferential field of view;

[0015] The determining the effective detection ranges corresponding to the detectors based on the detection area includes:

[0016] Based on the first planar area, determine the first effective detection ranges of the detectors within the axial field of view; and

[0017] Based on the second planar area, determine the second effective detection ranges of the detectors within the circumferential field of view.

[0018] In one embodiment, the determining the effective detection ranges corresponding to the detectors includes:

[0019] For the axial field of view, use the detector as an endpoint and the corresponding two first enclosing lines as side lines to enclose the first planar area to obtain a first enclosed area; use the visual field range corresponding to the first enclosed area as the first effective detection range; and

[0020] For the circumferential field of view, use the detector as an endpoint and the corresponding two second enclosing lines as side lines to enclose the second planar area to obtain a second enclosed area; use the visual field range corresponding to the second enclosed area as the second effective detection range;

[0021] One end of the first enclosing line is at the end point position, and the other end is within the axial length range of the detector array. The first enclosing area is used to enclose at least part of the first planar area.

[0022] One end of the second enclosing line is at the end point position, and the other end is within the circumferential length range of the detector array. The second enclosing area is used to enclose all of the second planar area.

[0023] In one embodiment, each detector has at least one coincidence link within its respective effective detection range. One end in the coincidence link is the local detector corresponding to the effective detection range, and the other end is the peer detector.

[0024] Extracting the target signal data of each detector within its respective effective detection range from the signal data set includes:

[0025] In the signal data set, extract the target tracer signals detected by the local detector and the peer detector on each coincidence link to which each detector belongs within the corresponding effective detection range, and use the target tracer signals as the target signal data.

[0026] In one embodiment, determining the detection scenario of the detector array for the detection object based on the data characteristics of the signal data set includes:

[0027] Perform signal recognition on each signal data in the signal data set to determine the statistical data of the detection object emitting the tracer signal based on the radioactive tracer. The statistical data is used to characterize the activity level of the radioactive tracer in the detection object.

[0028] Based on the activity level, determine the detection scenario of the detector array.

[0029] In one embodiment, performing signal recognition on each signal data in the signal data set to determine the statistical data of the detection object emitting the tracer signal based on the radioactive tracer includes:

[0030] Perform recognition on the preset radioactive signals and positron signals emitted by the detection object within the time window to obtain the data volume of the radioactive signals and the count rate of the positron signals, and use the data volume and / or the count rate as the statistical data for the tracer signal.

[0031] In a second aspect, the present application also provides a device for constructing a medical image. The device includes:

[0032] A signal detection module for obtaining a set of signal data obtained by a detector array detecting signals for a detection object; the detection object is a medical diagnosis and treatment object input with a radioactive tracer; the detector array is used to surround the detection object three-dimensionally and detect the tracer signals emitted by the detection object to obtain signal data;

[0033] A scene recognition module for determining the detection scene of the detector array for the detection object based on the data characteristics of the set of signal data;

[0034] A detection range module for determining the effective detection range of each detector in the detector array when the detection scene is a target scene; wherein, the effective detection range corresponding to the detector in different detection scenes is different;

[0035] An image construction module for extracting the target signal data of each detector within its respective effective detection range from the set of signal data and constructing a medical detection image for the detection object based on the target signal data.

[0036] In a third aspect, the present application also provides a computer device. The computer device includes:

[0037] A processor;

[0038] A memory for storing executable instructions of the processor;

[0039] Wherein, the processor is configured to execute the executable instructions to implement a method for constructing a medical image.

[0040] In a fourth aspect, the present application also provides a computer-readable storage medium. The computer-readable storage medium includes program data, and is characterized in that when the program data is executed by a processor of a computer device, the computer device can execute a method for constructing a medical image.

[0041] In a fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, it implements a method for constructing a medical image.

[0042] The above-mentioned method and device for constructing a medical image, computer equipment and storage medium, on the one hand, first determine the detection scenario of the detector array for the detection object through the data characteristics of the detected signal data set, and then determine the effective detection range of each detector according to the corresponding detection scenario, so as to construct a medical detection image by using the target signal data within the corresponding effective detection range, thereby optimizing the construction process of the medical image, and compared with the existing technology, effectively improving the construction efficiency of the medical image with a standardized execution program and reducing the consumption of manpower and material resources; on the other hand, by first detecting the tracer signal emitted by the detection object by stereoscopically surrounding the detection object, and then extracting the target signal data within the effective detection range of each detector from the tracer signal according to the detection scenario of the detector array to construct a medical detection image, thereby improving the accuracy and feasibility of the construction of the medical image, which is conducive to providing more effective reference information for subsequent medical treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings herein are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure, and do not constitute an improper limitation of the present disclosure.

[0044] Figure 1 It is an application environment diagram of a method for constructing a medical image shown according to an exemplary embodiment.

[0045] Figure 2 It is a flowchart of a method for constructing a medical image shown according to an exemplary embodiment.

[0046] Figure 3 It is a structural diagram of a detector array shown according to an exemplary embodiment.

[0047] Figure 4 It is a structural diagram of a coincidence link of a detector shown according to an exemplary embodiment.

[0048] Figure 5 It is a flowchart of a step for determining the effective detection range of a detector shown according to an exemplary embodiment.

[0049] Figure 6 It is a structural diagram of the effective detection range of a detector in the axial field of view shown according to an exemplary embodiment.

[0050] Figure 7 It is a structural diagram of the effective detection range of a detector in the circumferential field of view shown according to an exemplary embodiment.

[0051] Figure 8 It is a block diagram of a PET / CT system shown according to an exemplary embodiment.

[0052] Figure 9 A block diagram of a medical image construction device shown according to an exemplary embodiment.

[0053] Figure 10 A block diagram of a computer for medical image construction shown according to an exemplary embodiment.

[0054] Figure 11 A block diagram of a computer-readable storage medium for medical image construction shown according to an exemplary embodiment.

[0055] Figure 12 A block diagram of a computer program product for medical image construction shown according to an exemplary embodiment. Detailed implementation manners

[0056] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0057] The term "and / or" in the embodiments of the present application refers to any and all possible combinations including one or more of the associated listed items. It should also be noted that when used in this specification, "including / comprising" specifies the presence of the stated features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements and / or components and / or their groups.

[0058] The terms "first", "second", etc. in the present application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0059] In addition, although the terms "first", "second", etc. are used many times in the present application to describe various operations (or various elements or various applications or various instructions or various data), etc., these operations (or elements or applications or instructions or data) should not be limited by these terms. These terms are only used to distinguish one operation (or element or application or instruction or data) from another operation (or element or application or instruction or data).

[0060] The medical image construction method provided by the embodiments of the present application can be applied to, for example Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through a communication network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or placed in the cloud or on a web server.

[0061] In some embodiments, referring to Figure 1 , the server 104 first obtains a set of signal data obtained by the detector array for signal detection of the detection object; wherein, the detection object is a medical diagnosis and treatment object input with a radioactive tracer; the detector array is used to surround the detection object three-dimensionally and detect the tracer signal emitted by the detection object to obtain signal data; then, the server 104 determines the detection scenario of the detector array for the detection object based on the data characteristics of the set of signal data; and in the case where the detection scenario is the target scenario, determines the effective detection range of each detector in the detector array; wherein, the effective detection range corresponding to the detector in different detection scenarios is different; finally, the server 104 extracts the target signal data of each detector within its respective effective detection range from the set of signal data, and constructs a medical detection image for the detection object based on the target signal data.

[0062] In some embodiments, the terminal 102 (such as a mobile terminal, a fixed terminal) can be implemented in various forms. Among them, the terminal 102 can be a mobile terminal such as a mobile phone, a smart phone, a notebook computer, a portable handheld device, a personal digital assistant (PDA, Personal Digital Assistant), a tablet computer (PAD), etc., which can construct a medical detection image for the detection object according to the target signal data within the effective detection range of the detector, and the terminal 102 can also be a fixed terminal such as an automated teller machine (Automated Teller Machine, ATM), an all-in-one machine, a digital TV, a desktop computer, a fixed computer, etc., which can construct a medical detection image for the detection object according to the target signal data within the effective detection range of the detector.

[0063] Hereinafter, it is assumed that the terminal 102 is a fixed terminal. However, those skilled in the art will understand that if there are operations or components specifically for mobile purposes, the configuration according to the embodiments disclosed in the present application can also be applied to the mobile type of terminal 102.

[0064] In some embodiments, the data processing components running on the server 104 can load any one of various additional server applications and / or middleware applications being executed, such as including HTTP (HyperText Transfer Protocol), FTP (File Transfer Protocol), CGI (Common Gateway Interface), RDBMS (Relational Database Management System), etc.

[0065] In some embodiments, the server 104 may implement corresponding network functions through deployed servers (such as a stand-alone server or a server cluster composed of multiple servers). The server 104 may also be adapted to run one or more application services or software components of the terminal 102 described in the foregoing disclosure.

[0066] In some embodiments, the application services may include providing a service interface for medical detection image construction to the user (such as a tracer signal acquisition interface, a signal data processing and display interface, etc.), as well as corresponding program services, and so on. Among them, the software components may include, for example, an application program (SDK) or a client (APP) having an image reconstruction processing function according to the detection scenario.

[0067] In some embodiments, the application program or client provided by the server 104 having an image reconstruction processing function according to the detection scenario includes a portal port that provides one-to-one application services to the user in the foreground and multiple business systems that perform data processing in the background, so as to extend the image reconstruction processing function application to the APP or the client, so that the user can use and access the image reconstruction processing function at any time and any place.

[0068] In some embodiments, the image reconstruction processing function in the APP or the client may be a computer program running in the user mode to complete one or more specific tasks, which can interact with the user and has a visible user interface. Among them, the APP or the client may include two parts: a graphical user interface (GUI) and an engine, and a digital customer system that can provide various application services to the user in the form of a user interface can be realized by using these two parts.

[0069] In some embodiments, the user may input corresponding code data or control parameters to the APP or the client through a preset input device or an automatic control program to execute the application services of the computer program in the server 104 and display the application services in the user interface.

[0070] In some embodiments, the operating systems on which the APP or the client runs may include various versions of Microsoft Windows®, Apple Macintosh® and / or Linux operating systems, various commercial or UNIX®-like operating systems (including but not limited to various GNU / Linux operating systems, Google Chrome®OS, etc.) and / or mobile operating systems, such as iOS®, Windows® Phone, Android® OS, BlackBerry® OS, Palm® OS operating systems, as well as other online operating systems or offline operating systems, which are not specifically limited here.

[0071] In some embodiments, such as Figure 2 shown, a method for constructing a medical image is provided. Taking the method applied to the server 104 in Figure 1 as an example, the method includes the following steps:

[0072] Step S11: Obtain a set of signal data obtained by a detector array for signal detection of a detection object.

[0073] Wherein, the detection object is a medical diagnosis and treatment object input with a radioactive tracer. For example, a human object, an animal object, a plant object, etc.

[0074] In one embodiment, the radioactive tracer is a compound labeled with a radioactive isotope that acts on a living object's body. This compound can participate in the blood flow or metabolic process of the object's tissue, and it includes, for example, glucose labeled with a radioactive isotope.

[0075] In one embodiment, the detector array is used to stereoscopically surround the detection object and detect the tracer signals emitted by the detection object to obtain signal data.

[0076] In some embodiments, after the radioactive tracer is input into the detection object's body, it emits positrons. When these positrons meet the negative electrons in the body, annihilation occurs to generate two relatively moving gamma rays. Then, each detector on the detector array will detect and record these gamma rays to obtain a set of signal data.

[0077] In an exemplary embodiment, refer to Figure 3 , Figure 3 which is a schematic structural diagram of an embodiment of the detector array in this application. As Figure 3 shown, the detector array 104 may include one or more detector units, and the one or more detector units may be encapsulated to form a cylindrical three-dimensional detector box, that is, the detector array 104 may be arranged in a ring configuration (also referred to as a detection ring) in the cross-section. Among them, the detector array 104 may be covered and protected by a housing 104, and the housing 104 may be a hollow cylinder. Among them, the area surrounded by the detector array 104 may be a detection area, and the detection object 102 to be scanned may be accommodated in the detection area to stereoscopically surround the detection object 102. Among them, when the detection object 102 is within the field of view area of the detector array 104, the tracer signals (for example, γ photon signals, positron signals, etc.) emitted from the detection object 102 can be detected by the detector array 104 to obtain signal data.

[0078] In some embodiments, the detector array 104 may include one or more crystal elements (e.g., detector crystals). When a tracer signal (e.g., a gamma-ray photon) reaches the detector crystal, the detector crystal can absorb the energy of the tracer signal and convert the absorbed energy into visible light. In some embodiments, the detector crystals may be arranged in an N-row and M-column distribution. Here, N may be an integer greater than 0, and M may be an integer greater than 0. In some embodiments, a barrier material (e.g., a reflective film, etc.) may be filled between two adjacent detector crystals in the detector array 104. The detector crystal may use one or more types of crystals, including, for example, one or a combination of several of NaI(TI), BGO, LSO, YSO, GSO, LYSO, LaBr3, LFS, LuAP, LuI3, BaF2, CeF, CsI(TI), CsI(Na), CaF2(Eu), CdWO4, YAP, etc.

[0079] Step S12: Based on the data characteristics of the signal data set, determine the detection scenario of the detector array for the detection object.

[0080] Specifically, the server first performs signal identification on each signal data in the signal data set to determine the statistical data of the detection object based on the radioactive tracer for the tracer signal; then, based on this statistical data, determine the detection scenario of the detector array.

[0081] Among them, the statistical data is used to characterize the activity level of the radioactive tracer in the detection object. That is, if the statistical data of the tracer signal emitted by the detection object is higher, the activity level of the radioactive tracer is higher; if the statistical data of the tracer signal emitted by the detection object is lower, the activity level of the radioactive tracer is lower.

[0082] In one embodiment, the server determines the statistical data of the detection object based on the radioactive tracer for the tracer signal, including: identifying the preset radioactive signal and positron signal emitted by the detection object within the time window to obtain the data volume of the radioactive signal and the counting rate of the positron signal, and using the data volume and / or the counting rate as the statistical data for the tracer signal.

[0083] As an example, the signal data set collected by the detector array within a preset time window (e.g., 0 - 15 us) includes X pieces of signal data. The server identifies each of the X pieces of signal data one by one to determine the data volume of the radioactive signal (e.g., gamma-ray) and the counting rate of the positron signal therein, and then uses the data volume and / or the counting rate as the statistical data for the tracer signal.

[0084] Step S13: In the case where the detection scenario is the target scenario, determine the effective detection range of each detector in the detector array.

[0085] Among them, the effective detection ranges corresponding to the detector in different detection scenarios are different.

[0086] For example, the effective detection range corresponding to the detector in a detection scenario with high activity (the activity level of the radioactive tracer in the detection object is relatively high) is the first range; the effective detection range corresponding to the detector in a detection scenario with medium activity (the activity level of the radioactive tracer in the detection object is average) is the second range; the effective detection range corresponding to the detector in a detection scenario with low activity (the activity level of the radioactive tracer in the detection object is relatively low) is the third range. Among them, the first range is greater than the second range, and the second range is greater than the third range.

[0087] In one embodiment, each detector has at least one coincidence link within its respective effective detection range. Among them, one end in the coincidence link is the local detector corresponding to the effective detection range, and the other end is the remote detector.

[0088] In an exemplary embodiment, refer to Figure 4 , Figure 4 is a schematic structural diagram of an embodiment of the coincidence link of the detector in the present application. As shown in the figure, this schematic diagram is a cross-sectional view of the detector array, and each detector is arranged in a ring-shaped cylindrical manner to surround the space of the detection object 201. Among them, the detector P1 is the local detector, and within its effective field of view (FOV), it includes the remote detectors P2, P3, P4, P5, P6, and P7. Among them, the line connecting the detector P1 and the remote detector P2 is the coincidence link S1 (this line is also called the line of response (LOR)), the line connecting the detector P1 and the remote detector P3 is the coincidence link S2, the line connecting the detector P1 and the remote detector P4 is the coincidence link S3, the line connecting the detector P1 and the remote detector P5 is the coincidence link S4, the line connecting the detector P1 and the remote detector P6 is the coincidence link S5, and the line connecting the detector P1 and the remote detector P7 is the coincidence link S6.

[0089] Step S14: Extract the target signal data of each detector within its respective effective detection range from the signal data set.

[0090] Specifically, the server extracts the target tracer signals detected by the local detector and the remote detector on each coincidence link belonging to each detector within the corresponding effective detection range from the signal data set, and uses the target tracer signals as the target signal data.

[0091] Among them, the target trace signal is a trace signal that conforms to the link and generates a coincidence event.

[0092] In some embodiments, the server first takes the trace signals emitted by the local detector and the remote detector on each coincidence link as a signal data group, and obtains a set of signal data groups for each coincidence link; then, it separately performs coincidence event judgment based on a time window on the signal data groups in the set of signal data groups. When it is judged that a coincidence event occurs, the server records the response data of the trace signal (including information such as the energy intensity, response time, and response position generated by the coincidence event), and takes the response data of the trace signal as the target signal data and stores it.

[0093] Among them, after the radioactive tracer is injected into the detection object's body, the positrons emitted by the decay of the radionuclide combine with the negative electrons in the tissue to undergo annihilation, generating two γ photons with equal energy and opposite directions. Since the paths of the two γ photons in the body are different, there is also a certain difference in the time to reach the two detectors. If within a specified time window (for example, 0 - 15 μs), the local detector and the remote detector located on the coincidence link detect two γ photons that are 180 degrees apart, a coincidence event is formed.

[0094] Step S15: Construct a medical detection image for the detection object based on the target signal data.

[0095] Specifically, the server can sequentially perform data preprocessing, algorithm reconstruction processing, image postprocessing, and image display processing on the target signal data to obtain the corresponding medical detection image.

[0096] Among them, data preprocessing: used to preprocess the collected target signal data, including energy cutting, time correction, and scatter correction, etc. These preprocessing steps help improve the image quality and accuracy.

[0097] Among them, algorithm reconstruction processing: used to convert the preprocessed data into a three-dimensional PET image. Commonly used reconstruction algorithms include iterative algorithms, filtered backprojection algorithms, etc. These algorithms restore the image based on the characteristics of the signal data and the sampling method through mathematical models and image processing techniques.

[0098] Among them, image postprocessing: used to postprocess the reconstructed three-dimensional PET image, including removing noise, correcting the non-uniformity of the scanner, correcting gradient drift, enhancing contrast, smoothing the image, etc. These postprocessing steps help improve the visualization effect and diagnostic ability of the image.

[0099] Among them, image display processing: used to display the reconstructed PET image on the screen for doctors and researchers to analyze and diagnose.

[0100] In the process of constructing the above-mentioned medical image, the server first obtains a set of signal data obtained by the detector array for signal detection of the detection object; wherein, the detection object is a medical diagnosis and treatment object input with a radioactive tracer; the detector array is used to surround the detection object three-dimensionally and detect the tracer signals emitted by the detection object to obtain signal data; then, based on the data characteristics of the set of signal data, the detection scenario of the detector array for the detection object is determined; and when the detection scenario is the target scenario, the effective detection range of each detector in the detector array is determined; wherein, the effective detection range corresponding to the detector in different detection scenarios is different; finally, the target signal data of each detector within its respective effective detection range is extracted from the set of signal data, and a medical detection image for the detection object is constructed based on the target signal data. In this way, on the one hand, first, the detection scenario of the detector array for the detection object is determined through the data characteristics of the detected set of signal data, and then the effective detection range of each detector is determined according to the corresponding detection scenario, so as to construct a medical detection image using the target signal data within the corresponding effective detection range, thereby optimizing the construction process of the medical image, and compared with the method in the prior art, effectively improving the construction efficiency of the medical image with a standardized execution procedure and reducing the consumption of manpower and material resources; on the other hand, by first surrounding the detection object three-dimensionally to detect the tracer signals emitted by the detection object, and then extracting the target signal data of each detector within the corresponding effective detection range from the tracer signals according to the detection scenario of the detector array to construct a medical detection image, the accuracy and feasibility of the construction of the medical image are improved, which is conducive to providing more effective reference information for subsequent medical treatment.

[0101] Those skilled in the art can understand that in the above method of the specific implementation manner, the disclosed method can be implemented in a more specific manner. For example, the above-described implementation manner in which the server determines the effective detection range of each detector in the detector array according to the detection scenario of the detector array for the detection object is only illustrative.

[0102] In an exemplary embodiment, refer to Figure 5 , Figure 5 which is a schematic flowchart of an embodiment for determining the effective detection range of the detector in this application. In step S13, that is, the process in which the server determines the effective detection range of each detector in the detector array when the detection scenario is the target scenario, the technical content of the following method can be specifically executed:

[0103] Step S131: Obtain the detection area of the detector array for the detection object.

[0104] In one embodiment, the detection area is a physical space area in the detection object, which includes a first planar area of the detection object within the axial field of view of the detector array and a second planar area within the circumferential field of view.

[0105] Specifically, on the axial field of view of the detector array, the area within the object contour area occupied by the detection object that belongs to the detection area of the detector array for the detection object is used as the first planar area; and, on the circumferential field of view of the detector array, the area within the object contour area occupied by the detection object that belongs to the detection area of the detector array for the detection object is used as the second planar area.

[0106] In one embodiment, the detection area can be obtained based on the current scanning protocol of the detector array, the shooting area of the 2D / 3D cameras installed in the detector array, or the area of concern manually planned by a physician. Here, the specific determination method of the detection area is not specifically limited.

[0107] In some embodiments, the detector array scans and detects the detection object based on a preset scanning protocol. Among them, the detection area of the detector array for the detection object is different under different protocols.

[0108] In some embodiments, the scanning protocol is the scanning program and parameters configured when the detector array scans and detects the detection object, which includes corresponding scanning parameters, scanning time, and scanning area.

[0109] As an example, when the current scanning protocol represents that the detector array performs a head scan of a patient, its detection area is the head space area of the patient. The first planar area shown within the axial field of view of the detector array is the first planar area of the head entity, and the second planar area shown within the circumferential field of view is the second planar area of the head entity; when the current scanning protocol represents that the detector array performs a heart scan of a patient, its detection area is the heart space area of the patient. The first planar area shown within the axial field of view of the detector array is the first planar area of the heart entity, and the second planar area shown within the circumferential field of view is the second planar area of the heart entity.

[0110] Step S132: Based on the detection area, determine the effective detection range corresponding to each detector.

[0111] In one embodiment, for the axial field of view, the server determines the first effective detection range of each detector within the axial field of view based on the first planar area.

[0112] Specifically, the server first uses the detector as an endpoint and the corresponding two first enclosing lines as the side lines to enclose the first planar area to obtain a first enclosed area; then, the visual field range corresponding to the first enclosed area is used as the first effective detection range.

[0113] One end of the first surrounding line is at an end point position, and the other end is within the axial length range of the detector array, and the first surrounding region is used to surround at least a part of the first planar region.

[0114] In an exemplary embodiment, referring to Figure 6 , Figure 6 is a schematic structural diagram of an embodiment of the effective detection range of the detector in the axial field of view in this application. As shown in a and b of Figure 6 , the rectangular region P1 is the display region of the detector array in the axial field of view. Each detector in the detector array is arranged at the edge position of the rectangular region P1 to detect signals from the first planar region P2 where the radiation source (i.e., the detection object) is located at the center of the region. Among them, the length range of the rectangular region P1 is the axial length range of the detector array.

[0115] Among them, as shown in a of Figure 6 , for detector A, first, taking detector A as an end point and two first surrounding lines drawn from detector A as side lines, the entire first planar region P2 (i.e., the detection region of the detector array for the detection object) is surrounded to obtain the first surrounding region P3; then, the first surrounding region P3 is used as the first effective detection range of the detector array in the axial field of view. One end of the two first surrounding lines is at the end point position where detector A is located (i.e., detector A is the detector at this end), and the other end is at the positions where detectors A1 and A2 in the axial length range of the detector array are located (i.e., detectors A1 and A2 are the detectors at the opposite end), and the distance between the two first surrounding lines and the contour edge of the first planar region P2 is a preset safety distance, so that the first surrounding region P3 can surround the entire first planar region P2.

[0116] Similarly, as shown in Figure 6As shown in b of FIG. 0, for detector B, first, taking detector B as an endpoint and two first enclosing lines drawn from detector B as side lines, the entire first plane region P2 is regionally enclosed to obtain a first enclosed region P3; then, this first enclosed region P3 is taken as the first effective detection range of the detector array in the axial field of view. Among them, one end of the two first enclosing lines is at the endpoint position where detector B is located (i.e., detector B is the local detector), and the other end is at the positions of detectors B1 and B2 located within the axial length interval of the detector array in the axial field of view (i.e., detectors B1 and B2 are the opposite-end detectors). And for the first enclosing line where detector B and detector B1 are located, since detector B1 is at the endpoint position of the axial length interval of the detector array, this first enclosing line intersects the first plane region P2; also, for the first enclosing line where detector B and detector B2 are located, since detector B2 is at the middle position of the axial length interval of the detector array, the distance between this first enclosing line and the contour edge of the first plane region P2 is a preset safety distance, so that the first enclosed region P3 can enclose a part of the first plane region P2.

[0117] In another embodiment, for the circumferential field of view, the server determines the second effective detection range of each detector within the circumferential field of view based on the second plane region.

[0118] Specifically, the server first takes the detector as an endpoint and the corresponding two second enclosing lines as side lines to regionally enclose the second plane region to obtain a second enclosed region; then, the visual field range corresponding to the second enclosed region is taken as the second effective detection range.

[0119] Among them, one end of the second enclosing line is at the endpoint position, and the other end is within the circumferential length interval of the detector array, and the second enclosed region is used to enclose the entire second plane region.

[0120] In an exemplary embodiment, refer to Figure 7 , Figure 7 is a schematic structural diagram of an embodiment of the effective detection range of the detector in the circumferential field of view in the present application. Among them, as shown in a and b of FIG. Figure 7 , the circular region S1 is the display region of the detector array in the circumferential field of view, and each detector in the detector array is arranged at the edge position of the circular region S1 to detect signals from the second plane region S2 where the radiation source (i.e., the detection object) is located at the center of the region. Among them, the perimeter range of the circular region S1 is the circumferential length interval of the detector array.

[0121] Among them, as shown in Figure 7As shown in a) of the figure, for detector A, first, taking detector A as an endpoint and two second enclosing lines drawn from detector A as side lines, the entire second plane region S2 (i.e., the detection region of the detector array for the detection object) is regionally enclosed to obtain a second enclosed region S3; then, this second enclosed region S3 is taken as the second effective detection range of the detector array in the circumferential field of view. Among them, one end of the two second enclosing lines is at the endpoint position where detector A is located (i.e., detector A is the local detector), and the other end is at the positions where detectors A1 and A2 in the circumferential length interval of the detector array are located (i.e., detectors A1 and A2 are the opposite detectors), and the distance between both of the two second enclosing lines and the contour edge of the second plane region S2 is a preset safety distance, so that the second enclosed region S3 can enclose the entire second plane region S2.

[0122] Similarly, as Figure 7 shown in b) of the figure, for detector B, first, taking detector B as an endpoint and two second enclosing lines drawn from detector B as side lines, the entire second plane region S2 is regionally enclosed to obtain a second enclosed region S3; then, this second enclosed region S3 is taken as the second effective detection range of the detector array in the circumferential field of view. Among them, one end of the two second enclosing lines is at the endpoint position where detector B is located (i.e., detector B is the local detector), and the other end is at the positions where detectors B1 and B2 in the circumferential length interval of the detector array are located (i.e., detectors B1 and B2 are the opposite detectors), and the distance between both of the two second enclosing lines and the contour edge of the second plane region is a preset safety distance, so that the second enclosed region S3 can enclose the entire second plane region S2.

[0123] In this way, on the one hand, first, the detection scenario of the detector array for the detection object is determined through the data characteristics of the detected signal data set, and then the effective detection range of each detector is determined according to the corresponding detection scenario, so as to construct a medical detection image by using the target signal data within the corresponding effective detection range, thereby optimizing the construction process of the medical image, and compared with the method in the prior art, effectively improving the construction efficiency of the medical image with a standardized execution procedure and reducing the consumption of human and material resources; on the other hand, by first detecting the tracer signal emitted by the detection object by three-dimensionally enclosing the detection object, and then extracting the target signal data within the effective detection range of each detector from the tracer signal according to the detection scenario of the detector array to construct a medical detection image, the accuracy and feasibility of the construction of the medical image are improved, which is conducive to providing more effective reference information for subsequent medical treatment.

[0124] It should be understood that although Figures 2 - 7The steps in the flowchart are shown in sequence according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figures 2 - 7 at least some of the steps in Figures 2 - 7 may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least some of the steps or stages in other steps or other steps.

[0125] It can be understood that the same / similar parts between the various embodiments of the method in this specification can be referred to each other. Each embodiment focuses on the differences from other embodiments. For the relevant parts, refer to the descriptions of other method embodiments.

[0126] Figure 8 is a block diagram of a PET / CT system provided by an embodiment of the present application. Referring to Figure 8 , the PET / CT system 10A includes: a scanning bed 11A, a CT device 12A, a PET device 13A, a coincidence processing module 14A, and a display 15A.

[0127] Among them, the scanning bed 11A is used to support the object to be detected (i.e., the radioactive source) and position the object to be detected at the required position in the PET device 13A. In some embodiments, the detection object can lie on the scanning bed 11A. The scanning bed 11A can move under the control of the server and reach the required position of the PET device 13A. In some embodiments, the scanning bed 11A can have a relatively long axial field of view and a large circumferential field of view, such as an axial field of view of 2 meters.

[0128] Among them, the CT device 12A is used to scan the CT data of the detection object to reconstruct a CT image. Among them, the CT image can provide high-resolution anatomical structure information, including the detailed structures of bones, organs, and soft tissues. This information can help doctors accurately locate the specific position of the abnormal metabolic area in the PET image, thereby diagnosing diseases more accurately.

[0129] Among them, the PET device 13A is used to obtain a set of signal data by detecting signals for the detection object through a detector array. Among them, the detector array is used to surround the detection object three-dimensionally and detect the tracer signals emitted by the detection object to obtain signal data.

[0130] Among them, the coincidence processing module 14A is used to perform coincidence operations using the target signal data of the detectors within their respective effective detection ranges, so as to construct a medical detection image (i.e., a PET image) for the detection object according to the operation results of the target signal data.

[0131] Among them, the display 15A is used to display the reconstructed CT image and PET image on the display interface for doctors and researchers to analyze and diagnose.

[0132] In a specific implementation scenario, the PET / CT system 10A first statistically analyzes the signal data set collected by the PET device 13A in real time for the positron signal count rate to determine the current scanning protocol of the PET device 13A; then, according to the current scanning protocol of the PET device 13A, it determines the invalid scanning field of view area in the PET device 13A (i.e., determines the non-concerned area in the coincidence link); then, according to the invalid scanning field of view area, it determines the coincidence judgment link that needs to be closed in the PET device 13A (i.e., determines the coincidence limit range for the detector crystals in the coincidence link or the response lines outside the effective field of view); finally, it extracts the target signal data of the unclosed coincidence judgment link from the signal data set and constructs a PET image for the detection object based on the target signal data.

[0133] Figure 9 It is a block diagram of a medical image construction device provided by an embodiment of the present application. Refer to Figure 9 , the medical image construction device 10 includes: a signal detection module 11, a scene recognition module 12, a detection range module 13, and an image construction module 14.

[0134] Among them, the signal detection module 11 is used to obtain a signal data set obtained by the detector array for signal detection of the detection object; the detection object is a medical diagnosis and treatment object input with a radioactive tracer; the detector array is used to surround the detection object three-dimensionally and detect the tracer signals emitted by the detection object to obtain signal data;

[0135] Among them, the scene recognition module 12 is used to determine the detection scene of the detector array for the detection object based on the data characteristics of the signal data set;

[0136] Among them, the detection range module 13 is used to determine the effective detection range of each detector in the detector array when the detection scene is a target scene; among them, the effective detection range corresponding to the detector in different detection scenes is different;

[0137] Among them, the image construction module 14 is configured to extract the target signal data of each of the detectors within their respective effective detection ranges from the signal data set, and construct a medical detection image for the detection object based on the target signal data.

[0138] In some embodiments, in terms of determining the effective detection ranges of the detectors in the detector array, the apparatus 10 further includes:

[0139] Obtain the detection area of the detector array for the detection object;

[0140] Based on the detection area, determine the effective detection range corresponding to each of the detectors.

[0141] In some embodiments, the detection area includes a first planar area of the detection object within the axial field of view of the detector array and a second planar area within the circumferential field of view;

[0142] In terms of determining the effective detection range corresponding to each of the detectors based on the detection area, the apparatus 10 further includes:

[0143] Based on the first planar area, determine the first effective detection range of each of the detectors within the axial field of view; and

[0144] Based on the second planar area, determine the second effective detection range of each of the detectors within the circumferential field of view.

[0145] In some embodiments, in terms of determining the effective detection range corresponding to each of the detectors, the apparatus 10 further includes:

[0146] For the axial field of view, using the detector as an endpoint and the corresponding two first enclosing lines as side lines, enclose the first planar area to obtain a first enclosed area; use the visual field range corresponding to the first enclosed area as the first effective detection range; and

[0147] For the circumferential field of view, using the detector as an endpoint and the corresponding two second enclosing lines as side lines, enclose the second planar area to obtain a second enclosed area; use the visual field range corresponding to the second enclosed area as the second effective detection range;

[0148] Among them, one end of the first enclosing line is at the endpoint position, and the other end is within the axial length range of the detector array, and the first enclosed area is used to enclose at least part of the first planar area;

[0149] One end of the second surrounding line is at the end point position, and the other end is within the circumferential length range of the detector array, and the second surrounding area is used to surround all of the second plane areas.

[0150] In some embodiments, each of the detectors has at least one coincidence link within its respective effective detection range; one end in the coincidence link is the local detector corresponding to the effective detection range, and the other end is the opposite detector;

[0151] In terms of extracting, from the signal data set, the target signal data of each of the detectors within their respective effective detection ranges, the apparatus 10 further includes:

[0152] In the signal data set, extract the target tracer signals emitted by the local detector and the opposite detector on each coincidence link to which each of the detectors belongs within the corresponding effective detection range, and use the target tracer signals as the target signal data.

[0153] In some embodiments, in terms of determining, based on the data characteristics of the signal data set, the detection scenario of the detector array for the detection object, the apparatus 10 further includes:

[0154] Perform signal recognition on each signal data in the signal data set to determine the statistical data of the detection object emitting the tracer signal based on the radioactive tracer; the statistical data is used to characterize the activity level of the radioactive tracer in the detection object

[0155] Based on the activity level, determine the detection scenario of the detector array.

[0156] In some embodiments, in terms of performing signal recognition on each signal data in the signal data set to determine the statistical data of the detection object emitting the tracer signal based on the radioactive tracer, the apparatus 10 further includes:

[0157] Identify the preset radioactive signals and positron signals emitted by the detection object within a time window to obtain the data volume of the radioactive signals and the counting rate of the positron signals, and use the data volume and / or the counting rate as the statistical data for the tracer signal.

[0158] Figure 10 It is a block diagram of a computer device 20 provided by an embodiment of the present application. For example, the computer device 20 can be an electronic device, an electronic component, or a server array, etc. Refer to Figure 10, the computer device 20 includes a processor 21, and the processor 21 can further be a set of processors, which may include one or more processors. The computer device 20 also includes memory resources represented by a memory 22, where a computer program, such as an application program, is stored on the memory 22. The computer program stored in the memory 22 may include one or more modules, each corresponding to a set of executable instructions. In addition, when the processor 21 is configured to execute the computer program, it implements the method for constructing a medical image as described above.

[0159] In some embodiments, the computer device 20 is an electronic device, and the computing system in the electronic device can run one or more operating systems, including any of the operating systems discussed above and any commercial server operating systems. The computer device 20 can also run any of a variety of additional server applications and / or middleware applications, including HTTP (Hypertext Transfer Protocol) servers, FTP (File Transfer Protocol) servers, CGI (Common Gateway Interface) servers, super servers, database servers, etc. Exemplary database servers include, but are not limited to, database servers commercially available from (International Business Machines), etc.

[0160] In some embodiments, the processor 21 generally controls the overall operation of the computer device 20, such as operations associated with display, data processing, data communication, and recording operations. The processor 21 may include one or more processor components to execute the computer program to complete all or part of the steps of the above-described method. In addition, the processor components may include one or more modules to facilitate the interaction between the processor components and other components. For example, the processor components may include a multimedia module to facilitate controlling the interaction between the user computer device 20 and the processor 21 using the multimedia components.

[0161] In some embodiments, the processor component in the processor 21 may also be referred to as a CPU (Central Processing Unit). The processor component may be an electronic chip with the ability to process signals. The processor may also be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor component, etc. Additionally, the processor component may be implemented jointly by integrated circuit chips.

[0162] In some embodiments, the memory 22 is configured to store various types of data to support the operation of the computer device 20. Examples of such data include instructions for any application or method operating on the computer device 20, acquired data, messages, pictures, videos, etc. The memory 22 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disks, optical disks, or graphene memory.

[0163] In some embodiments, the memory 22 may be a memory module, a TF card, etc., and can store all the information in the computer device 20. The input raw data, computer programs, intermediate operation results, and final operation results are all saved in the memory 22. In some embodiments, it stores and retrieves information according to the locations specified by the processor. In some embodiments, with the memory 22, the computer device 20 has the memory function and can ensure normal operation. In some embodiments, the memory 22 of the computer device 20 can be classified into a main memory (RAM) and an auxiliary memory (external memory) according to its use, or there is also a classification method of dividing it into an external memory and an internal memory. The external memory is usually a magnetic medium or an optical disk, etc., which can store information for a long time. The RAM refers to the storage component on the motherboard, which is used to store the data and programs being currently executed, but only temporarily stores the programs and data. When the power is turned off or interrupted, the data will be lost.

[0164] In some embodiments, the computer device 20 may further include: a power supply component 23 configured to perform power management of the computer device 20, a wired or wireless network interface 24 configured to connect the computer device 20 to a network, and an input / output (I / O) interface 25. The computer device 20 may operate based on an operating system stored in the memory 22, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, or the like.

[0165] In some embodiments, the power supply component 23 provides power to various components of the computer device 20. The power supply component 23 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the computer device 20.

[0166] In some embodiments, the wired or wireless network interface 24 is configured to facilitate wired or wireless communication between the computer device 20 and other devices. The computer device 20 may access a wireless network based on communication standards, such as WiFi, carrier networks (such as 2G, 3G, 4G, or 5G), or a combination thereof.

[0167] In some embodiments, the wired or wireless network interface 24 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the wired or wireless network interface 24 further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0168] In some embodiments, the input / output (I / O) interface 25 provides an interface between the processor 21 and a peripheral interface module, and the peripheral interface module may be a keyboard, a click wheel, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

[0169] Figure 11 It is a block diagram of a computer-readable storage medium 30 provided by an embodiment of the present application. A computer program 31 is stored on the computer-readable storage medium 30, and when the computer program 31 is executed by a processor, the method for constructing a medical image as described above is implemented.

[0170] If the units integrated in each functional unit in the embodiments of the present application are implemented in the form of software functional units and sold or used as independent products, they can be stored in the computer-readable storage medium 30. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer-readable storage medium 30 contains a computer program 31 including several instructions to enable a computer device (which may be a personal computer, a system server, or a network device, etc.), an electronic device (such as an MP3, an MP4, etc., can also be an intelligent terminal such as a mobile phone, a tablet computer, a wearable device, etc., or a desktop computer, etc.) or a processor to execute all or part of the steps of the methods in various embodiments of the present application.

[0171] Figure 12 It is a block diagram of a computer program product 40 provided by an embodiment of the present application. The computer program product 40 includes program instructions 41, and the program instructions 41 can be executed by the processor of the server 20 to implement the method for constructing a medical image as described above.

[0172] Those skilled in the art should understand that the embodiments of the present application can provide a method for constructing a medical image, a medical image construction device 10, a computer device 20, a computer-readable storage medium 30, or a computer program product 40. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product 40 implemented on one or more computer program instructions 41 (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0173] The present application is described with reference to the flowcharts and / or block diagrams of the method for constructing a medical image, the medical image construction device 10, the computer device 20, the computer-readable storage medium 30, or the computer program product 40 in the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by the computer program product 40. These computer program products 40 can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the program instructions 41 executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0174] These computer program products 40 can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the program instructions 41 stored in the computer program product 40 produce a manufactured article including instruction means that implement the functions specified in one or more processes and / or blocks Figure 1 in one or more processes and / or blocks Figure 1 specified in the block or blocks.

[0175] These program instructions 41 can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, whereby the program instructions 41 executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes and / or blocks Figure 1 in one or more processes and / or blocks Figure 1 specified in the block or blocks.

[0176] It should be noted that the above-mentioned various methods, devices, electronic devices, computer-readable storage media, computer program products, etc. may also include other implementation manners according to the description of the method embodiments. The specific implementation manners can refer to the description of the relevant method embodiments and will not be elaborated herein one by one.

[0177] Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include known common general knowledge or conventional technical means in the technical field not disclosed by the present disclosure. The specification and examples are only to be considered as exemplary, and the true scope and spirit of the present disclosure are pointed out by the claims.

[0178] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A method for constructing a medical image, characterized in that, The method includes: Obtaining a set of signal data obtained by a detector array for signal detection of a detection object; the detection object is a medical diagnosis and treatment object input with a radioactive tracer; the detector array is used to surround the detection object three-dimensionally and detect the tracer signals emitted by the detection object to obtain signal data; Determining the detection scenario of the detector array for the detection object based on the data characteristics of the set of signal data; When the detection scenario is a target scenario, determining the effective detection range of each detector in the detector array; wherein, the effective detection range corresponding to the detector in different detection scenarios is different; Extracting the target signal data of each detector within its respective effective detection range from the set of signal data, and constructing a medical detection image for the detection object based on the target signal data.

2. The method according to claim 1, characterized in that, The determining the effective detection range of each detector in the detector array includes: Obtaining the detection area of the detector array for the detection object; Determining the effective detection range corresponding to each detector based on the detection area.

3. The method according to claim 2, characterized in that, The detection area includes a first planar area of the detection object within the axial field of view of the detector array and a second planar area within the circumferential field of view; The determining the effective detection range corresponding to each detector based on the detection area includes: Determining the first effective detection range of each detector within the axial field of view based on the first planar area; and Determining the second effective detection range of each detector within the circumferential field of view based on the second planar area.

4. The method according to claim 3, characterized in that, The determining the effective detection range corresponding to each detector includes: For the axial field of view, using the detector as an endpoint and two corresponding first enclosing lines as side lines, enclosing the first planar area to obtain a first enclosed area; taking the field of view range corresponding to the first enclosed area as the first effective detection range; and For the circumferential field of view, using the detector as an endpoint and two corresponding second enclosing lines as side lines, enclosing the second planar area to obtain a second enclosed area; taking the field of view range corresponding to the second enclosed area as the second effective detection range; Wherein, one end of the first enclosing line is at the endpoint position, and the other end is within the axial length interval of the detector array, and the first enclosed area is used to enclose at least part of the first planar area; One end of the second enclosing line is at the endpoint position, and the other end is within the circumferential length interval of the detector array, and the second enclosed area is used to enclose the entire second planar area.

5. The method according to claim 1, characterized in that, Each detector has at least one coincidence link within its respective effective detection range; one end in the coincidence link is the local detector corresponding to the effective detection range, and the other end is the opposite detector; The extracting the target signal data of each detector within its respective effective detection range from the set of signal data includes: In the signal data set, extract the target tracer signals detected by the local detector and the remote detector on each coincidence link to which each detector belongs within the corresponding effective detection range, and use the target tracer signals as target signal data.

6. The method according to claim 1, characterized in that, Determining the detection scenario of the detector array for the detection object based on the data characteristics of the signal data set includes: Performing signal recognition on each signal data in the signal data set to determine the statistical data of the detection object emitting tracer signals based on the radioactive tracer; the statistical data is used to characterize the activity level of the radioactive tracer in the detection object; Based on the activity level, determine the detection scenario of the detector array.

7. The method according to claim 6, characterized in that, Performing signal recognition on each signal data in the signal data set to determine the statistical data of the detection object emitting tracer signals based on the radioactive tracer includes: Identifying the preset radioactive signals and positron signals emitted by the detection object within a time window, obtaining the data volume of the radioactive signals and the counting rate of the positron signals, and using the data volume and / or the counting rate as the statistical data for the tracer signals.

8. An apparatus for constructing a medical image, characterized in that, The device includes: A signal detection module for obtaining a signal data set obtained by a detector array detecting signals for a detection object; the detection object is a medical diagnosis and treatment object input with a radioactive tracer; the detector array is used to surround the detection object three-dimensionally and detect the tracer signals emitted by the detection object to obtain signal data; A scenario recognition module for determining the detection scenario of the detector array for the detection object based on the data characteristics of the signal data set; A detection range module for determining the effective detection range of each detector in the detector array when the detection scenario is a target scenario; wherein, the effective detection range corresponding to the detector in different detection scenarios is different; An image construction module for extracting the target signal data of each detector within its respective effective detection range from the signal data set and constructing a medical detection image for the detection object based on the target signal data.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

Images