Image reconstruction processing method, system and medical imaging equipment

Abstract

An embodiment of the present specification provides an image reconstruction processing method, the method comprising: determining the position of a pixel to be reconstructed in the image to be reconstructed; determining a first angle data range corresponding to the pixel to be reconstructed based on the position and scanning parameters; obtaining a sufficiency limit threshold for the pixel to be reconstructed; determining target scanning data for reconstructing the pixel to be reconstructed based on the first angle data range, the sufficiency limit threshold and the original scanning data; reconstructing the pixel to be reconstructed based on the target scanning data, and determining a target reconstructed pixel corresponding to the pixel to be reconstructed; and determining a target reconstructed image based on the target reconstruction pixels corresponding to all pixels to be reconstructed in the image to be reconstructed.

Description

Technical Field

[0001] This specification relates to the field of medical imaging, and in particular to an image reconstruction processing method, system, and medical imaging equipment. Background Art

[0002] To reconstruct moving scanned objects (e.g., the human or animal heart or coronary arteries), limited-angle CT reconstruction algorithms are used to obtain high-temporal-resolution images. Existing CT reconstruction algorithms place very high demands on data integrity, making it difficult to reconstruct high-quality images at limited angles.

[0003] Therefore, it is necessary to provide an image reconstruction processing method, system and medical imaging equipment for reconstructing high-quality images at limited angles. Summary of the Invention

[0004] One of the embodiments of the present specification provides an image reconstruction processing method. The image reconstruction processing method includes: determining the position of a pixel to be reconstructed in an image to be reconstructed; determining a first angle data range corresponding to the pixel to be reconstructed based on the position and scanning parameters; obtaining a sufficiency limit threshold of the pixel to be reconstructed, the sufficiency limit threshold representing the minimum value of the angle data range corresponding to the scanning data required to reconstruct the pixel to be reconstructed at the position; determining target scanning data for reconstructing the pixel to be reconstructed based on the first angle data range, the sufficiency limit threshold, and the original scanning data; reconstructing the pixel to be reconstructed based on the target scanning data, and determining a target reconstructed pixel corresponding to the pixel to be reconstructed; and determining a target reconstructed image based on the target reconstructed pixels corresponding to all the pixels to be reconstructed in the image to be reconstructed.

[0005] In some embodiments, obtaining the position of the pixel to be reconstructed in the image to be reconstructed includes: determining the size of the display field of view of the image to be reconstructed and the number of pixels in the image to be reconstructed; and determining the position of the pixel to be reconstructed in the image to be reconstructed based on the size of the display field of view and the number of pixels.

[0006] In some embodiments, determining the first angle data range corresponding to the pixel to be reconstructed based on the position and scanning parameters includes: determining the initial scanning angle range of the pixel to be reconstructed; and determining the first angle data range based on the position, scanning parameters and the initial scanning angle range.

[0007] In some embodiments, determining the target scan data for reconstructing the pixel to be reconstructed based on the first angle data range, the sufficiency limit threshold and the original scan data includes: determining first sub-scan data based on the first angle data range and the original scan data; when the first angle data range is greater than or equal to the sufficiency limit threshold, determining the first sub-scan data as the target scan data.

[0008] In some embodiments, determining the target scan data for reconstructing the pixel to be reconstructed based on the first angle data range, the sufficiency limit threshold and the original scan data also includes: when the first angle data range is less than the sufficiency limit threshold, determining the second sub-scan data corresponding to the pixel to be reconstructed from the complete angle scan data; and determining the first sub-scan data and the second sub-scan data as the target scan data.

[0009] In some embodiments, determining the second sub-scanning data corresponding to the pixel to be reconstructed from the complete angle scanning data includes: determining the size of the second angle data range corresponding to the pixel to be reconstructed based on the difference between the first angle data range and the sufficiency limit threshold; determining the second angle data range of the pixel to be reconstructed and the second sub-scanning data corresponding to the second angle data range based on the complete angle scanning data, the first angle data range, the size of the second angle data range and the position of the pixel to be reconstructed.

[0010] In some embodiments, reconstructing the pixel to be reconstructed based on the target scan data and determining the target reconstructed pixel corresponding to the pixel to be reconstructed includes: reconstructing the pixel to be reconstructed through an iterative algorithm based on the first sub-scan data and the second sub-scan data to obtain the target reconstructed pixel, wherein the deviation term of the iterative algorithm is positively correlated with the first transformation term and the second transformation term.

[0011] In some embodiments, the deviation term is a weighted sum based on the first transformation term and the second transformation term, wherein the corresponding weights of the first transformation term and the second transformation term are related to the position of the pixel to be reconstructed in the image to be reconstructed.

[0012] One of the embodiments of the present specification provides an image reconstruction processing system, the system comprising: a first determination module for determining the position of a pixel to be reconstructed in the image to be reconstructed; a second determination module for determining a first angle data range corresponding to the pixel to be reconstructed based on the position and scanning parameters; an acquisition module for acquiring a sufficiency limit threshold for the pixel to be reconstructed; a third determination module for determining target scan data for reconstructing the pixel to be reconstructed based on the sufficiency limit threshold and original scan data; a first reconstruction module for reconstructing the pixel to be reconstructed based on the target scan data and determining a target reconstructed pixel corresponding to the pixel to be reconstructed; a second reconstruction module for determining a target reconstructed image based on the target reconstruction pixels corresponding to all pixels to be reconstructed in the image to be reconstructed; and a processor for executing to implement the image reconstruction processing method as described in any one of the above embodiments.

[0013] One of the embodiments of this specification provides a computer-readable storage medium, which stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes them to implement the image reconstruction processing method described in any of the above embodiments.

[0014] One embodiment of this specification provides a medical imaging device, which includes the image reconstruction processing system described in the above embodiment.

[0015] The embodiment of the present invention sets different sufficiency limit thresholds for pixels to be reconstructed at different positions, thereby screening out sufficient target scanning data with fewer artifacts to reconstruct the pixels to be reconstructed, thereby obtaining a more accurate target reconstructed image. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein:

[0017] Figure 1 is a schematic diagram of an application scenario of an image reconstruction processing system according to some embodiments of this specification;

[0018] Figure 2 is an exemplary block diagram of a processor according to some embodiments of this specification;

[0019] Figure 3 is an exemplary flow chart of an image reconstruction processing method according to some embodiments of this specification;

[0020] Figure 4 is an exemplary flow chart of determining a first angle data range according to some embodiments of this specification;

[0021] Figure 5 is an exemplary flowchart of determining a target reconstructed pixel according to some embodiments of this specification. DETAILED DESCRIPTION

[0022] To more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly describes the drawings required for describing the embodiments. Obviously, the drawings described below are merely examples or embodiments of this specification. Those skilled in the art can apply this specification to other similar scenarios based on these drawings without inventive effort. Unless otherwise apparent from the context or otherwise noted, the same reference numerals in the figures represent the same structure or operation.

[0023] It should be understood that the terms "system," "device," "unit," and / or "module" used herein are a method for distinguishing different components, elements, parts, portions, or assemblies at different levels. However, if other terms can achieve the same purpose, the terms may be replaced by other expressions.

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

[0025] Flowcharts are used throughout this specification to illustrate the operations performed by systems according to embodiments of this specification. It should be understood that preceding or following operations do not necessarily need to be performed in exact order. Instead, the steps may be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0026] Figure 1 It is a schematic diagram of an application scenario of an image reconstruction processing system 100 according to some embodiments of this specification.

[0027] In some embodiments, the image reconstruction processing system 100 can realize the reconstruction of CT images by implementing the methods and / or processes disclosed in this specification. Figure 1 As shown, the application scenario of the image reconstruction processing system 100 may include a processor 110 , a network 120 , a terminal 130 , a storage device 140 and a scanning device 150 .

[0028] The processor 110 can be used to process data and / or information from at least one component of the image reconstruction processing system 100 or an external data source (e.g., a cloud data center). For example, the processor 110 can process scan data from the scanning device 150. In some embodiments, the processor 110 can include a central processing unit (CPU), a digital signal processor (DSP), etc., and / or any combination thereof. In some embodiments, the processor 110 can be implemented locally, remotely, or on a cloud platform.

[0029] The network 120 may provide a channel for information exchange. In some embodiments, the processor 110, the terminal 130, the storage device 140, and the scanning device 150 may exchange information via the network 120. For example, the processor 110 may obtain scan data from the scanning device 150 via the network 120.

[0030] Terminal 130 refers to one or more terminal devices or software used by a user (such as a doctor or operator of processor 110). In some embodiments, terminal 130 can be one or any combination of a mobile device 131, a tablet computer 132, a laptop computer 133, or other devices with input and / or output functions. In some embodiments, terminal 130 can serve as a display terminal for the user, displaying reconstructed CT images. In some embodiments, the user can control other components of system 100 through terminal 130. For example, the user can control scanning device 150 to perform a scan through terminal 130. In some embodiments, terminal 130 can receive data and / or information from other components in system 100.

[0031] Storage device 140 may be used to store data and / or instructions. In some embodiments, storage device 140 may store data and / or instructions obtained from other components of system 100, such as processor 110, terminal 130, and scanning device 150. In some embodiments, storage device 140 may store data and / or instructions used by processor 110 to execute or use the exemplary methods described herein.

[0032] The scanning device 150 can be used to scan a scanned object and obtain scan data of the scanned object, where the scanned object may refer to the object to be scanned. In some embodiments, the scanning device may include a gantry 151, a detector 152, a radiation source 153, and a scanning bed 154. The gantry 151 can be used to support the detector 152, the radiation source 153, etc. The radiation source 153 can emit radiation toward the scanned object. The detector 152 can receive the radiation that passes through the scanned object. The scanning bed 154 can support the scanned object during scanning. During the scanning process, the radiation source 153 can emit radiation toward the scanned object located on the scanning bed 154. The radiation can pass through the scanned object and may be attenuated during the process. After passing through the scanned object, the attenuated radiation can be collected by the detector 152 to generate scan data.

[0033] It should be noted that the above description of the application scenario of the image reconstruction processing system 100 is only for convenience of description and does not limit this specification to the scope of the embodiments cited.

[0034] Figure 2 is an exemplary block diagram of the processor 110 according to some embodiments of the present specification.

[0035] In some embodiments, the processor 110 may include a first determination module 210 , a second determination module 220 , an acquisition module 230 , a third determination module 240 , a first reconstruction module 250 , and a second reconstruction module 260 .

[0036] The first determining module 210 can be used to determine the position of the pixel to be reconstructed in the image to be reconstructed. For more information about the image to be reconstructed, the pixel to be reconstructed and the position, please refer to Figure 3 The related descriptions are not repeated here. In some embodiments, the first determination module 210 can be further used to determine the size of the display field of view of the image to be reconstructed and the number of pixels in the image to be reconstructed; based on the size of the display field of view and the number of pixels, the position of the pixel to be reconstructed in the image to be reconstructed is determined. For more information about the size of the display field of view and the number of pixels of the image to be reconstructed, see Figure 3 The related descriptions will not be repeated here.

[0037] The second determination module 220 can be used to determine the first angle data range corresponding to the pixel to be reconstructed based on the position and scanning parameters. In some embodiments, the second determination module 220 can be further used to determine the initial scanning angle range of the pixel to be reconstructed; the first angle data range is determined based on the position, scanning parameters and the initial scanning angle range. For more information about scanning parameters, first angle data range, and initial scanning angle range, see Figure 3 The related descriptions will not be repeated here.

[0038] The acquisition module 230 can be used to obtain the sufficiency limit threshold of the pixel to be reconstructed. For more information about the sufficiency limit threshold, please refer to Figure 3 The related descriptions will not be repeated here.

[0039] The third determination module 240 can be used to determine the target scan data for reconstructing the pixel to be reconstructed based on the first angle data range, the sufficiency limit threshold and the original scan data. Figure 3 In some embodiments, the third determination module 240 can be further configured to determine first sub-scan data based on the first angle data range and the original scan data; when the first angle data range is greater than or equal to the sufficiency limit threshold, the first sub-scan data is determined as the target scan data. For more information about the first sub-scan data, see Figure 5 The description thereof will not be repeated here. In some embodiments, the third determination module 240 may also be used to determine the second sub-scan data corresponding to the pixel to be reconstructed from the complete angle scan data when the first angle data range is less than the sufficiency limit threshold; and determine the first sub-scan data and the second sub-scan data as the target scan data. For more information about the complete angle scan data and the second sub-scan data, please refer to Figure 5 The related description thereof will not be repeated here. In some embodiments, the third determination module 240 can be further used to determine the size of the second angular data range corresponding to the pixel to be reconstructed based on the difference between the first angular data range and the sufficiency limit threshold; based on the complete angular scan data, the first angular data range, the size of the second angular data range and the position of the pixel to be reconstructed, determine the second angular data range of the pixel to be reconstructed and the second sub-scan data corresponding to the second angular data range. For more information about the second angular data range, please refer to Figure 5 The related descriptions will not be repeated here.

[0040] The first reconstruction module 250 can be used to reconstruct the to-be-reconstructed pixel based on the target scan data and determine the target reconstructed pixel corresponding to the to-be-reconstructed pixel. For more information about the target reconstructed pixel, please refer to Figure 3 And the related descriptions are not repeated here. In some embodiments, the first reconstruction module 250 can be further used to reconstruct the pixel to be reconstructed based on the first sub-scan data, and determine the target reconstructed pixel corresponding to the pixel to be reconstructed. In some embodiments, the first reconstruction module 250 can be further used to reconstruct the pixel to be reconstructed based on the first sub-scan data and the second sub-scan data, and determine the target reconstructed pixel corresponding to the pixel to be reconstructed. In some embodiments, the first reconstruction module 250 can be further used to reconstruct the pixel to be reconstructed by an iterative algorithm based on the first sub-scan data and the second sub-scan data to obtain the target reconstructed pixel, wherein the deviation term of the iterative algorithm is positively correlated with the first transformation term and the second transformation term. For more information about reconstructing the pixel to be reconstructed in the image to be reconstructed by an iterative algorithm and obtaining the target reconstructed pixel, please refer to Figure 5 The related descriptions will not be repeated here.

[0041] The second reconstructed pixel 260 can be used to determine a target reconstructed image based on the target reconstructed pixels corresponding to all the pixels to be reconstructed in the image to be reconstructed. Figure 3 The related descriptions will not be repeated here.

[0042] It should be noted that the above description of each module is for convenience only and does not limit this specification to the scope of the embodiments. It is understandable that those skilled in the art, after understanding the principles of the system, may arbitrarily combine the modules or form a subsystem connected with other modules without deviating from the principles. In some embodiments, Figure 2 The first determination module 210, acquisition module 230, third determination module 240, first reconstruction module 250, and second reconstruction module 260 disclosed in the specification may be different modules within a system, or a single module may implement the functions of two or more of the aforementioned modules. For example, each module may share a storage module, or each module may have its own storage module. Such variations are within the scope of protection of this specification.

[0043] Figure 3 FIG3 is an exemplary flow chart of an image reconstruction processing method according to some embodiments of this specification. In some embodiments, process 300 may be executed by processor 110. Figure 3 As shown, process 300 includes the following steps:

[0044] Step 310 : For each pixel to be reconstructed in the image to be reconstructed, determine the position of the pixel to be reconstructed in the image to be reconstructed. In some embodiments, step 310 may be performed by the first determining module 210 .

[0045] The image to be reconstructed may refer to an image generated by direct projection based on the original scan data. During the scanning process, the scanned part of the scanned object may move (such as a beating heart), which may affect the scan data and cause artifacts in the image to be reconstructed. In some embodiments, the scanned object may be scanned within an initial scanning angle range based on a scanning device to obtain raw scan data, wherein the scanned object may be a biological object (e.g., a patient, an animal, etc.) or a non-biological object (e.g., a phantom, a water phantom, etc.). The scanning range of the raw scan data may be pre-set, for example, the scanning range of the raw scan data may be pre-set to [0°, 360°].

[0046] The image to be reconstructed may include but is not limited to a 2D image, a 3D image, etc. When the image to be reconstructed is a 2D image, the image to be reconstructed may be composed of pixels to be reconstructed. In some embodiments, the size of the display field of view of the image to be reconstructed and the number of pixels in the image to be reconstructed may be determined; based on the size of the display field of view and the number of pixels, the position of the pixel to be reconstructed in the image to be reconstructed may be determined. The size of the display field of view of the image to be reconstructed and the number of pixels may be determined by presetting. For example, the size of the display field of view of the image to be reconstructed may be pre-set to 150mm*150mm, and the number of pixels may be set to 420*420, thereby determining the pixel size of each pixel to be reconstructed and its corresponding position. The position of the pixel to be reconstructed may be determined as the center position of the pixel to be reconstructed. As in the above example, the lower left corner of the image to be reconstructed may be set as the coordinate origin, with the coordinate unit being mm. Correspondingly, the position of the pixel to be reconstructed located in the lower left corner is approximately (0.17, 0.17). Similarly, when the image to be reconstructed is a 3D image, the image to be reconstructed may be composed of voxels to be reconstructed. By determining the image size and the number of voxels in the image to be reconstructed, the position corresponding to each voxel in the image to be reconstructed can be determined. For ease of description only, this specification will be described based on pixels, but this specification is not intended to be limited to the scope of the embodiments described.

[0047] Step 320 : Determine a first angle data range corresponding to the pixel to be reconstructed based on the position and the scanning parameters. In some embodiments, step 320 may be performed by the second determination module 220 .

[0048] Scanning parameters may refer to parameters set by the scanning device. In some embodiments, scanning parameters may include, but are not limited to, the detector fan angle, the distance between the radiation source and the rotation center, and the like. Scanning parameters can be obtained by pre-setting the scanning device. For example, the pre-set distance between the radiation source and the rotation center in the scanning device is 1050 mm.

[0049] The first angle data range may refer to the angle data range corresponding to the original scan data corresponding to the pixel to be reconstructed, which has no artifacts or only a small amount of artifacts. The scan data corresponding to the first angle data may be used to reconstruct the pixel to be reconstructed. For more information about the first angle data range, see Figure 4 The related descriptions will not be repeated here.

[0050] In some embodiments, modeling or various data analysis algorithms, such as regression analysis and discriminant analysis, can be used to analyze and process the positions of pixels to be reconstructed and the scanning parameters of the scanning device to obtain the first angle data range.

[0051] In some embodiments, the initial scanning angle range of the pixel to be reconstructed can be determined; based on the position, scanning parameters and the initial scanning angle range, the first angle data range is determined. For more information about the above embodiments, see Figure 4 The related descriptions will not be repeated here.

[0052] Step 330 , obtaining a sufficiency limit threshold of the pixel to be reconstructed. In some embodiments, step 330 may be performed by the obtaining module 230 .

[0053] The sufficiency threshold may represent the minimum value of the range of angular data corresponding to the scan data required to reconstruct the pixel at that location. In some embodiments, the sufficiency threshold may vary depending on the location of the pixel to be reconstructed. For example, reconstructing a pixel at location A may require at least 180° of scan data, while reconstructing a pixel at location B may require at least 270° of scan data.

[0054] In some embodiments, based on the position of the pixel to be reconstructed, a sufficiency limit threshold corresponding to the position may be obtained according to a preset correspondence relationship, wherein the preset correspondence relationship may be set by the user based on experience.

[0055] When reconstructing pixels at different locations in an image to be reconstructed, each pixel requires different amounts of scan data. Pixels at some locations can achieve better reconstruction results using less scan data, while pixels at other locations require more scan data to reconstruct. Some embodiments of this specification set different sufficiency limit thresholds for pixels at different locations in an image to be reconstructed. This ensures the sufficiency of data used to reconstruct the pixels, while also maximizing the use of the first sub-scan data with fewer artifacts during reconstruction and avoiding the use of other unnecessary scan data with more artifacts, thereby obtaining a reconstructed image with fewer artifacts.

[0056] Step 340 : Determine target scan data for reconstructing the pixel to be reconstructed based on the first angle data range, the sufficiency limit threshold, and the original scan data. In some embodiments, step 340 may be performed by the third determination module 240 .

[0057] The target scan data may refer to scan data for reconstructing pixels to be reconstructed. In some embodiments, the target scan data may be determined based on a sufficiency limit threshold and the original scan data.

[0058] In some embodiments, it may be determined whether the first angle data range satisfies a sufficiency restriction threshold, and based on the determination result, scan data satisfying the sufficiency restriction threshold is selected from the original scan data and determined as the target scan data.

[0059] In some embodiments, the first sub-scan data can be determined based on the first angle data range and the original scan data; when the first angle data range is greater than or equal to the sufficiency limit threshold, the first sub-scan data is determined as the target scan data. In some embodiments, when the first angle data range is less than the sufficiency limit threshold, the second sub-scan data corresponding to the pixel to be reconstructed is determined from the complete angle scan data; the first sub-scan data and the second sub-scan data are determined as the target scan data. For more information about the above embodiments, see Figure 5 The related descriptions will not be repeated here.

[0060] Step 350 : Reconstruct the to-be-reconstructed pixel based on the target scan data and determine the target reconstructed pixel corresponding to the to-be-reconstructed pixel. In some embodiments, step 350 may be performed by the first reconstruction module 250 .

[0061] The target reconstructed pixel may refer to a pixel without artifacts or with fewer artifacts obtained after reconstructing the pixel to be reconstructed.

[0062] In some embodiments, the corresponding pixel to be reconstructed can be iteratively reconstructed based on the target scan data, thereby obtaining the target reconstructed pixel corresponding to the pixel to be reconstructed. In some embodiments, the first sub-scan data can be determined as the target scan data, and the corresponding pixel to be reconstructed can be iteratively reconstructed based on the first sub-scan data, thereby obtaining the target reconstructed pixel corresponding to the pixel to be reconstructed. For more information about the above embodiments, see Figure 5 In some embodiments, the first sub-scanning data and the second sub-scanning data can be determined as target scanning data, and the pixel to be reconstructed can be reconstructed based on the first sub-scanning data and the second sub-scanning data to determine the target reconstructed pixel corresponding to the pixel to be reconstructed. For more information about the above embodiments, see Figure 5 The related descriptions will not be repeated here.

[0063] Step 360 , based on the target reconstructed pixels corresponding to all the pixels to be reconstructed in the image to be reconstructed, determines the target reconstructed image. In some embodiments, step 360 may be performed by the second reconstruction module 260 .

[0064] A target reconstructed image may refer to an artifact-free or artifact-reduced image obtained by reconstructing an image to be reconstructed. After determining the target reconstructed pixels corresponding to all pixels to be reconstructed in the image to be reconstructed, the target reconstructed pixels corresponding to all pixels to be reconstructed may be arranged according to their positions in the image to form the target reconstructed image.

[0065] In some embodiments of the present specification, the sufficiency limit threshold corresponding to the pixel to be reconstructed is obtained by the position of the pixel to be reconstructed, and the target scanning data corresponding to the pixel to be reconstructed is further determined to reconstruct the pixel to be reconstructed. The target scanning data used for reconstruction is screened, so that motion artifacts and limited angle artifacts can be processed simultaneously, and a more accurate target reconstructed image can be obtained.

[0066] Figure 4 FIG4 is an exemplary flow chart of determining the first angle data range according to some embodiments of this specification. In some embodiments, process 400 may be executed by the second determination module 220. Figure 4 As shown, process 400 may include the following steps:

[0067] Step 410: Determine the initial scanning angle range of the pixels to be reconstructed.

[0068] The initial scanning angle range may refer to the angular range of each scanning angle when scanning a patient's scanning area. The initial scanning angle range may be a continuous interval. For example, the initial scanning angle range may be [0°, 60°]. The initial scanning angle range may also be composed of multiple continuous sub-intervals. For example, the initial scanning angle range may be {[0°, 60°], [90°, 160°]}.

[0069] In some embodiments, the initial scanning angle range can be determined by the user based on their own experience. For example, the user can determine the initial scanning angle range to be [30°, 270°] based on their own experience.

[0070] In some embodiments, the initial scanning angle range can also be determined by other means. For example, a limited reconstruction angle range can be pre-set, and the reconstruction start angle, reconstruction center angle, or reconstruction end angle corresponding to the initial scanning angle range can be determined based on the limited reconstruction angle range, thereby determining the corresponding initial scanning angle range. As shown in formula (1), the initial scanning angle range can be determined based on the reconstruction center angle:

[0071]

[0072] Among them, {θ LA} is the initial scanning angle range, θ c is the reconstruction center angle, and Δθ is the limited reconstruction angle range.

[0073] For example, a limited reconstruction angle range of 160° can be predetermined. When scanning based on this limited reconstruction angle range, 90 degrees can be selected as the center of the scanning range. Correspondingly, the reconstruction center angle can be determined to be 90°, thereby determining the initial scanning angle range to be [10°, 170°]. The reconstruction center angle can be determined in various ways. For example, when scanning the heart, an electrocardiogram can be acquired simultaneously. Based on the electrocardiogram, the moment when the heart motion amplitude is minimum can be determined, and the scanning angle corresponding to this moment can be determined as the reconstruction center angle.

[0074] Correspondingly, the corresponding initial scanning angle range can also be determined based on the reconstruction start angle or reconstruction end angle corresponding to the initial scanning angle range. As shown in formula (2), the initial scanning angle range can be determined based on the reconstruction start angle:

[0075] {θ LA}=[θ b ,θ b +Δθ] (2)

[0076] Among them, {θ LA} is the initial scanning angle range, θ bis the reconstruction starting angle, and Δθ is the limited reconstruction angle range.

[0077] As shown in formula (3), the initial scanning angle range can be determined based on the reconstruction end angle:

[0078] {θ LA}=[θ e -Δθ,θ e ] (3)

[0079] Among them, {θ LA} is the initial scanning angle range, θ e is the reconstruction end angle, and Δθ is the limited reconstruction angle range.

[0080] Step 420: Determine a first angle data range based on the position, the scanning parameters, and the initial scanning angle range.

[0081] Similar to the initial scanning angle range, the first angle data range may also be a continuous interval range or consist of multiple continuous sub-intervals.

[0082] In some embodiments, based on relevant settings in the scanning device, the initial scanning angle range, and the position of the pixel to be reconstructed in the image to be reconstructed, the first angle data range of the pixel to be reconstructed can be determined.

[0083] In some embodiments, the first angle data range of a pixel may be calculated based on formula (4):

[0084] {T}(x,y)=F({θ LA},Δγ,SID,P(x,y)) (4)

[0085] Wherein, {T}(x,y) is the first angle data range of the pixel to be reconstructed at position (x,y); {θ LA} is the initial scanning angle range; Δγ is the detector fan angle size; SID is the distance from the radiation source to the rotation center; P(x, y) is the position of the pixel to be reconstructed in the image to be reconstructed; F is the mapping of the radiation emitted by the radiation source to the angle corresponding to the pixel to be reconstructed, and its specific form can be determined by geometric calculation.

[0086] In the same initial scanning angle range, since the positions of the pixels to be reconstructed are different in the image to be reconstructed, the corresponding first angle data ranges may be different.

[0087] Some embodiments of the present specification may determine the first angle data range corresponding to the to-be-reconstructed pixel by calculation, thereby determining the sufficiency of the scan data of the to-be-reconstructed pixel at different positions.

[0088] Figure 5FIG5 is an exemplary flow chart of determining a target reconstructed pixel according to some embodiments of this specification. In some embodiments, process 500 may be executed by the third determination module 240. Figure 5 As shown, process 500 may include the following steps:

[0089] Step 510: Determine first sub-scan data based on the first angle data range and the original scan data.

[0090] The first sub-scan data may refer to the scan data corresponding to the first angle data range. The first sub-scan data may be filtered scan data without artifacts or with fewer artifacts. Therefore, the pixel to be reconstructed may be reconstructed based on the first sub-scan data, and the target reconstructed pixel may have no artifacts or fewer artifacts. In some embodiments, the first sub-scan data of the pixel to be reconstructed may be determined from the original scan data based on the first angle data range of the pixel to be reconstructed. For example, if the first angle data range is [10°, 170°], the scan data with a scan angle of [10°, 170°] in the original scan data is used as the first sub-scan data.

[0091] Step 520: When the first angle data range is greater than or equal to the sufficiency limit threshold, determine the first sub-scan data as the target scan data.

[0092] In some embodiments, when the first angle data range is greater than or equal to the sufficiency threshold, the first sub-scan data corresponding to the first angle data range can be directly determined as the target scan data. For example, if the first angle data range corresponding to a pixel to be reconstructed is [45°, 140°] and the sufficiency threshold corresponding to the position of the pixel to be reconstructed is 90°, the first angle data range is greater than the sufficiency threshold, and the first sub-scan data corresponding to the first angle data range can be directly determined as the target scan data.

[0093] Step 530 : Reconstruct the to-be-reconstructed pixel based on the first sub-scan data and determine the target reconstructed pixel corresponding to the to-be-reconstructed pixel. In some embodiments, step 450 may be performed by the first reconstruction module 250 .

[0094] In some embodiments, the pixel to be reconstructed can be reconstructed based on the first sub-scan data of the pixel in the image to be reconstructed by an iterative algorithm to determine the target reconstructed pixel corresponding to the pixel to be reconstructed. The objective function constructed by the iterative algorithm is as shown in formula (5):

[0095]

[0096] Where FP is the forward projection operator that converts the image domain to the projection domain, V is the target reconstructed pixel, FP(V) is the projection data of the target reconstructed pixel, Y is the original scan data, β is a parameter that controls the balance between data similarity and image smoothness, and R is the regularization penalty factor.

[0097] By optimizing and solving the above objective function through an optimization algorithm, an update function for iterative reconstruction can be obtained. The optimization algorithm includes, but is not limited to, gradient descent, Newton's method, and Lagrange multiplier method. For example, the Newton method can be used to optimize and solve formula (5) to obtain the update function (6) as follows:

[0098]

[0099] Among them, V n+1 is the target reconstructed pixel to be updated, V n is the target reconstructed pixel before updating, also known as the intermediate iterative reconstructed image; α is the correction term adjustment parameter, which can be calculated by solving the formula or empirically set based on clinical experiments; BP is the back-projection operator that converts the projection domain to the image domain; Y is the original scan data; and are the first-order derivative and second-order derivative of the regularization penalty factor R, also known as the regularization penalty factor; β is a parameter that controls the balance between data similarity and image smoothness. This parameter can be calculated by solving the formula or empirically set based on clinical experiments; I is the unit matrix of the same dimension as the target reconstructed pixel, and FP is the forward projection operator that converts the image domain to the projection domain.

[0100] The final target reconstructed pixel V can be solved using the update function (6).

[0101] In some embodiments, the regularization term βR(V) in formula (5) can be determined in a variety of ways, including but not limited to zero norm, one norm, two norm, trace norm, Frobenius norm, and nuclear norm. In some embodiments, the regularization term βR(V) can also be transformed into (1-δ)(V) based on the Prior Image Constrained Compressed Sensing (PICCS) algorithm. P -V) 2 +δR(V), where V P is the prior image of the full-angle reconstruction of the pixel to be reconstructed, and δ is an adjustment parameter that can be set based on experience.

[0102] In some embodiments, the regularization term in formula (5) can be directly removed, and the denoising process can be processed using a deep learning method. Specifically, the regularization term in formula (5) is removed, and an update is performed based on an iterative algorithm, and then denoising is performed based on the regularized network.

[0103] In some embodiments, when the first angle data range is less than the sufficiency limit threshold, process 500 may further include the following steps:

[0104] Step 540 : When the first angle data range is smaller than the sufficiency limit threshold, determine the second sub-scanning data corresponding to the pixel to be reconstructed from the complete angle scanning data.

[0105] The second sub-scanning data may be scanning data used to reconstruct the pixels to be reconstructed together with the first sub-scanning data.

[0106] In some embodiments, when the first angle data range is less than the sufficiency limit threshold, the second sub-scan data corresponding to the pixel to be reconstructed can be determined based on the sufficiency limit threshold, the first angle data range, the position of the pixel to be reconstructed, and the complete angle scan data. The complete angle scan data can refer to the scan data obtained when a complete 360° scan of the scanned portion is performed. In some embodiments, when a complete scan is performed at all angles, the complete angle data range corresponding to the pixel to be reconstructed can be determined based on formula (7):

[0107] {R}(x,y)=F({θ},Δγ,SID,P(x,y)) (7)

[0108] Where {R}(x,y) represents the angular data range corresponding to the pixel to be reconstructed at position (x,y) during a complete scan, {θ} represents the scanning range of the complete scan, i.e., [0°, 360°], Δγ is the detector fan angle, SID is the distance from the radiation source to the rotation center, P(x,y) is the position of the pixel to be reconstructed in the reconstructed image, and F is the mapping of the angle of the radiation emitted by the radiation source to the corresponding pixel to be reconstructed, which can be determined by geometric calculation.

[0109] For example, it can be determined according to formula (7) that when a full scan is performed, the complete angle data range corresponding to the pixel to be reconstructed at position A is [0°, 160°].

[0110] In some embodiments, the size of the second angular data range corresponding to the pixel to be reconstructed can be determined based on the difference between the first angular data range and the sufficiency limit threshold. The second angular data range can refer to the angular range corresponding to the second sub-scanning data.

[0111] In some embodiments, the second angular data range of the pixel to be reconstructed and the second sub-scan data corresponding to the second angular data range can be determined based on the full angular scan data, the first angular data range, the size of the second angular data range, and the position of the pixel to be reconstructed. In some embodiments, the second angular data range corresponding to the pixel to be reconstructed can be determined according to a preset condition based on the full angular data range, the first angular data range, and the size of the second angular data range. In some embodiments, the preset condition can be that the selected second angular data range should be as close as possible to the first angular data range. For example, if the first angular data range of a pixel to be reconstructed is [0°, 60°], the full angular range is {[0°, 60°], [90°, 160°]}, and the size of the second angular data range is 40°, the second angular data range of the pixel to be reconstructed can be determined to be [90°, 130°] according to the preset condition. In some embodiments, the preset condition can also be other conditions, for example, the preset condition can also be selecting scan data with fewer artifacts. The size of the artifact in the scan data can be determined in a variety of ways. For example, when scanning the heart, the size of the artifact corresponding to the scan data can be determined based on the electrocardiogram collected synchronously. When the amplitude of the heart movement is large, the artifact corresponding to the scan data at that moment is large. When the amplitude of the heart movement is small, the artifact corresponding to the scan data at that moment is small.

[0112] In some embodiments, based on the second angle data range, second sub-scanning data corresponding to the pixel to be reconstructed is determined from the complete angle scanning data.

[0113] It should be understood that since the second sub-scan data is intended to supplement the first sub-scan data so that the angle data range corresponding to its data can meet the sufficiency limit threshold, the first angle data range and the scanning angle range corresponding to the second sub-scan data should not overlap with each other, and there should be no repeated scanning data in the first target data and the second target data.

[0114] In some embodiments, the second sub-scan data corresponding to the pixel to be reconstructed in the image to be reconstructed may be determined from the complete angular scan data in other ways. For example, a portion of the scan data may be randomly selected from the complete angular scan data excluding the first sub-scan data as the second sub-scan data.

[0115] Step 550: Determine the first sub-scanning data and the second sub-scanning data as target scanning data.

[0116] For example, when the first angle data range corresponding to the first sub-scan data is [45°, 115°] and the second angle data range corresponding to the second sub-scan data is (115°, 135°], it can be determined that the target scan data is the scan data corresponding to the angle range [45°, 135°].

[0117] Step 560 : reconstruct the pixel to be reconstructed based on the first sub-scanning data and the second sub-scanning data, and determine a target reconstructed pixel corresponding to the pixel to be reconstructed.

[0118] In some embodiments, based on the first sub-scan data and the second sub-scan data, an iterative algorithm can be used to reconstruct the target reconstructed pixel, wherein the deviation term of the iterative algorithm is positively correlated with the first transformation term and the second transformation term. In some embodiments, the first transformation term can be a first error between a first iterative image iteratively generated based on the first sub-scan data and the first sub-scan data after forward projection. In some embodiments, the second transformation term can be a second error between a second iterative image iteratively generated based on the second sub-scan data and the second sub-scan data after forward projection. In some embodiments, the optimized Newton method can be used to optimize and solve formula (5), and the update function (8) is obtained as follows:

[0119]

[0120] Among them, V n+1 is the target reconstructed pixel to be updated, V n is the target reconstructed pixel before updating, also known as the intermediate iterative reconstructed image; α is the correction term adjustment parameter, which can be calculated by solving the formula or empirically set based on clinical experiments; and are the first-order derivative and second-order derivative of the regularization penalty factor R, also known as the regularization penalty factor; β is a parameter that controls the balance between data similarity and image smoothness. This parameter can be calculated by solving the formula or empirically set based on clinical experiments; k is the weight of the image update corresponding to the second sub-scan data. For more information about k, please refer to the following text of this manual and will not be repeated here; FP is a forward projection operator that converts the image domain to the projection domain; BP is a back projection operator that converts the projection domain to the image domain; I is a unit matrix of the same dimension as the reconstructed image; {x, y} represents the position of the pixel to be reconstructed in the image to be reconstructed; {θ m} represents the scanning angle range corresponding to the second angle data range; {θ LA} is the initial scanning angle range; is projection data of a unit matrix having the same dimension as the reconstructed image based on the first sub-scan data; is projection data of a unit matrix having the same dimension as the reconstructed image based on the second sub-scan data; is the first transformation term; is projection data of an image reconstructed based on the first sub-scan data; is the first sub-scan data; is the second transformation term; is projection data of an image reconstructed based on the second sub-scan data; It is the second sub-scan data.

[0121] The final target reconstructed pixel V can be solved using the update function (8).

[0122] As shown in the update function (8), the deviation term of the above iterative algorithm can be a weighted sum based on the first transformation term and the second transformation term. In some embodiments, the corresponding weights of the first transformation term and the second transformation term are related to the position of the pixel to be reconstructed in the image to be reconstructed. The corresponding weights of the first transformation term and the second transformation term can be determined according to the pre-set correspondence between the position and the weight. The closer the position of the pixel to be reconstructed is to the center of the image to be reconstructed, the more sufficient the corresponding first sub-scan data is. The influence of the second sub-scan data on the reconstruction of the pixel to be reconstructed can be reduced by reducing the k value; the farther the position of the pixel to be reconstructed is from the center of the image to be reconstructed, the more missing data there is in the first sub-scan data. The k value can be increased to increase the supplement of the second sub-scan data to the data reconstructed by the pixel to be reconstructed, thereby ensuring the quality of the target reconstructed pixel. For example, when the position of the pixel to be reconstructed is at the edge of the image to be reconstructed, k can be 1, and when the position of the pixel to be reconstructed is at the center of the image to be reconstructed, k can be 0.5.

[0123] Some embodiments of this specification can ensure sufficient scan data for image reconstruction by determining artifact-free or artifact-reduced first sub-scan data for image reconstruction and selecting second sub-scan data based on the first sub-scan data to supplement the first sub-scan data. Image reconstruction is then performed based on the first and second sub-scan data, effectively reducing artifacts in the iteratively reconstructed image and ensuring the quality of the reconstructed image.

[0124] At the same time, the amount of first sub-scan data corresponding to pixels to be reconstructed at different locations in the image to be reconstructed varies. Pixels to be reconstructed near the center of the image to be reconstructed correspond to a larger amount of first sub-scan data, while pixels to be reconstructed near the edge of the image to be reconstructed correspond to a smaller amount of first sub-scan data. Some embodiments of this specification optimize the iterative algorithm by assigning different weights to the first and second transformation terms in the deviation term, and by assigning weights that are related to the location of the pixel to be reconstructed. This allows for differentiating the importance of different types of scan data during reconstruction, thereby achieving both a higher-quality reconstructed image and ensuring the integrity of the reconstructed image.

[0125] This specification also provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes them to implement the image reconstruction processing method described in any one of the above embodiments.

[0126] This specification also provides a medical imaging device, which includes the image reconstruction processing system described in this specification.

[0127] It should be noted that the above descriptions of the various processes are for illustration and purpose only and do not limit the scope of application of this specification. Those skilled in the art may make various modifications and alterations to the above processes under the guidance of this specification. However, such modifications and alterations are still within the scope of this specification.

[0128] While the basic concepts have been described above, it will be apparent to those skilled in the art that the detailed disclosure is merely illustrative and does not limit this specification. Although not explicitly stated herein, various modifications, improvements, and revisions to this specification may be made by those skilled in the art. Such modifications, improvements, and revisions are suggested in this specification and remain within the spirit and scope of the exemplary embodiments of this specification.

[0129] This specification also uses specific terms to describe the embodiments of this specification. For example, "one embodiment," "an embodiment," and / or "some embodiments" refer to a feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "one embodiment," "an embodiment," or "an alternative embodiment" two or more times in different locations in this specification do not necessarily refer to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of this specification may be appropriately combined.

[0130] In addition, unless expressly stated in the claims, the order of the processing elements and sequences, the use of alphanumeric characters, or the use of other names described in this specification are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some of the invention embodiments currently considered useful through various examples, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the spirit and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0131] Similarly, it should be noted that, in order to simplify the presentation of this specification and thus facilitate understanding of one or more embodiments of the invention, the foregoing descriptions of the embodiments of this specification sometimes combine multiple features into a single embodiment, figure, or description thereof. However, this disclosure method does not imply that the subject matter of this specification requires more features than those recited in the claims. In fact, an embodiment may have fewer features than all of the features of a single disclosed embodiment.

[0132] In some embodiments, numbers are used to describe the quantity of components and attributes. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise stated, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the description and claims are approximate values, which may change according to the required characteristics of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the settings of such numerical values are as accurate as possible within the feasible range.

[0133] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, and documents, cited in this specification is hereby incorporated by reference in its entirety. This includes application history documents that are inconsistent with or conflict with the content of this specification, as well as documents (currently or subsequently attached to this specification) that limit the broadest scope of the claims of this specification. It should be noted that if the descriptions, definitions, and / or terminology used in the accompanying materials are inconsistent or conflicting with the content of this specification, the descriptions, definitions, and / or terminology used in this specification will control.

[0134] Finally, it should be understood that the embodiments described in this specification are intended only to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly described and illustrated in this specification.

Claims

1. An image reconstruction processing method, characterized in that: include: For a pixel to be reconstructed in an image to be reconstructed, determining a position of the pixel to be reconstructed in the image to be reconstructed; Determining a first angle data range corresponding to the pixel to be reconstructed based on the position and scanning parameters; Obtaining a sufficiency limit threshold of the pixel to be reconstructed; Determining target scan data for reconstructing the pixel to be reconstructed based on the first angle data range, the sufficiency limit threshold, and the original scan data; Reconstructing the to-be-reconstructed pixel based on the target scan data, and determining a target reconstructed pixel corresponding to the to-be-reconstructed pixel; A target reconstructed image is determined based on target reconstructed pixels corresponding to all the pixels to be reconstructed in the image to be reconstructed.

2. The method according to claim 1, wherein The obtaining of the position of the to-be-reconstructed pixel in the to-be-reconstructed image comprises: Determining the size of the display field of the image to be reconstructed and the number of pixels in the image to be reconstructed; The position of the to-be-reconstructed pixel in the to-be-reconstructed image is determined based on the size of the display field of view and the number of pixels.

3. The method according to claim 1, wherein The determining, based on the position and the scanning parameters, a first angle data range corresponding to the pixel to be reconstructed includes: Determining an initial scanning angle range of the pixel to be reconstructed; The first angle data range is determined based on the position, scanning parameters, and the initial scanning angle range.

4. The method according to claim 1, wherein Determining target scan data for reconstructing the pixel to be reconstructed based on the first angle data range, the sufficiency limit threshold, and the original scan data includes: Determining first sub-scanning data based on the first angle data range and the original scanning data; When the first angle data range is greater than or equal to the sufficiency limit threshold, the first sub-scan data is determined as the target scan data.

5. The method according to claim 4, wherein Also includes: When the first angle data range is smaller than the sufficiency limit threshold, determining second sub-scanning data corresponding to the to-be-reconstructed pixel from the complete angle scanning data; The first sub-scanning data and the second sub-scanning data are determined as the target scanning data.

6. The method according to claim 5, wherein The determining the second sub-scanning data corresponding to the pixel to be reconstructed from the full angle scanning data includes: determining a size of a second angular data range corresponding to the to-be-reconstructed pixel according to a difference between the first angular data range and the sufficiency limit threshold; Based on the complete angular scan data, the first angular data range, the size of the second angular data range and the position of the pixel to be reconstructed, the second angular data range of the pixel to be reconstructed and the second sub-scan data corresponding to the second angular data range are determined.

7. The method according to claim 5, wherein The reconstructing the to-be-reconstructed pixel based on the target scan data and determining the target reconstructed pixel corresponding to the to-be-reconstructed pixel includes: Based on the first sub-scan data and the second sub-scan data, the pixel to be reconstructed is reconstructed by an iterative algorithm to obtain the target reconstructed pixel, wherein the deviation term of the iterative algorithm is positively correlated with the first transformation term and the second transformation term.

8. The method according to claim 7, wherein The deviation term is based on a weighted sum of the first transformation term and the second transformation term, wherein the corresponding weights of the first transformation term and the second transformation term are related to the position of the to-be-reconstructed pixel in the to-be-reconstructed image.

9. An image reconstruction processing system, characterized in that: include: A first determining module is configured to determine, for a pixel to be reconstructed in the image to be reconstructed, a position of the pixel to be reconstructed in the image to be reconstructed; A second determining module is configured to determine a first angle data range corresponding to the pixel to be reconstructed based on the position and scanning parameters; A threshold acquisition module, configured to acquire a sufficiency limit threshold of the pixel to be reconstructed; a third determining module, configured to determine target scan data for reconstructing the pixel to be reconstructed based on the sufficiency limit threshold and the original scan data; A first reconstruction module is configured to reconstruct the to-be-reconstructed pixel based on the target scan data, and determine a target reconstructed pixel corresponding to the to-be-reconstructed pixel; A second reconstruction module is configured to determine a target reconstructed image based on target reconstructed pixels corresponding to all pixels to be reconstructed in the image to be reconstructed; A processor for executing the image reconstruction processing method as described in any one of claims 1 to 8.

10. A medical imaging device, characterized in that: The method comprises the image reconstruction processing system according to claim 9.

Images