An imaging method and system

Abstract

An imaging method and system, the method comprising: acquiring a plurality of partition input functions of a target object located at a plurality of beds, the plurality of beds comprising a target bed and a reference bed, adjacent beds in the plurality of beds corresponding scanning regions having an overlapping scanning region; acquiring overlapping input function information corresponding to the overlapping scanning region; correcting a reference partition input function corresponding to the reference bed based on the overlapping input function information, and determining a continuous input function corresponding to the target bed.

Description

Technical Field

[0001] This manual relates to the field of medical technology, and in particular to an imaging method and system. Background Technology

[0002] PET parametric imaging and its applications are still in their early stages of development. A major requirement for parametric imaging is obtaining three-dimensional distribution information of drugs and radionuclides over time. However, considering the low drug dose in PET and the limited amount of radionuclide attenuation information, achieving dynamic imaging with limited information over a short timeframe is inherently challenging. Furthermore, parametric imaging requires a continuous input function as the basis for computation. When lesions are distributed over a range wider than the short axis, short-axis imaging becomes even more difficult to achieve continuous acquisition, obtaining an input function and lesion region image that fully covers the entire body area.

[0003] Therefore, there is an urgent need for a method to collect continuous input functions. Summary of the Invention

[0004] One embodiment of this specification provides an imaging method, the method comprising: acquiring multiple partition input functions of a target object located in multiple beds, the multiple beds including a target bed and a reference bed, the scanning areas corresponding to adjacent beds in the multiple beds having overlapping scanning areas; acquiring overlapping input function information corresponding to the overlapping scanning areas; correcting the reference partition input function corresponding to the reference bed based on the overlapping input function information; and determining the continuous input function corresponding to the target bed.

[0005] In some embodiments, obtaining multiple partition input functions for a target object located in multiple beds includes: for each of the multiple beds, obtaining scan data of the target object located in that bed; and determining the partition input function corresponding to that bed based on the scan data.

[0006] In some embodiments, the step of correcting the reference partition input function corresponding to the reference bed based on the overlapping input function information to determine the continuous input function corresponding to the target bed includes: determining the ratio of the partition input functions of adjacent beds corresponding to each overlapping region; and determining at least a portion of the continuous input function based on the ratio and the partition input function corresponding to the reference region outside the overlapping region in the scan region corresponding to the last reference bed in the reference beds.

[0007] In some embodiments, the reference bed includes a first reference bed, and the overlapping scan region includes a first overlapping scan region where the scan region corresponding to the target bed overlaps with the scan region corresponding to the first reference bed. The step of correcting the reference partition input function corresponding to the reference bed based on the overlapping input function information to determine the continuous input function corresponding to the target bed includes: obtaining target function information of the target input function in a first time period; obtaining first function information of the first reference input function in the first time period; obtaining a first ratio between the target function information and the first function information; and correcting the second function information of the first reference input function in a second time period based on the first ratio to obtain at least a portion of the continuous input function in the second time period.

[0008] In some embodiments, obtaining the first ratio of the target function information to the first function information includes:

[0009] The average value of the ratio of the objective function information to the first function information at each time point within the first time period is obtained, and the average value is used as the first ratio.

[0010] In some embodiments, the reference bed further includes a second reference bed, and the overlapping scan area further includes a second overlapping scan area of ​​the scan area corresponding to the first reference bed and the scan area corresponding to the second reference bed. The step of correcting the reference partition input function corresponding to the reference bed based on the overlapping input function information to determine the continuous input function corresponding to the target bed further includes: obtaining the second function information of the first reference input function before correction in the second time period; obtaining the third function information of the second reference input function in the second time period; obtaining a second ratio between the second function information and the third function information; and correcting the fourth function information of the second reference input function in the third time period based on the second ratio to obtain at least a portion of the continuous input function in the third time period.

[0011] In some embodiments, the step of correcting the fourth function information of the second reference input function in the third time period based on the second ratio to obtain at least a portion of the continuous input function in the third time period includes: obtaining the average value of the ratio of the second function information to the third function information at each time point in the second time period, and using the average value as the second ratio; and correcting the fourth function information of the second reference input function in the third time period based on the first ratio and the second ratio to obtain at least a portion of the continuous input function in the third time period.

[0012] In some embodiments, the method further includes: performing multiple rounds of scanning, each round of scanning including scanning of multiple beds; and correcting the reference partition input function corresponding to the reference bed based on the overlapping input function information to determine the continuous input function corresponding to the target bed, which further includes: correcting the reference partition input function corresponding to the reference bed based on the overlapping input function information within the same scanning round to determine the continuous input function corresponding to the target bed in the scanning round.

[0013] One embodiment of this specification provides an imaging system, comprising: a first acquisition module, configured to acquire multiple partition input functions of a target object located at multiple beds, the multiple beds including a target bed and a reference bed, wherein adjacent beds in the multiple beds have overlapping scanning regions; a second acquisition module, configured to acquire overlapping input function information corresponding to the overlapping scanning regions; and a determination module, configured to correct the reference partition input function corresponding to the reference bed based on the overlapping input function information, and determine the continuous input function corresponding to the target bed.

[0014] One embodiment of this specification provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions, the computer executes the imaging method as described above.

[0015] Existing parametric imaging mainly relies on a fixed imaging method on a single bed, which acquires the curve of PET images on the time axis through continuous long-term scanning.

[0016] The embodiments in this specification propose multi-bed scanning, which can broaden the amount of short-axis information and obtain a wider range of continuous information, such as input function curves, target lesion curves, continuous imaging, and even whole-body imaging. Attached Figure Description

[0017] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0018] Figure 1 These are schematic diagrams illustrating application scenarios of exemplary imaging systems according to some embodiments of this specification;

[0019] Figure 2 This is a block diagram of an exemplary imaging system shown according to some embodiments of this specification;

[0020] Figure 3 This is a flowchart illustrating an exemplary imaging method according to some embodiments of this specification;

[0021] Figure 4 This is a schematic diagram of an imaging method according to some embodiments of this specification;

[0022] Figure 5 This is a schematic diagram of the input function according to some embodiments of this specification; Detailed Implementation

[0023] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0024] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0025] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0026] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0027] Figure 1 These are schematic diagrams illustrating application scenarios of exemplary imaging systems according to some embodiments of this specification. In some embodiments, such as Figure 1 As shown, the application scenario 100 of the imaging system may include at least an imaging device 110, a processing device 120, a terminal device 130, a storage device 140, and a network 150.

[0028] Imaging device 110 can scan a target object within a detection area or scanning area to obtain scan data of the target object. In some embodiments, the target object may include biological objects and / or non-biological objects. For example, the target object may include a patient, an artificial object, etc. In some embodiments, the target object may include a specific part of the body, such as the head, chest, abdomen, etc., or any combination thereof. In some embodiments, the target object may include a specific organ, such as the heart, esophagus, trachea, bronchi, stomach, gallbladder, small intestine, colon, bladder, ureter, uterus, fallopian tubes, etc., or any combination thereof. In some embodiments, the target object may include a region of interest (ROI), such as a tumor, a node, etc.

[0029] In some embodiments, the imaging device 110 may be or include a PET (Positron Emission Computed Tomography) imaging device. In some embodiments, the imaging device 110 may include a single-modality scanner and / or a multimodality scanner, for example, a multimodality scanner may include a PET-CT imaging device, a PET-MRI imaging device, or any combination thereof. The above description of the imaging device is for illustrative purposes only and is not intended to limit the scope of this specification.

[0030] The processing device 120 can process data and / or information acquired from the imaging device 110, the terminal device 130, the storage device 140, and / or other components of the imaging system in the application scenario 100. For example, the processing device 120 can acquire image data from the imaging device 110, the terminal device 130, and the storage device 140, and analyze and process it.

[0031] In some embodiments, processing device 120 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processing device 120 may be local or remote. For example, processing device 120 may access information and / or data from imaging device 110, terminal device 130, and / or storage device 140 via network 150. Alternatively, processing device 120 may be directly connected to imaging device 110, terminal device 130, and / or storage device 140 to access information and / or data. In some embodiments, processing device 120 may be implemented on a cloud platform. For example, the cloud platform may include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, inter-cloud cloud, multi-cloud, etc., or any combination thereof.

[0032] In some embodiments, the processing device 120 and the imaging device 110 may be integrated into one unit. In some embodiments, the processing device 120 and the imaging device 110 may be directly or indirectly connected to work together to implement the methods and / or functions described herein.

[0033] In some embodiments, the processing device 120 may include input and / or output devices. These input and / or output devices enable interaction with the user (e.g., setting scan parameters, etc.). In some embodiments, the input and / or output devices may include a display screen, keyboard, mouse, microphone, etc., or any combination thereof.

[0034] Terminal device 130 can communicate and / or connect to imaging device 110, processing device 120, and / or storage device 140. In some embodiments, interaction with a user can be achieved through terminal device 130. In some embodiments, terminal device 130 may include mobile device 131, tablet computer 132, laptop computer 133, etc., or any combination thereof. In some embodiments, terminal device 130 (or all or part of its functions) may be integrated into processing device 120.

[0035] Storage device 140 may store data, instructions, and / or any other information. In some embodiments, storage device 140 may store data (e.g., scan parameters, image data, input functions, etc.) acquired from imaging device 110, processing device 120, terminal device 130, and / or other sources. In some embodiments, storage device 140 may store data and / or instructions used by processing device 120 to perform or use in order to complete the exemplary methods described herein.

[0036] In some embodiments, storage device 140 may include one or more storage components, each of which may be a separate device or part of another device. In some embodiments, storage device 140 may include random access memory (RAM), read-only memory (ROM), mass storage, removable memory, volatile read-write memory, and any combination thereof. In some embodiments, storage device 140 may be implemented on a cloud platform. In some embodiments, storage device 140 may be part of imaging device 110, processing device 120, and / or terminal device 130.

[0037] Network 150 may include any suitable network capable of facilitating information and / or data exchange. In some embodiments, at least one component of application scenario 100 of the imaging system (e.g., imaging device 110, processing device 120, terminal device 130, storage device 140) may exchange information and / or data with at least one other component of application scenario 100 of the imaging system via network 150. For example, processing device 120 may acquire image data from imaging device 110 via network 150.

[0038] It should be noted that the above description of application scenario 100 of the imaging system is provided for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can make various modifications or variations based on the description in this specification. For example, application scenario 100 of the imaging system can achieve similar or different functions on other devices. However, these changes and modifications will not depart from the scope of this specification.

[0039] Figure 2 This is a block diagram of an exemplary imaging system according to some embodiments of this specification. Figure 2 As shown, in some embodiments, the imaging system 200 may include a first acquisition module 210, a second acquisition module 220, and a determination module 230. In some embodiments, the functions corresponding to the imaging system 200 may be performed by the processing device 120.

[0040] The first acquisition module 210 can be used to acquire multiple partition input functions for a target object located in multiple beds. The multiple beds include the target bed and reference beds, and the scanning areas of adjacent beds have overlapping scanning areas. More information on acquiring multiple partition input functions can be found in [reference needed]. Figure 3 Step 310 and its related description.

[0041] The second acquisition module 220 can be used to acquire the overlapping input function information corresponding to the overlapping scan region. For more information on acquiring overlapping input function information, please refer to [link / reference needed]. Figure 3 Step 320 and its related description.

[0042] The determination module 230 can be used to correct the reference partition input function corresponding to the reference bed based on the overlap input function information, and determine the continuous input function corresponding to the target bed. For more information on determining continuous input functions, please refer to [link to relevant documentation]. Figure 3 Step 330 and its related description.

[0043] It should be understood that Figure 2The systems and modules shown can be implemented in various ways. For example, they can be implemented by hardware, software, or a combination of both. The systems and modules in this specification can be implemented not only by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips and transistors, or programmable hardware devices such as field-programmable gate arrays and programmable logic devices, but also by software, for example, executed by various types of processors, or by a combination of the aforementioned hardware circuits and software (e.g., firmware).

[0044] It should be noted that the above description of the system and its modules is for illustrative purposes only and should not be construed as limiting this specification to the scope of the illustrated embodiments. It is understood that those skilled in the art, after understanding the principles of this system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from these principles.

[0045] Figure 3 This is a flowchart illustrating an exemplary imaging method according to some embodiments of this specification. In some embodiments, process 300 may be executed by processing device 120 or imaging system 200. For example, process 300 may be stored in a storage device (e.g., storage device 140, storage unit of processing device 120) in the form of a program or instructions, and executed by the processor or... Figure 2 When the module shown executes a program or instructions, it can implement process 300. In some embodiments, process 300 may be completed using one or more additional operations not described below, and / or not through one or more operations discussed below. Additionally, as Figure 3 The order of operations shown is not restrictive.

[0046] Step 310: Obtain multiple partition input functions for the target object located in multiple beds, including the target bed and reference beds, wherein the scanning areas corresponding to adjacent beds in the multiple beds have overlapping scanning areas. In some embodiments, step 310 may be performed by the processing device 120 or the first acquisition module 210.

[0047] Multiple beds refer to the multiple beds used for whole-body or half-body scans, each corresponding to a different scanning range, due to the longitudinal limitation of the detector. A target bed is a bed whose scanning range covers a specific area (tissue, organ, etc.). For example, a heart bed covering the heart region, or a bladder bed covering the bladder region. Reference beds are one or more beds other than the target bed among the multiple beds; for example, a first reference bed, a second reference bed, etc. Reference beds may or may not be adjacent to the target bed.

[0048] The scanning areas of adjacent beds in a multi-bed system have overlapping scanning areas. That is, the scanning area of ​​each bed (excluding the first and last beds) includes the scanning area of ​​the bed preceding it (R is a percentage), and the scanning area of ​​the bed following it (R is also a percentage). The percentage of overlapping scanning areas R can be set based on experience and / or requirements; for example, R can be set to 25%, 30%, 50%, etc.

[0049] For example, such as Figure 4 As shown, the scanning area 410 corresponding to the target bed (cardiac bed) has an overlapping scanning area 412 with the scanning area 420 corresponding to the first reference bed, the scanning area 420 corresponding to the first reference bed has an overlapping scanning area 423 with the scanning area 430 corresponding to the second reference bed, and the scanning area 430 corresponding to the second reference bed has an overlapping scanning area 434 with the scanning area 440 corresponding to the third reference bed.

[0050] The input function is the time-activity curve of a radionuclide and / or the standardized uptake value (SUV) curve of a drug within a voxel in the scanned area. For example, the time-activity curve of a radionuclide and / or the standardized uptake value (SUV) curve of a drug within a voxel in the descending aorta region of the scanned area. The input function can be used in subsequent parametric image reconstruction, calculations of organ blood flow, and other calculations. In some embodiments, the x-axis of the input function curve is time, and the y-axis is the activity of the radionuclide. In some embodiments, the x-axis of the input function curve is time, and the y-axis is the standardized uptake value (SUV) of the drug. It should be noted that the input function is the input information of the parametric imaging model and can be obtained by analyzing blood information in the image using imaging methods, for example, using blood pools such as the aorta and left ventricle as image information input sources to obtain the input function.

[0051] In some embodiments, multiple beds where the target object is located correspond to multiple partition input functions. In some embodiments, each bed may correspond to one partition input function or a portion thereof. For example, as... Figure 5 As shown, the target bed corresponds to the target partition input function 510, the first reference bed corresponds to the first reference partition input function 520, and the second reference bed corresponds to the second reference partition input function 530.

[0052] In some embodiments, the first acquisition module 210 can obtain multiple partition input functions corresponding to the scanning time period by scanning target objects located at multiple beds. For example, Figure 5As shown, scanning the scanning area 410 corresponding to the target bed (cardiac bed) during the time period t0-t2 yields the target partition input function 510 for the target bed during the time period t0-t2; scanning the scanning area 420 corresponding to the first reference bed during the time period t1-t3 yields the first reference partition input function 520 for the first reference bed during the time period t1-t3; and scanning the scanning area 430 corresponding to the second reference bed during the time period t2-t4 yields the second reference partition input function 530 for the second reference bed during the time period t2-t4.

[0053] In some embodiments, the first acquisition module 210 may acquire multiple partition input functions for multiple beds where the target object is located through the following steps. For each of the multiple beds, firstly, the first acquisition module 210 may acquire scan data of the target object located at that bed; secondly, the first acquisition module 210 may determine the partition input function corresponding to that bed based on the scan data.

[0054] Taking PET imaging as an example, in some embodiments, the first acquisition module 210 can obtain scan data by scanning the target object located at the bed position, such as raw data stored in Listmode, Sinogram, or histo-images mode. In some embodiments, the first acquisition module 210 can convert the scan data into image data using methods such as Radon transform. In some embodiments, the first acquisition module 210 can obtain the average activity value of a portion of specific voxels (e.g., voxels in the descending aorta region) within the scan area corresponding to the bed position from the image data of each frame image, and use this as the value of the ordinate corresponding to the time point of that frame image, thereby obtaining the curve of the input function during the scan time of the bed position. In some embodiments, the first acquisition module 210 can determine the partition input function corresponding to the bed position based on the scan data in other ways. For example, the scan data can be input into a trained machine learning model to obtain the corresponding partition input function.

[0055] In some embodiments, the first acquisition module 210 may acquire multiple partition input functions of the target object located in multiple beds in other ways, such as by arterial continuous blood sampling or by importing input functions based on population information.

[0056] In some embodiments, the first acquisition module 210 can perform multiple rounds of scanning on the target object, with each round including scanning of multiple beds. In some embodiments, the first acquisition module 210 can acquire multiple partition input functions of the target object located in multiple beds in each round of scanning to generate continuous input functions within that scanning round.

[0057] Step 320: Obtain the overlapping input function information corresponding to the overlapping scan region. In some embodiments, step 320 may be performed by the processing device 120 or the second acquisition module 220.

[0058] In some embodiments, the second acquisition module 220 can acquire the overlapping input function information corresponding to the overlapping scan region by means of truncating the partition input function, and then use it as correction information for time and dose differences during multi-bed scanning. For example, Figure 5 As shown, the second acquisition module 220 can obtain the overlapping input function information of the overlapping scan region 412 in the t1-t2 time period by extracting the partition input function 510 obtained by scanning the scan region 410 corresponding to the target bed (cardiac bed); by extracting the first reference partition input function 520 obtained by scanning the scan region 420 corresponding to the first reference bed, it can obtain the overlapping input function information of the overlapping scan region 412 in the t1-t2 time period; by extracting the first reference partition input function 520 obtained by scanning the scan region 420 corresponding to the first reference bed, it can obtain the overlapping input function information of the overlapping scan region 423 in the t2-t3 time period; and by extracting the second reference partition input function 530 obtained by scanning the scan region 430 corresponding to the second reference bed, it can obtain the overlapping input function information of the overlapping scan region 423 in the t2-t3 time period.

[0059] It is worth noting that, for the sake of simplicity, this explanation... Figure 5 The scan area is drawn based on an overlap ratio R of 50%. In other words, the first 50% of the scan area corresponding to each bed (excluding the first and last beds) overlaps with the scan area corresponding to the previous bed, and the last 50% overlaps with the scan area corresponding to the next bed.

[0060] Step 330: Based on the overlapping input function information, the reference partition input function corresponding to the reference bed is corrected to determine the continuous input function corresponding to the target bed. In some embodiments, step 330 may be performed by the processing device 120 or the determining module 230.

[0061] The continuous input function corresponding to the target bed refers to the complete and uninterrupted input function corresponding to the target bed across the entire scanning time interval. For example, the complete and uninterrupted input function corresponding to the target bed during the time interval t0-t4. Through step 310, the first acquisition module 210 can only obtain the input function information for the scanning time interval of the target bed, for example, the target partition input function corresponding to the target bed within the time interval t0-t2. In some embodiments, the determining module 230 can correct the reference partition input function corresponding to the reference bed based on the overlapping input function information, thereby obtaining the input functions corresponding to the target bed for other scanning time intervals, and thus obtaining the continuous input function corresponding to the target bed across the entire scanning time interval. For example, such as Figure 5 As shown, the determining module 230 can correct the first reference partition function of other scanning areas (outside the overlapping scanning areas) of the first reference bed scanned during the t2-t3 time period based on the overlap input function information of the overlapping scanning areas of the target bed and the first reference bed scanned during the t1-t2 time period, thereby obtaining the target input function corresponding to the target bed during the t2-t3 time period. For example, the determining module 230 can also correct the second reference partition function of other scanning areas of the second reference bed scanned during the t3-t4 time period based on the overlap input function information of the overlapping scanning areas of the target bed and the first reference bed scanned during the t1-t2 time period, and the overlap input function information of the overlapping scanning areas of the first reference bed and the second reference bed scanned during the t2-t3 time period, thereby obtaining the target input function corresponding to the target bed during the t3-t4 time period.

[0062] In some embodiments, the reference bed includes a first reference bed, and the overlapping scan region includes a first overlapping scan region where the scan region corresponding to the target bed overlaps with the scan region corresponding to the first reference bed. In some embodiments, the determining module 230 can correct the first reference input function corresponding to the first reference bed based on the input function information of the first overlapping scan region through the following steps to obtain at least a portion of the continuous input function.

[0063] First, module 230 determines that it can obtain the target function information of the target input function in the first time period. The first time period is the time period for scanning the first overlapping scan region, and the target input function is the input function of the corresponding target bed. For example, it obtains the target function information of the target input function 510 in the time period t1-t2.

[0064] Secondly, module 230 can obtain the first function information of the first reference input function in the first time period. The first reference input function is the input function corresponding to the first reference bed. For example, it can obtain the first function information of the first reference input function 520 in the time period t1-t2.

[0065] Furthermore, module 230 can obtain a first ratio between the target function information and the first function information. For example, obtaining a first ratio between the target function information and the first function information.

[0066] In some embodiments, the determining module 230 may obtain the average value of the ratio of the objective function information to the first function information at each time point within the first time period, and use the average value as the first ratio.

[0067] Finally, the determining module 230 can correct the second function information of the first reference input function in the second time period based on the first ratio to obtain at least a portion of the continuous input function in the second time period. For example, based on the first ratio, the second function information of the first reference input function 520 in the time period t2-t3 can be corrected to obtain at least a portion of the continuous input function in the time period t2-t3.

[0068] In some embodiments, the determining module 230 may obtain at least a portion of the continuous input function in the second time period based on the following formula (1).

[0069] P1(t 23 ) = mean(f 12 (t 12 ))×P2(t 23 (1)

[0070] Where, mean(f 12 (t 12 P2(t) represents the average ratio of the target input function to the first input function at each time point in the time interval t1-t2. 23 P1(t) is the input function for other regions outside the first overlapping scan region within the scan region corresponding to the first reference bed, i.e., the input function for the t2-t3 time period when scanning these other regions. 23 () represents at least a portion of the continuous input function corresponding to the target bed during the corrected time period t2-t3.

[0071] In some embodiments, the reference bed further includes a second reference bed, and the overlapping scan region further includes a second overlapping scan region of the scan region corresponding to the first reference bed and the scan region corresponding to the second reference bed. The determining module 230 can correct the second reference input function corresponding to the second reference bed based on the input function information of the first overlapping scan region and the input function information of the second overlapping scan region through the following steps to obtain at least a portion of the continuous input function.

[0072] First, module 230 determines that it can obtain the second function information of the first reference input function before correction in the second time period. The second time period is the time period for scanning the second overlapping scan region. For example, it obtains the second function information of the first reference input function 520 before correction in the time period t2-t3.

[0073] Secondly, module 230 can obtain the third function information of the second reference input function in the second time period. The second reference input function is the input function corresponding to the second reference bed. For example, it can obtain the third function information of the second reference input function 530 in the time period t2-t3.

[0074] Furthermore, module 230 can obtain a second ratio between the second function information and the third function information. For example, obtaining a second ratio between the second function information and the third function information.

[0075] In some embodiments, the determining module 230 may obtain the average value of the ratio of the second function information to the third function information at each time point within the second time period, and use the average value as the second ratio.

[0076] Finally, the determining module 230 can correct the fourth function information of the second reference input function in the third time period based on the second ratio to obtain at least a portion of the continuous input function in the third time period. For example, based on the second ratio, the fourth function information 544 of the second reference input function in the t3-t4 time period can be corrected to obtain at least a portion of the continuous input function in the t3-t4 time period.

[0077] In some embodiments, the determining module 230 may correct the fourth function information of the second reference input function in the third time period based on the first ratio and the second ratio to obtain at least a portion of the continuous input function in the third time period. For example, the determining module 230 may obtain at least a portion of the continuous input function in the third time period based on the following formula (2).

[0078] P1(t 34 ) = mean(f 12 (t 12 ))×mean(f 23 (t 23 ))×P3(t 34 (2)

[0079] Where, mean(f 12 (t 12 )) represents the average ratio of the target input function to the first input function at each time point in the time interval t1-t2; mean(f 23 (t 23P3(t) represents the average ratio of the first input function to the second input function at each time point in the time interval t2-t3. 34 P1(t) is the input function for other regions outside the second overlapping scan region within the scan area corresponding to the second reference bed, i.e., the input function for the t3-t4 time period when scanning these other regions. 34 () represents at least a portion of the continuous input function corresponding to the target bed during the corrected time period t3-t4.

[0080] In some embodiments, the determining module 230 may determine the ratio of the partition input functions of adjacent beds corresponding to each overlapping region. In some embodiments, the determining module 230 may determine at least a portion of the continuous input function based on the ratio and the partition input function corresponding to the reference region outside the overlapping region in the scan region corresponding to the last reference bed in the reference beds. The last reference bed in the reference beds refers to the last scanned bed and / or the bed farthest from the target bed. In some embodiments, at least a portion of the continuous input function (e.g., the last part of the continuous input function) may be obtained by the following formula (3).

[0081] P1(t n,n+1 ) = mean(f 12 (t 12 ))×mean(f 23 (t 23 ))×…×mean(f n-1,n (t n-1,n ))×P n (t n,n+1 (3)

[0082] Where, mean(f 12 (t 12 )) represents the average ratio of the target input function to the first input function at each time point in the time interval t1-t2; mean(f 23 (t 23 )) represents the average ratio of the first input function to the second input function at each time point in the time interval t2-t3. n (t n,n+1 ) is the input function for the regions outside the nth overlapping scan region within the scan region corresponding to the nth reference bed, i.e., the t function for scanning these other regions. n -t n+1 The input function for the time interval. P1(t) n,n+1 ) represents the corrected t n -t n+1 The time period is at least a portion of the continuous input function corresponding to the target bed.

[0083] In some embodiments, the determining module 230 can concatenate the target partition input function and the corrected input functions of each reference partition to obtain a continuous input function for the corresponding target bed. This continuous input function is analogous to the drug concentration curve obtained after multiple blood collections. In some embodiments, the determining module 230 can perform curve smoothing on the concatenated continuous input function to ensure the continuity of the curve.

[0084] In some embodiments, the processing device 120 can perform multiple scans on the target object, with each scan including multiple beds. For example, each scan includes scanning the target bed, the first reference bed, the second reference bed, ..., and the last reference bed sequentially from head to toe. Alternatively, each scan includes scanning the last reference bed, ..., the second reference bed, the first reference bed, and the target bed sequentially from foot to head.

[0085] In some embodiments, the processing device 120 can correct the reference partition input function corresponding to the reference bed based on the overlapping input function information within the same scanning round, and determine the continuous input function corresponding to the target bed in that scanning round. For example, both the first and second scanning rounds include scanning the target bed, the first reference bed, the second reference bed, ..., the last reference bed in a head-to-toe direction. The processing device 120 can determine the continuous input function of the first scanning round based on the overlapping input function information obtained in the first scanning round, and the processing device 120 can determine the continuous input function of the second scanning round based on the overlapping input function information obtained in the second scanning round.

[0086] It should be noted that the above description of process 300 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to process 300 under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0087] In some embodiments of this specification, (1) multi-bed short-axis scanning is beneficial to achieve more comprehensive image imaging; (2) by using the information of the overlapping scanning area, continuous input functions on the time axis are obtained, realizing the acquisition of continuous input functions in short-axis PET; (3) by using the information of the overlapping scanning area, the difference in input function count rate between adjacent beds under different scanning conditions can be corrected.

[0088] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0089] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0090] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0091] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0092] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0093] For each patent, patent application, patent application publication, and other material, such as articles, books, specifications, publications, and documents, referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0094] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. An imaging method, characterized in that, The method includes: An input function is used to obtain multiple partitions of a target object located in multiple beds, wherein the multiple beds include target beds and reference beds, and the scanning areas of adjacent beds in the multiple beds have overlapping scanning areas; Obtain the overlapping input function information corresponding to the overlapping scan region; Based on the overlapping input function information, the reference partition input function corresponding to the reference bed is corrected to determine the continuous input function corresponding to the target bed, including: Determine the ratio of the partition input function of the adjacent beds corresponding to each of the overlapping scan regions; Based on the ratio and the partition input function corresponding to the reference region outside the overlapping scan region in the scan region corresponding to the last reference bed in the reference beds, at least a portion of the continuous input function is determined.

2. The method as described in claim 1, characterized in that, The function for obtaining multiple partitions of the target object located in multiple beds includes: For each of the plurality of beds Obtain scan data of the target object located at the bed position; Based on the scan data, determine the partition input function corresponding to the bed.

3. The method as described in claim 1, characterized in that, The reference bed includes a first reference bed, and the overlapping scan region includes a first overlapping scan region where the scan region corresponding to the target bed overlaps with the scan region corresponding to the first reference bed. The step of correcting the reference partition input function corresponding to the reference bed based on the overlapping input function information to determine the continuous input function corresponding to the target bed includes: Obtain the target function information of the target input function in the first time period; Obtain the first function information of the first reference input function in the first time period; Obtain the first ratio between the target function information and the first function information; Based on the first ratio, the second function information of the first reference input function in the second time period is corrected to obtain at least a portion of the continuous input function in the second time period.

4. The method as described in claim 3, characterized in that, The step of obtaining the first ratio between the target function information and the first function information includes: The average value of the ratio of the objective function information to the first function information at each time point within the first time period is obtained, and the average value is used as the first ratio.

5. The method as described in claim 3, characterized in that, The reference bed further includes a second reference bed, and the overlapping scan region further includes a second overlapping scan region of the scan region corresponding to the first reference bed and the scan region corresponding to the second reference bed. The step of correcting the reference partition input function corresponding to the reference bed based on the overlapping input function information to determine the continuous input function corresponding to the target bed further includes: Obtain the information of the second function of the first reference input function before correction in the second time period; Obtain the third function information of the second reference input function in the second time period; Obtain a second ratio between the second function information and the third function information; Based on the second ratio, the fourth function information of the second reference input function in the third time period is corrected to obtain at least a portion of the continuous input function in the third time period.

6. The method as described in claim 5, characterized in that, The step of correcting the fourth function information of the second reference input function in the third time period based on the second ratio to obtain at least a portion of the continuous input function in the third time period includes: The average value of the ratio of the second function information to the third function information at each time point within the second time period is obtained, and the average value is used as the second ratio. Based on the first ratio and the second ratio, the fourth function information of the second reference input function in the third time period is corrected to obtain at least a portion of the continuous input function in the third time period.

7. The method as described in claim 1, characterized in that, Also includes: Perform multiple rounds of scanning, each round of which includes scanning of multiple beds; The step of correcting the reference partition input function corresponding to the reference bed based on the overlapping input function information, and determining the continuous input function corresponding to the target bed, further includes: Based on the overlapping input function information within the same scanning cycle, the reference partition input function corresponding to the reference bed is corrected to determine the continuous input function of the target bed in the scanning cycle.

8. An imaging system, characterized in that, The system includes: The first acquisition module is used to acquire multiple partition input functions of the target object located in multiple beds, the multiple beds including target beds and reference beds, and the scanning areas of adjacent beds in the multiple beds have overlapping scanning areas; The second acquisition module is used to acquire the overlapping input function information corresponding to the overlapping scan region; The determining module is used to correct the reference partition input function corresponding to the reference bed based on the overlapping input function information, and to determine the continuous input function corresponding to the target bed, including: Determine the ratio of the partition input function of the adjacent beds corresponding to each of the overlapping scan regions; Based on the ratio and the partition input function corresponding to the reference region outside the overlapping scan region in the scan region corresponding to the last reference bed in the reference beds, at least a portion of the continuous input function is determined.

9. A computer-readable storage medium storing computer instructions that, when read by a computer, execute the method as described in any one of claims 1 to 7.

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