System and method for image reconstruction

Abstract

The invention relates to a system and method for image reconstruction. The method may include obtaining original raw data collected by a medical device, obtaining an initial image, and generating a target image based on the original raw data and the initial image according to an image reconstruction algorithm.

Description

Technical Field

[0001] This application relates generally to systems and methods for medical imaging, and more specifically to systems and methods for image reconstruction. Background Technology

[0002] Medical imaging, such as computed tomography (CT), is widely used for the diagnosis and / or treatment of various diseases (e.g., cancer, coronary artery disease, brain diseases). Image reconstruction is a key technology in the field of medical imaging. Raw data collected by medical devices (e.g., CT scanners) can be processed using image reconstruction algorithms to generate reconstructed images. However, image reconstruction processes (e.g., iterative reconstruction processes) are typically computationally intensive and time-consuming. Therefore, there is a need to provide image reconstruction systems and methods with improved reconstruction speed, thereby enhancing the efficiency of medical analysis and / or diagnosis. Summary of the Invention

[0003] According to one aspect of this application, a method for image reconstruction is provided, implemented on a computing device including at least one processor and at least one storage device. The method may include acquiring raw data collected by a medical device, acquiring an initial image, and generating a target image based on the raw data and the initial image according to an image reconstruction algorithm. Generating the target image based on the raw data and the initial image according to the image reconstruction algorithm may include determining a processed initial image by transforming the initial image from an initial coordinate system to a target coordinate system, and generating the target image based on a second difference image. Multiple element values ​​in the processed initial image may be represented by multiple grids in the target coordinate system, which is determined based on the structure of the detector of the medical device.

[0004] In some embodiments, generating a target image based on a processed initial image may include determining a first difference image based on the processed initial image, determining a second difference image by transforming the first difference image from a target coordinate system to an initial coordinate system, and generating the target image based on the second difference image. Multiple element values ​​in the second difference image may be represented by multiple grids in the initial coordinate system.

[0005] In some embodiments, determining a first difference image based on a processed initial image may include determining first projection data by performing a forward projection operation on the processed initial image, determining second projection data based on the first projection data and the original raw data, and determining the first difference image by performing a backward projection operation on the second projection information.

[0006] In some embodiments, the raw data may correspond to multiple initial projection angles. Determining the processed initial image by transforming the initial image from an initial coordinate system to a target coordinate system may include determining a second processed initial image by transforming the initial image from the initial coordinate system to a reference coordinate system, and determining the second processed initial image by transforming the initial image from the initial coordinate system to the reference coordinate system. The reference coordinate system may correspond to a reference projection angle.

[0007] In some embodiments, determining a second difference image by transforming a first difference image from a target coordinate system to an initial coordinate system may include determining a third difference image by transforming the first difference image from a target coordinate system to a reference coordinate system, and determining a second difference image by transforming the third difference image from a reference coordinate system to an initial coordinate system.

[0008] In some embodiments, the origin of the reference coordinate system may be located at the rotation center of the medical device's frame, and the first axis direction of the reference coordinate system may be the same as the first axis direction of the target coordinate system.

[0009] In some embodiments, the target coordinate system may include at least a polar coordinate system.

[0010] In some embodiments, the detector of the medical device may include a plurality of detector units, comprising at least one row of detector units arranged along a first direction and at least one column of detector units arranged along a second direction. The origin of the target coordinate system may be located at the focal point of the X-ray tube of the medical device. The first axis of the target coordinate system may extend along a line connecting the origin and one of the detector units of the plurality of detector units. The second axis of the target coordinate system may be the angular direction between the line connecting the origin and one of the detector units of the at least one row of detector units and the first axis. The third axis of the target coordinate system may be the angular direction between the line connecting one of the detector units of the plurality of detector units and the origin and the plane formed by the first axis and the second axis.

[0011] In some embodiments, the size of each grid in a plurality of grids in the target coordinate system is related to the size of each detector element in a plurality of detector elements.

[0012] In some embodiments, the width of each of the plurality of grids along the second axis of the target coordinate system is related to the width of the corresponding detector element along the first direction. The height of each of the plurality of grids along the third axis of the target coordinate system is related to the height of the corresponding detector element along the second direction.

[0013] In some embodiments, the length of each of the plurality of grids along the first axis of the target coordinate system is approximately the same as the width of each of the plurality of grids along the second axis of the target coordinate system.

[0014] In some embodiments, the farther the mesh is from the origin of the target coordinate system along the first axis, the smaller the angle between the two sides of the mesh along the second axis, or the smaller the angle between the two sides of the mesh along the third axis.

[0015] In some embodiments, the width of the detector unit along the first direction is an integer multiple of the width of the corresponding grid along the second axis of the target coordinate system, or the height of the detector unit along the second direction is an integer multiple of the height of the corresponding grid along the third axis of the target coordinate system.

[0016] In some embodiments, the projected edges of the multiple grids on the detector plane coincide with or are parallel to the edge of the detector.

[0017] In some embodiments, determining the second-processed initial image by transforming the initial image from an initial coordinate system to a reference coordinate system may include performing interpolation operations on multiple element values ​​of multiple elements at multiple grids in the initial coordinate system to obtain multiple element values ​​of multiple elements at multiple grids in the reference coordinate system, and determining the second-processed initial image based on the multiple element values ​​of multiple elements at multiple grids in the reference coordinate system.

[0018] In some embodiments, determining the processed initial image by transforming the second processed initial image from the reference coordinate system to the target coordinate system may include obtaining multiple element values ​​of multiple elements at multiple non-integer grids in the reference coordinate system by performing interpolation operations on multiple element values ​​of multiple elements at multiple integer grids in the reference coordinate system. The multiple non-integer grids in the reference coordinate system correspond to multiple integer grids in the target coordinate system. Determining the processed initial image by transforming the second processed initial image from the reference coordinate system to the target coordinate system may also include obtaining multiple element values ​​of multiple elements at multiple integer grids in the target coordinate system based on the multiple element values ​​of multiple elements at multiple non-integer grids in the reference coordinate system, and determining the processed initial image based on the multiple element values ​​of multiple elements at multiple integer grids in the target coordinate system.

[0019] In some embodiments, for each of a plurality of integer grids in a reference coordinate system, determining a third difference image by transforming the first difference image from the target coordinate system to the reference coordinate system may include determining a plurality of corresponding non-integer grids in the reference coordinate system. The plurality of corresponding non-integer grids in the reference coordinate system correspond to a plurality of integer grids in the target coordinate system. Determining the third difference image by transforming the first difference image from the target coordinate system to the reference coordinate system may further include determining a plurality of element values ​​for a plurality of corresponding non-integer grids in the reference coordinate system based on a plurality of element values ​​for a plurality of elements at the plurality of integer grids in the target coordinate system, and determining the element values ​​of the integer grids in the reference coordinate system by performing interpolation operations on the plurality of element values ​​for a plurality of elements at the plurality of corresponding non-integer grids in the reference coordinate system. Determining the third difference image by transforming the first difference image from the target coordinate system to the reference coordinate system may further include determining the third difference image based on a plurality of element values ​​for a plurality of elements at the plurality of integer grids in the reference coordinate system.

[0020] In some embodiments, determining the second difference image by transforming the third difference image from the reference coordinate system to the initial coordinate system may include performing an interpolation operation on multiple element values ​​of multiple elements at multiple grids in the reference coordinate system to obtain multiple element values ​​of multiple elements at multiple grids in the initial coordinate system, and determining the second difference image based on the multiple element values ​​of multiple elements at multiple grids in the initial coordinate system.

[0021] In some embodiments, the image reconstruction algorithm may include an iterative reconstruction algorithm.

[0022] According to another aspect of this application, a system for image reconstruction is provided. The system may include at least one storage device and at least one processor, the storage device including a set of instructions, the processor being configured to communicate with the at least one storage device. When the instruction set is executed, the at least one processor may be configured to instruct the system to perform operations including acquiring raw data collected by a medical device, acquiring an initial image, and generating a target image based on the raw data and the initial image according to an image reconstruction algorithm. Generating the target image based on the raw data and the initial image according to the image reconstruction algorithm may include determining a processed initial image by transforming the initial image from an initial coordinate system to a target coordinate system, and generating the target image based on a second difference image. Multiple element values ​​in the processed initial image are represented by multiple grids in the target coordinate system, the target coordinate system being determined based on the structure of the detector of the medical device.

[0023] According to another aspect of this application, a non-transitory computer-readable medium is provided that includes a set of instructions for generating 3D images. When executed by at least one processor, this set of instructions can instruct at least one processor to implement a method that may include acquiring raw data collected by a medical device, acquiring an initial image, and generating a target image based on the raw data and the initial image according to an image reconstruction algorithm. Generating the target image based on the raw data and the initial image according to the image reconstruction algorithm may include determining a processed initial image by transforming the initial image from an initial coordinate system to a target coordinate system, and generating the target image based on a second difference image. Multiple element values ​​in the processed initial image may be represented by multiple grids in the target coordinate system, which is determined based on the structure of the detector of the medical device.

[0024] Additional features will be set forth in part in the description which follows, and will become apparent in part to those skilled in the art upon examination of the following and the accompanying drawings, or may be learned by production or operation of the examples. The features of this application may be realized and obtained by practice or by using various aspects of the methods, tools, and combinations presented in the detailed examples discussed below. Attached Figure Description

[0025] This application is further described through exemplary embodiments. These exemplary embodiments are described in detail with reference to the accompanying drawings. These drawings are not to scale. These embodiments are not limiting exemplary embodiments; in the various drawings, structures with the same reference numerals are represented as similar structures in the various views, and wherein: Figure 1 These are schematic diagrams of exemplary medical systems according to some embodiments of this application; Figure 2 These are schematic diagrams of exemplary hardware and / or software components of an exemplary computing device on which the processing device shown in some embodiments of this application may be implemented; Figure 3 These are schematic diagrams of exemplary hardware and / or software components of an exemplary mobile device according to some embodiments of this application; Figure 4 These are schematic diagrams of exemplary processing devices according to some embodiments of this application; Figure 5 This is a flowchart illustrating an exemplary process for generating a target image according to some embodiments of this application; Figure 6 This is a flowchart illustrating an exemplary process for generating a target image according to some embodiments of this application; Figure 7This is a flowchart illustrating an exemplary process for determining a processed initial image based on one or more historical record patterns, according to some embodiments of this application; Figure 8 This is a flowchart illustrating an exemplary process for determining a second differential image based on one or more historical record patterns, according to some embodiments of this application; Figure 9 This is a schematic diagram of an exemplary polar coordinate system according to some embodiments of this application; Figure 10 This is a schematic diagram of an exemplary mesh in a polar coordinate system according to some embodiments of this application; Figure 11 These are schematic diagrams of exemplary reference Cartesian coordinate systems and exemplary polar coordinate systems according to some embodiments of this application; and Figure 12 This is a schematic diagram of an exemplary reference Cartesian coordinate system and an exemplary initial Cartesian coordinate system according to some embodiments of this application. Detailed Implementation

[0026] In the following detailed description, numerous specific details are set forth by way of example in order to provide a thorough understanding of the relevant disclosure. However, those skilled in the art will understand that this application can be practiced without these details. In other instances, well-known methods, processes, systems, components, and / or circuits have been described at a relatively high level without detailed description in order to avoid unnecessarily obscuring aspects of this application. Various modifications to the disclosed embodiments will be apparent to those skilled in the art, and the general principles defined herein can be applied to other embodiments and applications without departing from the spirit and scope of this application. Therefore, this application is not limited to the embodiments shown but is given the widest scope consistent with the claims.

[0027] The terminology used herein is for describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” used herein may also include the plural forms. As used herein, the terms “and / or” and “at least one” include any and all combinations of one or more of the associated listed items. It is further understood that when the terms “comprising,” “including,” and / or “encompassing” are used in this specification, and when the terms “comprises,” “contains,” and / or “covers” are used, they specify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. Furthermore, the term “exemplary” is intended to refer to an example or illustration.

[0028] It should be understood that the terms “system,” “engine,” “unit,” “module,” and / or “block” used herein are a method of distinguishing different components, elements, parts, sections, or assemblies at different levels in ascending order. However, if these terms serve the same purpose, they may be replaced by another expression.

[0029] Generally, the terms "module," "unit," or "block" as used herein refer to a collection of logic or software instructions contained in hardware or firmware. Modules, units, or blocks described herein may be implemented in software and / or hardware and may be stored in any type of non-transitory computer-readable medium or other storage device. In some embodiments, software modules / units / blocks may be compiled and linked into an executable program. It should be understood that software modules may be invoked from other modules / units / blocks, may invoke themselves, and / or may be invoked in response to detected events or interrupts. Software modules / units / blocks configured for execution on a computing device may be provided on computer-readable media, such as optical discs, digital video discs, flash drives, disks, or any other tangible media, or may be provided as digital downloads (and may be initially stored in a compressed or installable format, requiring installation, decompression, or decryption before execution). Such software code may be stored, in part or in whole, on a storage device executing the computing device for execution by the computing device. Software instructions may be embedded in firmware, for example, EPROM. It should be further understood that hardware modules / units / blocks can be contained within connected logical components, such as gates and flip-flops, and / or can be contained within programmable units, such as programmable gate arrays or processors. The module / unit / block or computing device functionality described herein can be implemented as a software module / unit or block, but can also be represented in hardware or firmware. Generally, the module / unit / block described herein refers to a logical module / unit and block that can be combined with other modules / units or blocks or divided into submodules / subunits / subblocks, regardless of their physical organization or storage method. This description may apply to a system, an engine, or a part thereof.

[0030] It should be understood that although the terms "first," "second," and "third," etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, without departing from the scope of exemplary embodiments of this application, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.

[0031] Various terms are used to describe spatial and functional relationships between elements, including “connection,” “attachment,” and “mounting.” Unless explicitly described as “direct,” when describing a relationship between first and second elements in this application, the relationship includes a direct relationship where no other intervening element exists between the first and second elements, and an indirect relationship where one or more intermediate elements (spatially or functionally) exist between the first and second elements. In contrast, when an element is referred to as “directly connected,” attached, or positioned to another element, no intermediate element exists. Other terms used to describe relationships between elements should be interpreted in a similar manner (e.g., “between” vs. “directly between,” “adjacent” vs. “directly adjacent,” etc.).

[0032] These and other features, characteristics, as well as the methods of operation and functions of the related structural elements, the combination of components, and the economics of manufacture of this application, will become more apparent upon consideration of the following description and the accompanying drawings, which are an integral part of this application. It should be clearly stated that these drawings are for illustrative and descriptive purposes only and are not intended to limit the scope of the invention. Obviously, these drawings are not drawn to scale.

[0033] The term "image" in this application is used collectively to refer to image data (e.g., scanned data, projected data) and / or images of various forms, including two-dimensional (2D) images, three-dimensional (3D) images, four-dimensional (4D) images, etc. The term "anatomical structure" in this application can refer to a gas (e.g., air), a liquid (e.g., water), a solid (e.g., stone), a cell, tissue, an organ of an object, or any combination thereof, that can be shown in an image and actually exists or is attached to the body of the object. The terms "region," "location," and "area" in this application can refer to the location of an anatomical structure shown in an image, or the actual location of an anatomical structure existing within or attached to the body of the object, because an image can indicate the actual location of an anatomical structure existing within or attached to the body of the object. For the sake of brevity, the term "image of an object" may be simply referred to as the object.

[0034] One aspect of this application relates to systems and methods for image reconstruction. According to some embodiments of this application, a processing device can acquire raw raw data collected by a medical device. The processing device can acquire an initial image. The processing device can generate a target image based on the raw raw data and the initial image according to an image reconstruction algorithm. For example, the processing device can determine a processed initial image by transforming the initial image from an initial Cartesian coordinate system to a polar coordinate system. In the polar coordinate system, multiple element values ​​in the processed initial image can be represented by multiple integer grids. The processing device can determine first projection data by performing a forward projection operation on the processed initial image. The processing device can determine second projection data based on the first projection data and the raw raw data. The processing device can determine a first difference image by performing a back projection operation on the second projection data. The processing device can determine a second difference image by transforming the first difference image from a polar coordinate system to an initial Cartesian coordinate system. In the initial Cartesian coordinate system, multiple element values ​​in the second difference image can be represented by multiple integer grids. The processing device can generate a target image based on the second difference image.

[0035] In some embodiments, a polar coordinate system can be established based on the structure of the detector in the medical device. For example, the polar coordinate system may include multiple grids. The size of each grid may be related to the size of each of the multiple detector elements in the medical device's detector. Therefore, by transforming an image (e.g., an initial image) from an initial Cartesian coordinate system to a polar coordinate system, multiple elements of the transformed image (e.g., a processed initial image) can be discretized according to the structure of the medical device's detector. The projected edges of the multiple elements of the transformed image on the detector plane may coincide with or be parallel to the edges of the detector. When performing a forward projection operation on the transformed image (e.g., the processed initial image), a summation operation can be performed on an integer number of elements, which can reduce computational complexity, increase the computational speed of the forward projection operation, and thus improve the efficiency of image reconstruction.

[0036] Figure 1 This is a schematic diagram of an exemplary medical system according to some embodiments of this application. As shown, the medical system 100 may include a medical device 110, a processing device 120, a storage device 130, a terminal 140, and a network 150. The components of the medical system 100 may be connected in one or more of various ways. This is merely an example. Figure 1As shown, medical device 110 can be directly connected to processing device 120, such as by connecting medical device 110 and processing device 120 via a bidirectional connection cable as shown by the dashed arrow, or by connecting via network 150. Similarly, storage device 130 can be directly connected to medical device 110, such as by connecting medical device 110 and storage device 130 via a bidirectional connection cable as shown by the dashed arrow, or by connecting via network 150. Likewise, terminal 140 can be directly connected to processing device 120, such as by connecting terminal 140 and processing device 120 via a bidirectional connection cable as shown by the dashed arrow, or by connecting via network 150.

[0037] Medical device 110 can be configured to acquire object-related imaging data. Object-related imaging data may include images (e.g., image slices), projection data, or a combination thereof. In some embodiments, imaging data may be two-dimensional (2D) imaging data, three-dimensional (3D) imaging data, or four-dimensional (4D) imaging data, or any combination thereof. The object may be biological or non-biological. For example, the object may include a patient, an artificial object, etc. Or, for instance, the object may include a specific part of a patient's body, organ, and / or tissue. Specifically, the object may include the head, neck, chest, heart, stomach, blood vessels, soft tissue, tumor, etc., or any combination thereof. In this application, the terms "object" and "object group" are used interchangeably.

[0038] In some embodiments, medical device 110 may include a single-modality imaging device. For example, medical device 110 may include a positron emission tomography (PET) device, a single-photon emission computed tomography (SPECT) device, a magnetic resonance imaging (MRI) device (also known as an MR device or MR scanner), a computed tomography (CT) device, an ultrasound (US) device, an X-ray imaging device, etc., or any combination thereof. In some embodiments, medical device 110 may include a multimodal imaging device. Exemplarily, a multimodal imaging device may include a PET-CT device, a PET-MRI device, a SPET-CT device, etc., or any combination thereof. Multimodal imaging devices can perform multimodal imaging simultaneously. For example, a PET-CT device can simultaneously generate structural X-ray CT data and functional PET data in a single scan. A PET-MRI device can simultaneously generate MRI data and PET data in a single scan.

[0039] Processing device 120 can process data and / or information acquired from medical device 110, storage device 130, and / or terminal 140. For example, processing device 120 can acquire raw data collected by a medical device (e.g., medical device 110). As another example, processing device 120 can acquire an initial image. As yet another example, processing device 120 can generate a target image based on the raw data and the initial image according to an image reconstruction algorithm. In some embodiments, processing device 120 can be a single server or a group of servers. The server group can be centralized or distributed. In some embodiments, processing device 120 can be local or remote. For example, processing device 120 can access information and / or data from medical device 110, storage device 130, and / or terminal 140 via network 150. As yet another example, processing device 120 can directly connect to medical device 110, terminal 140, and / or storage device 130 to access information and / or data. In some embodiments, processing device 120 can be implemented on a cloud platform. For example, a cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, a cross-cloud, a multi-cloud, or a combination thereof. In some embodiments, the processing device 120 may be part of the terminal 140. In some embodiments, the processing device 120 may be part of the medical device 110.

[0040] Storage device 130 may store data, instructions, and / or any other information. In some embodiments, storage device 130 may store data acquired from medical device 110, processing device 120, and / or terminal 140. Data may include image data acquired by processing device 120, algorithms and / or models for processing the image data, etc. For example, storage device 130 may store raw data of an object acquired by the medical device. As another example, storage device 130 may store an initial image determined by processing device 120. As another example, storage device 130 may store a target image determined by processing device 120. As another example, storage device 130 may store a polar coordinate system and / or a reference Cartesian coordinate system determined by processing device 120. In some embodiments, storage device 130 may store data and / or instructions that processing device 120 and / or terminal 140 may execute or be used to execute the exemplary methods described in this application. In some embodiments, storage device 130 may include a mass storage device, removable memory, volatile read-write memory, read-only memory (ROM), etc., or any combination thereof. For example, mass storage devices may include disks, optical disks, solid-state drives, etc. For example, removable storage devices may include flash drives, floppy disks, optical disks, memory cards, zip disks, magnetic tapes, etc. For example, volatile read / write storage devices may include random access memory (RAM). For example, RAM may include dynamic RAM (DRAM), double data rate synchronous dynamic RAM (DDR SDRAM), static RAM (SRAM), thyristor RAM (T-RAM), zero-capacitance RAM (Z-RAM), high-speed RAM, etc. For example, ROM may include mask ROM (MROM), programmable ROM (PROM), erasable programmable ROM, electrically erasable programmable ROM (EEPROM), optical disc ROM (CD-ROM), and digital multifunction disk ROM, etc. In some embodiments, storage device 130 may be implemented on a cloud platform. By way of example only, a cloud platform may include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, cross-cloud, multi-cloud, etc., or any combination thereof.

[0041] In some embodiments, storage device 130 may be connected to network 150 to communicate with one or more other components of medical system 100 (e.g., processing device 120, terminal 140). One or more components of medical system 100 may access data or instructions stored in storage device 130 via network 150. In some embodiments, storage device 130 may be integrated into medical device 110.

[0042] Terminal 140 can connect to and communicate with medical device 110, processing device 120, and / or storage device 130. In some embodiments, terminal 140 may include mobile device 141, tablet computer 142, laptop computer 143, etc., or any combination thereof. For example, mobile device 141 may include mobile phone, personal digital assistant (PDA), gaming device, navigation device, point-of-sale (POS) device, laptop computer, tablet computer, desktop computer, etc., or any combination thereof. In some embodiments, terminal 140 may include input devices, output devices, etc. Input devices may include alphanumeric and other keys that can be input via a keyboard, touchscreen (e.g., with haptic or haptic feedback), voice input, eye-tracking input, brain monitoring system, or any other similar input mechanism. Other types of input devices may include cursor control devices, such as a mouse, trackball, or arrow keys. Output devices may include a display, printer, etc., or any combination thereof.

[0043] Network 150 may include any suitable network capable of facilitating information and / or data exchange within the medical system 100. In some embodiments, one or more components of the medical system 100 (e.g., medical device 110, processing device 120, storage device 130, terminal 140, etc.) may exchange information and / or data with other components of the medical system 100 via network 150. For example, processing device 120 and / or terminal 140 may retrieve raw data of an object from medical device 110 via network 150. As another example, processing device 120 and / or terminal 140 may retrieve information stored in storage device 130 via network 150. Network 150 may be and / or include public networks (e.g., the Internet), private networks (e.g., local area networks (LANs), wide area networks (WANs), etc.), wired networks (e.g., Ethernet), wireless networks (e.g., 802.11 networks, Wi-Fi networks, etc.), cellular networks (e.g., Long Term Evolution (LTE) networks), Frame Relay networks, Virtual Private Networks (VPNs), satellite networks, telephone networks, routers, hubs, switches, server computers, and / or any combination thereof. For example, network 150 may include cable networks, wired networks, fiber optic networks, telecommunications networks, intranets, wireless local area networks (WLANs), metropolitan area networks (MANs), public switched telephone networks (PSTNs), Bluetooth, etc. TM Network, ZigBee TMNetworks, near field communication (NFC) networks, and any combination thereof. In some embodiments, network 150 may include one or more network access points. For example, network 150 may include wired and / or wireless network access points, such as base stations and / or internet exchange points, through which one or more components of medical system 100 may connect to network 150 to exchange data and / or information.

[0044] In some embodiments, a medical coordinate system 160 may be provided for the medical system 100 to define the position of components (e.g., absolute position, position relative to other components) and / or the movement of components. For ease of illustration, the medical coordinate system 160 may include an R-axis, a T-axis, and an S-axis. Figure 1 The R-axis and S-axis shown can be horizontal, and the T-axis can be vertical. As shown, the positive R-axis can be viewed from the right to the left of the scanning stage when viewed from the front of the medical device 110; the positive T-axis can be viewed from the bottom of the frame of the medical device 110 (or from the floor on which the medical device 110 stands) to the top; and the positive S-axis can be viewed from the front of the medical device 110, in the direction in which the scanning stage moves out of the scanning channel (or aperture) of the medical device 110.

[0045] This specification is intended to be illustrative, not limiting. Many alternatives, modifications, and variations will be apparent to those skilled in the art. The features, structures, methods, and other features of the exemplary embodiments described herein can be combined in various ways to obtain additional and / or alternative exemplary implementations. However, these variations and modifications do not depart from the scope of the invention.

[0046] Figure 2 This is a schematic diagram of exemplary hardware and / or software components of an exemplary computing device on which the processing device 120, as shown in some embodiments of this application, may be implemented. Figure 2 As shown, computing device 200 may include processor 210, storage device 220, input / output (I / O) 230 and communication port 240.

[0047] Processor 210 may execute computer instructions (e.g., program code) and perform the functions of processing device 120 according to the techniques described herein. Computer instructions may include, for example, routines, programs, objects, components, data structures, procedures, modules, and functions that perform the specific functions described herein. For example, processor 210 may process image data acquired from medical device 110, terminal 140, storage device 130, and / or any other component of medical system 100. In some embodiments, processor 210 may include one or more hardware processors, such as microcontrollers, microprocessors, reduced instruction set computers (RISC), application-specific integrated circuits (ASICs), application-specific instruction set processors (ASIPs), central processing units (CPUs), graphics processing units (GPUs), physical processing units (PPUs), microcontroller units, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), advanced RISC computers (ARMs), programmable logic devices (PLDs), any circuit or processor capable of performing one or more functions, or any combination thereof.

[0048] For illustrative purposes only, only one processor is described in computing device 200. However, it should be noted that computing device 200 in this application may also include multiple processors. Therefore, as described in this application, operations and / or method steps performed by one processor may also be performed jointly or individually by multiple processors. For example, if in this application, the processors of computing device 200 execute process A and process B, it should be understood that process A and process B may also be performed jointly or individually by two or more different processors in computing device 200 (e.g., the first processor executes process A, the second processor executes process B, or the first and second processors jointly execute processes A and B).

[0049] Storage device 220 can store data / information acquired from medical device 110, terminal 140, storage device 130, and / or any other component of medical system 100. Storage device 220 can be connected to... Figure 1 The storage device 130 described herein is similar and will not be described in detail here.

[0050] I / O 230 can input and / or output signals, data, information, etc. In some embodiments, I / O 230 enables a user to interact with processing device 120. In some embodiments, I / O 230 may include input devices and output devices. Examples of input devices may include a keyboard, mouse, touchscreen, microphone, recording device, etc., or combinations thereof. Examples of output devices may include a display device, speaker, printer, projector, etc., or combinations thereof. Examples of display devices may include a liquid crystal display (LCD), a light-emitting diode (LED) based display, a flat panel display, a curved screen, a television device, a cathode ray tube (CRT), a touchscreen, etc., or combinations thereof.

[0051] Communication port 240 can be connected to a network (e.g., network 150) to facilitate data communication. Communication port 240 can establish a connection between processing device 120 and medical device 110, terminal 140, and / or storage device 130. This connection can be a wired connection, a wireless connection, any other communication connection capable of enabling data transmission and / or reception, and / or any combination of these connections. Wired connections can include, for example, electrical wires, fiber optic cables, telephone lines, etc., or any combination thereof. Wireless connections can include, for example, Bluetooth™ links, Wi-Fi, etc. TM Link, WiMa TM The communication port 240 may be a link, a WLAN link, a ZigBee link, a mobile network link (e.g., 3G, 4G, 5G), or any combination thereof. In some embodiments, the communication port 240 may be and / or include standardized communication ports, such as RS232 or RS485. In some embodiments, the communication port 240 may be a specially designed communication port. For example, the communication port 240 may be designed according to the Medical Digital Imaging and Communication (DICOM) protocol.

[0052] Figure 3 These are schematic diagrams of exemplary hardware and / or software components of an exemplary mobile device according to some embodiments of this application. In some embodiments, terminal 140 and / or processing device 120 may be implemented on mobile device 300, respectively.

[0053] like Figure 3 As shown, the mobile device 300 may include a communication platform 310, a display 320, a graphics processing unit (GPU) 330, a central processing unit (CPU) 340, I / O 350, memory 360, and storage 390. In some embodiments, the mobile device 300 may also include any other suitable components, including but not limited to a system bus or controller (not shown).

[0054] In some embodiments, the communication platform 310 may be configured to establish a connection between the mobile device 300 and other components of the medical system 100, and to enable the transmission of data and / or signals between the mobile device 300 and other components of the medical system 100. For example, the communication platform 310 may establish a wireless connection between the mobile device 300 and the medical device 110 and / or the processing device 120. The wireless connection may include, for example, a Bluetooth™ link, Wi-Fi, etc. TM Link, WiMax TM The communication platform 310 can also realize data and / or signal transmission between the mobile device 300 and other components of the medical system 100. For example, the communication platform 310 can transmit user-inputted data and / or signals to other components of the medical system 100. The input data and / or signals may include user instructions. As another example, the communication platform 310 can receive data and / or signals sent from the processing device 120. The received data and / or signals may include imaging data acquired by the medical device 110.

[0055] In some embodiments, the mobile operating system (OS) 370 (e.g., iOS) TM Android TM Windows Phone TM One or more applications (Apps) 380 can be loaded from storage 390 into memory 360 for execution by CPU 340. Application 380 may include a browser or any other mobile application suitable for receiving and presenting information from processing device 120. User interaction with the information flow can be achieved through I / O 350 and provided to processing device 120 and / or other components of medical system 100 via network 150.

[0056] To implement the various modules, units, and functions described in this application, a computer hardware platform can be used as the hardware platform for one or more elements described herein. A computer with user interface elements can be used to implement a personal computer (PC) or other type of workstation or terminal, although a computer can also act as a server if properly programmed. Those skilled in the art will be familiar with the structure, programming, and general operation of such computer devices, and therefore the accompanying drawings should be self-evident.

[0057] Figure 4 This is a schematic diagram of an exemplary processing device according to some embodiments of this application. In some embodiments, the processing device 120 may include a first acquisition module 410, a second acquisition module 420, and a determination module 430.

[0058] The first acquisition module 410 can be configured to acquire raw biodata collected by a medical device. Further description of acquiring the initial vascular image can be found elsewhere in this application (e.g., step 510 or its description).

[0059] The second acquisition module 420 can be configured to acquire an initial image. Further description of acquiring the initial image can be found elsewhere in this disclosure (e.g., step 520 or its description).

[0060] The determining module 430 can be configured to generate a target image based on the raw data and the initial image according to an image reconstruction algorithm. Further description of generating a target image based on the raw data and the initial image according to the image reconstruction algorithm can be found elsewhere in this application (e.g., step 530 or its description).

[0061] The modules in processing device 120 can connect to or communicate with each other via wired or wireless connections. Wired connections can include metal cables, optical fibers, hybrid cables, or any combination thereof. Wireless connections can include local area networks (LANs), wide area networks (WANs), Bluetooth, ZigBee, near field communication (NFC), or any combination thereof.

[0062] It should be noted that the above description of the processing device 120 is for illustrative purposes only and is not intended to limit the scope of this application. Various changes and modifications can be made by those skilled in the art based on the teachings of this application. However, these changes and modifications do not depart from the scope of this application. In some embodiments, one or more modules can be combined into a single module. For example, the first acquisition module 410 and the second acquisition module 420 can be combined into a single module. In some embodiments, one or more modules can be added to or omitted from the processing device 120. For example, the processing device 120 may also include a storage module (…). Figure 4 (not shown in the image), which is configured to store data and / or information associated with the medical system 100 (e.g., raw data, initial images, target images, reference Cartesian coordinate system, polar coordinate system).

[0063] Figure 5 This is a flowchart illustrating an exemplary process for generating a target image according to some embodiments of this application. In some embodiments, process 500 may be executed by medical system 100. For example, process 500 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., storage device 130, storage device 220, and / or memory 390). In some embodiments, processing device 120 (e.g., processor 210 of computing device 200, CPU 340 of mobile device 300, and / or...) Figure 4One or more modules shown can execute this set of instructions and can be instructed to execute process 500 accordingly. The operation of the processes presented below is merely exemplary. In some embodiments, process 500 can be implemented by one or more additional operations not described and / or one or more operations not discussed. Furthermore, Figure 5 The sequence of operations in process 500 shown and described below is not intended to be restrictive.

[0064] In step 510, the processing device 120 (e.g., the first acquisition module 410) can acquire the raw data collected by the medical device.

[0065] In some embodiments, raw data may include raw projection data acquired by scanning an object using a medical device (e.g., medical device 110). Raw data (e.g., raw CT projection data) may reflect attenuation information of radiation rays (e.g., X-rays) passing through the object. In some embodiments, the object may include biological and / or non-biological objects. For example, the object may include specific body parts such as the head, chest, abdomen, etc., or any combination thereof. As another example, the object may be an artificial composition of living or non-living organic and / or inorganic matter.

[0066] In some embodiments, the processing device 120 can acquire raw biometric data from one or more projection angles using a medical device. For example, a medical device (e.g., a CT scanner) can scan an object by irradiating it with X-rays. During the scan, the radiation source and detector can be positioned along the scan axis (e.g., as shown in the image) with the gantry. Figure 1 The coordinate system shown (S-axis 160) is rotated to scan the object from different angles.

[0067] In some embodiments, the projection angle may be defined by the line connecting the center of rotation of the radiation source and the frame and the axis in the coordinate system (e.g., ...). Figure 1 The angle formed by the R-axis and T-axis in the coordinate system 160 shown. In some embodiments, the radiation source can continuously emit radiation rays (e.g., X-rays) towards the object as the gantry rotates. The detector can collect multiple raw data corresponding to multiple projection angles (e.g., multiple projection angles from 0° to 360°). Alternatively, the radiation source can intermittently emit radiation rays (e.g., X-rays) towards the object as the gantry rotates.

[0068] In some embodiments, processing device 120 may acquire raw data from one or more components of medical system 100 (e.g., medical device 110, storage device 130, terminal 140). Alternatively or additionally, processing device 120 may acquire raw data from an external source (e.g., a medical database) via network 150.

[0069] In step 520, the processing device 120 (e.g., the second acquisition module 410) can acquire the initial image.

[0070] In some embodiments, the processing device 120 may determine an initial image based on multiple raw data corresponding to multiple projection angles collected by the detector.

[0071] In some embodiments, the initial image may include multiple elements (e.g., pixels, voxels) having estimated features (e.g., grayscale values, intensity). In some embodiments, the grayscale values ​​of the elements in the initial image may be set to different values ​​or the same value. For example, the grayscale values ​​of the elements in the initial image may be set to 0 or 1. In some embodiments, the initial image may be determined based on default settings, manually set by a user (e.g., a doctor, technician), or determined by the processing device 120 as needed.

[0072] In step 530, the processing device 120 (e.g., the determining module 430) can generate a target image based on the raw data and the initial image according to the image reconstruction algorithm.

[0073] In some embodiments, the image reconstruction algorithm may include an iterative reconstruction algorithm. For example, the iterative reconstruction algorithm may include Adaptive Statistical Iterative Reconstruction (ASiR), Model Based Iterative Reconstruction (MBiR), Iterative Reconstruction in Image Space (iRIS), Sinogram Affirmed Iterative Reconstruction (SAFIRE), Double Model Based Iterative Reconstruction (DMBiR), Adaptive Iterative Dose Reduction (AIDR), IMR, etc., or any combination thereof.

[0074] In some embodiments, the processing device 120 can generate a target image by iteratively updating an initial image according to an iterative reconstruction algorithm. The initial image can be iteratively updated by optimizing an objective function. The objective function can be determined based on the original data, the initial image (or the updated image), and a regularization term. As used herein, a regularization term can refer to a term that can be used to regularize the original raw data during image reconstruction. In some embodiments, the regularization term can include a total variation-based (TV-based) regularization term, a Tikhonov regularization term, a bilateral total variation regularization term, a local information adaptive total variation regularization term, etc., or any combination thereof. Further description of generating the target image can be found elsewhere in this application (e.g., Figure 6-8 (and its description).

[0075] It should be noted that the above description is for illustrative purposes only and is not intended to limit the scope of this application. Various changes and modifications can be made by those skilled in the art based on the teachings of this application. However, these changes and modifications do not depart from the scope of this application. In some embodiments, steps 510 and 520 may be combined into a single operation.

[0076] Figure 6 This is a flowchart illustrating an exemplary process for generating a target image according to some embodiments of this application. In some embodiments, process 600 may be executed by medical system 100. For example, process 600 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., storage device 130, storage device 220, and / or memory 390). In some embodiments, processing device 120 (e.g., processor 210 of computing device 200, CPU 340 of mobile device 300, and / or...) Figure 4 One or more modules shown can execute this set of instructions and can be instructed to execute process 600 accordingly. The operation of the process shown below is intended to illustrate the problem. In some embodiments, process 600 can be implemented by one or more additional operations not described and / or one or more operations not discussed. Furthermore, Figure 6 The sequence of operations in process 600 shown and described below is not intended to be restrictive.

[0077] In some embodiments, one or more operations of process 600 may be performed to achieve, as in combination Figure 5 At least a portion of step 530. For example, process 600 can be executed to implement the current iteration in the iterative image reconstruction process.

[0078] In step 610, the processing device 120 (e.g., the determining module 430) can determine the processed initial image by transforming the initial image from an initial coordinate system to a target coordinate system. Multiple element values ​​in the processed initial image can be represented by multiple grids in the target coordinate system. The multiple grids in the target coordinate system can include integer grids and non-integer grids.

[0079] In some embodiments, the initial coordinate system and the target coordinate system may include a Cartesian coordinate system, a polar coordinate system, a cylindrical coordinate system, or a spherical coordinate system, which is not limited herein. The initial coordinate system and the target coordinate system may be different.

[0080] In some embodiments, the target coordinate system can be determined based on the structure of the detector in the medical device.

[0081] In some embodiments, the structure of the detector may refer to the arrangement of the detectors in the medical device. The target coordinate system can be determined based on the arrangement of the detectors in the medical device.

[0082] For illustrative purposes only and not intended to limit the scope of this application, the following description uses Cartesian coordinates as the initial coordinate system and polar coordinates as the target coordinate system as an example.

[0083] In some embodiments, the processing device 120 may establish a reference Cartesian coordinate system corresponding to a reference projection angle. The reference projection angle may be manually set by a user of the medical system 100 or determined by one or more components of the medical system 100 (e.g., the processing device 120). In some embodiments, the origin of the reference Cartesian coordinate system (e.g., as shown in the image) is... Figure 11 The origin O' shown can be located at the center of rotation of the medical device gantry. Referencing the first axis direction of the Cartesian coordinate system (e.g., as...) Figure 11 The Y-axis direction (as shown) can be along the origin and a line connecting one of the multiple detector units of the medical device's detectors. The second axis direction (e.g., as shown) is referenced in a Cartesian coordinate system. Figure 11 The X-axis direction (as shown) can be perpendicular to the first axis direction of the reference Cartesian coordinate system. The second axis direction can lie in a plane perpendicular to the detector plane. The third axis direction of the reference Cartesian coordinate system can be perpendicular to the plane formed by the first and second axes directions of the reference Cartesian coordinate system.

[0084] In some embodiments, the reference Cartesian coordinate system may include multiple grids. In this application, an image in the reference Cartesian coordinate system may refer to an image (e.g., multiple element values ​​of multiple elements (e.g., pixels, voxels) in the image) represented by multiple integer grids in the reference Cartesian coordinate system. For example, each element of the image may correspond to an integer grid in the reference Cartesian coordinate system. In some embodiments, the size of each grid in the multiple grids may be (approximately) the same or different. In some embodiments, the size of each grid in the multiple grids of the reference Cartesian coordinate system may be related to the size of the elements of the reconstructed image and the extent of the objects used for image reconstruction.

[0085] In some embodiments, the processing device 120 can establish a polar coordinate system. In some embodiments, the polar coordinate system can be established based on the structure of the detector of the medical device. For example, the detector of a CT device (e.g., a curved detector) may include multiple detector units. The multiple detector units may include those along a first direction (e.g., as shown in the image). Figure 9 At least one row of detector units arranged in the M direction (as shown) and along the second direction (e.g., as shown) Figure 9 At least one column of detector units arranged in the N direction (as shown). In some embodiments, when the X-ray tube is located directly above the scanning stage of the medical device and the detector is located directly below the scanning stage of the medical device, such as... Figure 1 As shown, the first direction can be substantially parallel to the R-axis of the medical coordinate system 160, and the second direction can be parallel to the S-axis of the medical coordinate system 160. The origin of the polar coordinate system (e.g., as...) Figure 9-11 The origin O shown can be located at the focal point of the X-ray tube in the medical device. The first axis direction of the polar coordinate system can be the same as the first axis direction of the reference Cartesian coordinate system. For example, the first axis direction of the polar coordinate system (e.g., as...) Figure 9 The L-axis direction is shown, as follows: Figure 11 The L-axis direction (as shown) can extend along a line connecting the origin and one of the multiple detector units of the medical device's detector. The second axis direction of the polar coordinate system (e.g., as shown) Figure 9 The γ-axis direction (as shown) can be the angular direction between the line connecting the origin and one of the detector elements in at least one row of detector elements and the first axis direction of the polar coordinate system. The third axis direction of the polar coordinate system (e.g., as shown) Figure 9 The φ-axis direction shown can be the angular direction between the line connecting the detector units and the origin in multiple detector units and the plane formed by the first and second axis directions of the polar coordinate system (also known as the L-γ plane).

[0086] In some embodiments, the polar coordinate system may include multiple grids. In this application, an image in the polar coordinate system may refer to an image (e.g., multiple element values ​​of multiple elements (e.g., pixels, voxels) in the image), represented by multiple integer grids in the polar coordinate system. In some embodiments, the size of each grid in the multiple grids may be (approximately) the same or different. In some embodiments, the size of each grid in the multiple grids may be related to the size of a corresponding detector unit in a plurality of detector units. In some embodiments, the width of a grid along a second axis of the polar coordinate system may be related to the width of the corresponding detector unit along a first direction. For example, the width of the detector unit along the first direction may be an integer multiple of the width of the corresponding grid along the second axis of the polar coordinate system. In some embodiments, the height of a grid along a third axis of the polar coordinate system may be related to the height of the corresponding detector unit along a second direction. For example, the height of the detector unit along the second direction may be an integer multiple of the height of the corresponding grid along the third axis of the polar coordinate system.

[0087] In some embodiments, the polar coordinates of the grid in the polar coordinate system (corresponding to the element value of an element at a certain grid position) can be determined according to equation (1): (1), in, , and Represents the polar coordinates (e.g., first axis coordinates, second axis coordinates, and third axis coordinates) of the grid (i, j, k) in the polar coordinate system. This refers to the grid length along the first axis of the polar coordinate system; It refers to the angle corresponding to the width of the grid along the second axis of the polar coordinate system; It refers to the third coordinate of the grid (i, j, k-1) in the polar coordinate system; This refers to the grid (i, j, k-1) (corresponding to the detector element). The height along the third axis of the polar coordinate system; This refers to the grid (i, j, k) (corresponding to the detector element). The angle corresponding to the height along the third axis of the polar coordinate system. In some embodiments, grids (i, j, k) and grids (i, j, k-1) may correspond to the same detector element. and They can be the same detector element. In some embodiments, grids (i, j, k) and grids (i, j, k-1) can correspond to two adjacent detector elements. and It can be two different detector units.

[0088] In some embodiments, the angle formed by the two edges of the mesh along the second axis of the polar coordinate system (also called the angle corresponding to the width) can be determined according to equation (2) (e.g., as shown in the figure). Figure 9 Angle shown ): (2), in, This refers to the angle corresponding to the grid width along the second axis of the polar coordinate system; It refers to the angle corresponding to the width of the corresponding detector unit along the first direction; Represents an integer.

[0089] In some embodiments, the angle formed by the two edges of the grid along the third axis of the polar coordinate system (also called the angle corresponding to the height) can be determined according to equation (3) (e.g., as shown in equation (3)). Figure 9 Angle shown ): (3), in, It refers to the angle corresponding to the height of the grid along the third axis of the polar coordinate system; This refers to connecting the origin and the detector unit. The first line on the first side (e.g., the upper side) connects the origin and the detector unit. The angle between the second line on the second side (opposite to the first side) (e.g., the lower side); Represents integers. Detector unit The first or second side can be along the direction of the first axis of the polar coordinate system. In some embodiments, It can be determined according to equation (4): (4), in, This refers to the distance between the focal point of the X-ray tube of the medical device and the detector of the medical device; s is the serial number of the detector unit in the detector unit column; This indicates the height of the detector unit along the second direction.

[0090] In some embodiments, the shape of each grid in the L-γ plane can be approximated as a square. For example, the length of each grid along the first axis of the polar coordinate system can be substantially the same as the width of each grid along the second axis of the polar coordinate system.

[0091] Figure 9 This is a schematic diagram of an exemplary polar coordinate system according to some embodiments of this application. For example... Figure 9As shown, object 910 can be scanned by a medical device. The medical device may include multiple detector units (e.g., detector unit 920). The multiple detector units may include at least one row of detector units arranged along a first direction M and at least one column of detector units arranged along a second direction N. The polar coordinate system may include an origin O, a first axis direction L, a second axis direction γ, and a third axis direction φ. The polar coordinate system may include multiple grids (e.g., grid 930). The size of each grid in the multiple grids may be related to the size of a corresponding detector unit in the multiple detector units. Figure 9 As shown, the dimensions of grid 930 can be related to the dimensions of detector element 920. For example, the width W1 of grid 930 along the second axis γ of the polar coordinate system may be related to the width W2 of detector element 920 along the first direction M. The height H1 of grid 930 along the third axis φ of the polar coordinate system may be related to the height H2 of detector element 920 along the second direction N. The length K of grid 930 along the first axis L of the polar coordinate system may be substantially the same as the width W1 of grid 930 along the second axis γ of the polar coordinate system.

[0092] In some embodiments, under the condition of constant grid size, the farther the grid is from the origin of the polar coordinate system along the first axis, the smaller the angle between the two sides of the grid along the first axis (also known as the angle corresponding to the grid width). Figure 10 This is a schematic diagram of an exemplary mesh in a polar coordinate system according to some embodiments of this application. For example... Figure 10 As shown, the distance between the origin O and grid 1020 can be greater than the distance between the origin O and grid 1010. The angle between edges C and D of grid 1020 along the first axis L can be smaller than the angle between edges A and B of grid 1010 along the first axis L. The angle between edges G and H of grid 1020 can be smaller than the angle between edges E and F of grid 1010. Therefore, the size of grid 1020 can be substantially the same as the size of grid 1010.

[0093] In some embodiments, a detector unit may correspond to one or more grids along a first direction M and / or a second direction N. For example, detector unit 1030 may correspond to a grid 1010 along the first direction M and the second direction N. As another example, detector unit 1030 may correspond to at least two grids 1020 along the first direction M or the second direction N. In some embodiments, if the size of the detector unit (e.g., the width of the detector unit along the first direction M and the height of the detector unit along the second direction N) is relatively small (e.g., less than a threshold), multiple detector units may correspond to a grid along the first direction M and / or the second direction N.

[0094] It should be noted that Figure 9 and Figure 10 The detector cells and grids in the polar coordinate system shown are for illustrative purposes only and are not intended to limit the scope of this application. The detectors in medical devices can have any shape. The grids in the polar coordinate system can also have any shape. For example, the detector can be a flat panel detector with a square or rectangular shape. The grids in the polar coordinate system can also have a square or rectangular shape.

[0095] In some embodiments, the projected edges of the plurality of grids on the detector plane may coincide with or be parallel to the edges of the detector. As used herein, the detector plane refers to a plane perpendicular to the first axial direction L of the polar coordinate system.

[0096] In some embodiments, the raw raw data may correspond to one or more initial projection angles. For example, when the medical device is located at one or more initial projection angles, the medical device may acquire partial raw raw data. The initial projection angle may be different from the reference projection angle. The processing device 120 can determine the second processed initial image by transforming the initial image from an initial Cartesian coordinate system to a reference Cartesian coordinate system. The processing device 120 can determine the processed initial image by transforming the second processed initial image from a reference Cartesian coordinate system to a polar coordinate system. Further description of methods for determining the processed initial image can be found elsewhere in this application (e.g., Figure 7 (and its description).

[0097] In step 620, the processing device 120 (e.g., the determination module 430) can determine the first projection data by performing a forward projection operation on the processed initial image.

[0098] According to the forward projection operation, the processing device 120 can convert data in the image domain (e.g., the processed initial image) into numbers in the projection domain (e.g., first projection data). In some embodiments, the processing device 120 can convert the processed initial image into first projection data by multiplying the processed initial image by the forward projection matrix. In some embodiments, the forward projection matrix can be the default setting of the medical system 100, or it can be adjusted under different circumstances.

[0099] In some embodiments, the processing device 120 may determine the first projection data according to equation (5): (5), in, This refers to the projection data (e.g., the first projection data). It refers to the elemental volume of an element (e.g., a voxel) in an image (e.g., the processed initial image); It refers to the angle corresponding to the width of the detector unit along the first direction; This refers to the angle corresponding to the height of the detector unit along the second direction; The element value represents an element (e.g., a voxel) in an image (e.g., the processed initial image); i refers to the number (or count) of elements along the path of the X-ray emitted from the X-ray tube of the medical device; j and k represent the number (or count) of elements corresponding to detector units [m, n], where m and n represent the sequence numbers of detector units in at least one row and at least one column of detector units, respectively. In some embodiments, the element volume of an element in the image can be determined based on the element's position in the coordinate system and the relationship between the element volume and the element position. For example, the relationship between the element volume and the element position can be expressed as equation (6): (6), in, It refers to the elemental volume of an element (e.g., a voxel) in an image; Refers to functional relationships; This refers to the position of an element in a coordinate system (e.g., the polar coordinates of an element in a polar coordinate system).

[0100] Therefore, multiple elements of an image (e.g., the processed initial image) can be discretized based on the structure of the detector in the medical device, and the projected edges of multiple elements on the detector plane can coincide with or be parallel to the detector edges. When performing a forward projection operation on the processed initial image, a summation operation can be performed on an integer number of elements, which can improve the computational speed of the forward projection operation and thus improve the efficiency of image reconstruction.

[0101] In step 630, the processing device 120 (e.g., the determination module 430) can determine the second projection data based on the first projection data and the raw data.

[0102] In some embodiments, the processing device 120 may determine the second projection data based on the difference between the first projection data and the original raw data. For example, the processing device 120 may determine the second projection data by subtracting the first projection data (or the original raw data) from the original raw data (or the first projection data). As another example, the processing device 120 may determine the ratio between the first projection data and the original raw data as the second projection data.

[0103] In step 640, the processing device 120 (e.g., the determination module 430) can determine the first differential image by performing a back-projection operation on the second projection data.

[0104] According to the backprojection operation, the processing device 120 can convert data in the projection domain (e.g., second projection data) into data in the image domain (e.g., a first difference image). In some embodiments, the processing device 120 can convert second prediction data into a first difference image by multiplying the second projection data by the backprojection matrix. In some embodiments, the backprojection matrix can be the default setting of the medical system 100, or it can be adjusted under different circumstances.

[0105] In some embodiments, the processing device 120 may determine the first difference image according to equation (7): (7), in, This refers to projection data (e.g., second projection data). It refers to the elemental volume of an element (e.g., a voxel) in an image; It refers to the angle corresponding to the width of the detector unit along the first direction; This refers to the angle corresponding to the height of the detector unit along the second direction; i refers to the element value of an element (e.g., a voxel) in an image (e.g., a first differential image); i refers to the number (or count) of elements along the path of the X-ray emitted from the X-ray tube of the medical device; j and k represent the number (or count) of elements corresponding to detector units [m, n], where m and n represent the sequence numbers of detector units in at least one row of detector units and at least one column of detector units, respectively.

[0106] In step 650, the processing device 120 (e.g., the determination module 430) can determine the second difference image by transforming the first difference image from the target coordinate system to the initial coordinate system. Multiple element values ​​in the second difference image can be represented by multiple grids in the initial coordinate system. The multiple grids in the initial coordinate system can include integer grids and non-integer grids.

[0107] For illustrative purposes only and without limiting the scope of this application, the following description uses the Cartesian coordinate system as the initial coordinate system and the polar coordinate system as the target coordinate system as an example.

[0108] In some embodiments, the processing device 120 can determine the third difference image by transforming the first difference image from a polar coordinate system to a reference Cartesian coordinate system. The processing device 120 can determine the second difference image by transforming the third difference image from a reference Cartesian coordinate system to an initial Cartesian coordinate system. Further description of how to determine the second difference image can be found elsewhere in this application (e.g., Figure 8 (and its description).

[0109] In step 660, the processing device 120 (e.g., the determining module 430) may generate a target image based on one or more second difference images. In some embodiments, the one or more second difference images may correspond to one or more initial projection angles.

[0110] In some embodiments, the processing device 120 can update an initial image based on multiple initial projection angles and determine the updated image as the target image. As an example only, in the first iteration, the processing device 120 can determine a second difference image based on the initial image and a first initial projection angle, as described in steps 610-650, and obtain a first updated image by updating the initial image based on the second difference image. In the second iteration, the processing device 120 can determine an updated second difference image based on the first updated image and a second initial projection angle, as described in steps 610-650, and obtain a second updated image by updating the first updated image based on the updated second difference image. In the nth iteration, the processing device 120 can determine an updated second difference image based on the nth updated image and the nth initial projection angle, as described in steps 610-650, and obtain an nth updated image by updating the (n-1)th updated image based on the updated second difference image. The processing device 120 can determine the nth updated image as the target image.

[0111] Taking the image reconstruction process based on the gradient descent algorithm as an example, processing device 120 can determine a first gradient descent value based on a second difference image and a regularization term. As described in steps 610-650, processing device 120 can determine a second difference image based on an initial image and an initial projection angle from one or more initial projection angles. Processing device 120 can update the initial image based on the first gradient descent value. For example, processing device 120 can generate a first updated image by adding the first gradient descent value to the initial image.

[0112] In the next iteration, based on another initial projection angle from one or more initial projection angles, processing device 120 can determine the processed first updated image by transforming the first updated image from the initial Cartesian coordinate system to the polar coordinate system, as described in conjunction with step 610. Processing device 120 can determine updated first projection data by performing a forward projection operation on the processed first updated image, as described in conjunction with step 620. Processing device 120 can determine updated second projection data based on the updated first projection data and the original raw data, as described in conjunction with step 630. Processing device 120 can determine the updated first difference image by performing a back projection operation on the updated second projection data, as described in conjunction with step 640. Processing device 120 can determine the updated second difference image by transforming the updated first difference image from the polar coordinate system to the initial Cartesian coordinate system, as described in conjunction with step 650. Processing device 120 can determine a second gradient descent value based on the updated second difference image and a regularization term. Processing device 120 can update the first updated image based on the second gradient descent value to generate the second updated image.

[0113] In some embodiments, the processing device 120 may update the initial image based on at least two second differential images.

[0114] Taking an image reconstruction process based on the gradient descent algorithm as an example, processing device 120 can determine a first gradient descent value (e.g., the average or weighted value of the gradient descent values ​​corresponding to at least two second difference images) based on the gradient descent values ​​and regularization terms corresponding to at least two second difference images. As described in conjunction with steps 610-650, processing device 120 can determine at least two second difference images based on an initial image and at least two initial projection angles from one or more initial projection angles. Processing device 120 can update the initial image based on the first gradient descent value. For example, processing device 120 can generate a first updated image by adding the first gradient descent value to the initial image.

[0115] In the next iteration, processing device 120 may determine the first updated image as the initial updated image, and based on the first updated image and at least two additional initial projection angles from one or more initial projection angles, determine at least two updated second difference images, as described above. Processing device 120 may determine a second gradient descent value based on the gradient descent value and regularization term corresponding to the at least two updated second difference images. Processing device 120 may update the first updated image based on the second gradient descent value to generate the second updated image.

[0116] In some embodiments, steps 610-660 may be repeated until a termination condition is met. In some embodiments, in response to determining that a termination condition is met in the current iteration, the processing device 120 may determine the updated image in the current iteration (e.g., a first updated image, a second updated image, etc.) as the target image. The termination condition may be related to the objective function or the number of iterations in the iterative process. For example, a termination condition may be met if the value of the objective function is minimized or less than a threshold. As another example, a termination condition may be met when a specified number (or counted) of iterations are performed during image reconstruction.

[0117] In some embodiments, the processing device 120 may update the initial image based on one or more second difference images. Taking an image reconstruction process according to a gradient descent algorithm as an example, the processing device 120 may determine one or more gradient descent values ​​based on one or more second difference images and a regularization term. As described in conjunction with steps 610-650, the processing device 120 may determine one or more second difference images based on the initial image and one or more initial projection angles. The processing device 120 may update the initial image based on one or more gradient descent values. For example, the processing device 120 may determine an average gradient descent value or a weighted average gradient descent value of one or more gradient descent values, and generate an updated image by adding the average gradient descent value or the weighted average gradient descent value to the initial image.

[0118] In some embodiments, the processing device 120 may determine the updated image as the target image.

[0119] It should be noted that the above description is for illustrative purposes only and is not intended to limit the scope of this application. Various changes and modifications can be made by those skilled in the art based on the teachings of this application. However, these changes and modifications do not depart from the scope of this application.

[0120] Figure 7 This is a flowchart illustrating an exemplary process for determining a processed initial image according to some embodiments of this application. In some embodiments, process 700 may be executed by medical system 100. For example, process 700 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., storage device 130, storage device 220, and / or memory 390). In some embodiments, processing device 120 (e.g., processor 210 of computing device 200, CPU 340 of mobile device 300, and / or...) Figure 4 One or more modules shown can execute this set of instructions and can be instructed to execute process 700 accordingly. The steps of the process presented below are intended as examples. In some embodiments, process 700 can be implemented by one or more additional operations not described and / or one or more operations not discussed. Furthermore, Figure 7 The order of operations of process 700 shown and described below is not intended to be limiting. In some embodiments, one or more operations of process 700 may be performed to achieve, as in combination Figure 6 At least a portion of step 610.

[0121] In step 710, the processing device 120 (e.g., the determination module 430) can determine the second-processed initial image by transforming the initial image from an initial coordinate system to a reference coordinate system. The reference coordinate system may correspond to a reference projection angle. The reference coordinate system may include multiple grids. The multiple grids may include integer grids and non-integer grids.

[0122] In some embodiments, the reference coordinate system may include a Cartesian coordinate system, a polar coordinate system, a cylindrical coordinate system, or a spherical coordinate system, which is not limited herein.

[0123] For illustrative purposes only and without limiting the scope of this application, the following description uses the Cartesian coordinate system as the initial coordinate system and the polar coordinate system as the target coordinate system as an example.

[0124] In some embodiments, the processing device 120 can determine the second-processed initial image by transforming the initial image from an initial Cartesian coordinate system corresponding to the initial projection angle to a reference Cartesian coordinate system corresponding to the reference projection angle.

[0125] Figure 11 These are schematic diagrams of exemplary reference Cartesian coordinate systems and exemplary polar coordinate systems according to some embodiments of this application. Figure 12 These are schematic diagrams illustrating exemplary reference Cartesian coordinate systems and exemplary initial Cartesian coordinate systems according to some embodiments of this application. Figure 11 and 12 As shown, referencing the Cartesian coordinate system This can include the origin O', the X-axis direction, the Y-axis direction, and the Z-axis direction. Figure 11 and 12 (Not shown in the image). Polar coordinate system The first axis direction L may be relative to the reference Cartesian coordinate system. The X-axis directions are the same. Initial Cartesian coordinate system. This may include the origin O', the X' axis direction, the Y' axis direction, and the Z' axis direction. Figure 11 and 12 (Not shown in the image). Referencing the Cartesian coordinate system. Possibly corresponding to the reference projection angle Initial Cartesian coordinate system It can correspond to the initial projection angle The angle between the axes of the reference Cartesian coordinate system (e.g., the x-axis and y-axis) and the axes of the initial Cartesian coordinate system (e.g., the x'-axis and y'-axis) can be determined as follows: In some embodiments, the processing device 120 may determine a reference Cartesian coordinate system. and the initial Cartesian coordinate system The transformation relationship between them (e.g., rotation matrix). For example, it can be achieved by referencing a Cartesian coordinate system. Multiply the coordinates of the corresponding elements in the original coordinate system by the rotation matrix to determine the initial Cartesian coordinate system. The coordinates of the elements in the middle.

[0126] In this application, multiple elements in an image (e.g., pixels, voxels) can each correspond to multiple grids in a coordinate system, so that multiple element values ​​of multiple elements in the image can be represented by multiple grids in the coordinate system. For example, for each of the multiple elements in the image, the position of the element in the coordinate system (i.e., the grid where the element is located) can be determined based on the origin of the coordinate system and the spacing between adjacent elements along the coordinate axes. The origin of the coordinate system can correspond to the origin of the image. As an example only, the processing device 120 can obtain multiple element values ​​of multiple pixels at multiple grids in an initial coordinate system based on multiple element values ​​of multiple elements in the image. Each of the multiple element values ​​of multiple elements in the image can correspond to the element value of an element at a grid in the initial coordinate system. Based on the transformation relationship, multiple element values ​​of multiple elements at multiple grids in the initial coordinate system can each correspond to multiple element values ​​of multiple elements at multiple grids in a reference coordinate system, and based on the transformation relationship, multiple element values ​​of multiple cells at multiple grids in the reference coordinate system can each correspond to multiple element values ​​of multiple elements at multiple grids in the target coordinate system. More details about the transformation relationship can be found elsewhere in this application, for example, Figure 7 And its related descriptions.

[0127] In some embodiments, the processing device 120 can obtain multiple element values ​​of multiple elements at multiple grids (e.g., integer grids) in a reference Cartesian coordinate system by performing interpolation operations on multiple element values ​​of multiple elements at multiple grids (e.g., integer grids) in an initial Cartesian coordinate system. For example, the processing device 120 can obtain multiple element values ​​of multiple elements at multiple non-integer grids in an initial Cartesian coordinate system by performing interpolation operations on multiple element values ​​of multiple elements at multiple integer grids in an initial Cartesian coordinate system. The multiple non-integer grids in the initial Cartesian coordinate system may correspond to multiple integer grids in the reference coordinate system. As used herein, an integer grid in a coordinate system refers to a grid whose coordinates are integers, and a non-integer grid in a coordinate system refers to a grid whose coordinates are non-integers. The interpolation operation can be performed based on nearest neighbor interpolation algorithms, multi-strip interpolation algorithms, trilinear interpolation algorithms, deep learning algorithms, etc., or any combination thereof.

[0128] As an example only, processing device 120 can determine multiple element values ​​of multiple elements at multiple integer grids in a reference Cartesian coordinate system according to equation (8): (8), in, It refers to the element value of the element at the integer grid position in the initial Cartesian coordinate system; It refers to the element value of the element at the non-integer grid position in the initial Cartesian coordinate system; This refers to the element value at an integer grid location in the Cartesian coordinate system. This refers to interpolation operations (e.g., trilinear interpolation).

[0129] The processing device 120 can obtain multiple element values ​​of multiple elements at multiple integer grids in a reference Cartesian coordinate system based on multiple element values ​​of multiple elements at multiple non-integer grids in the initial Cartesian coordinate system. For example, the transformation relationship between the element coordinates at non-integer grids in the initial Cartesian coordinate system and the element coordinates at integer grids in the reference Cartesian coordinate system can be determined according to equations (9)-(10): (9), (10) in, This represents the coordinates of the element in the initial Cartesian coordinate system; Indicates the coordinates of the element in the reference Cartesian coordinate system; and This represents the rotation matrix. Therefore, the element values ​​at non-integer grid positions in the initial Cartesian coordinate system ( ) may be related to the element values ​​at the integer grid of the reference Cartesian coordinate system ( The same. According to equation (8), the element values ​​of the elements at the non-integer grid points in the initial Cartesian coordinate system are ( The coordinates can be determined by performing interpolation operations on multiple element values ​​at multiple integer grids in the initial Cartesian coordinate system. In some embodiments, the transformation relationship between the element coordinates at non-integer grids in the initial Cartesian coordinate system and the element coordinates at integer grids in the reference Cartesian coordinate system can be stored in the storage device (e.g., storage device 130) of the medical system 100.

[0130] Furthermore, the processing device 120 can determine the initial image after the second processing based on multiple element values ​​of multiple elements at multiple grids (e.g., integer grids) in a reference Cartesian coordinate system. For example, the processing device 120 can determine the initial image after the second processing by combining multiple element values ​​of multiple elements at multiple integer grids in a reference Cartesian coordinate system.

[0131] In step 720, the processing device 120 (e.g., the determination module 430) can determine the processed initial image by transforming the second processed initial image from the reference coordinate system to the target coordinate system.

[0132] For illustrative purposes only and without limiting the scope of this application, the following description uses the Cartesian coordinate system as the initial coordinate system and the polar coordinate system as the target coordinate system as an example.

[0133] In some embodiments, the processing device 120 can obtain multiple element values ​​of multiple elements at multiple non-integer grids in a reference Cartesian coordinate system by performing interpolation operations on multiple element values ​​of multiple elements at multiple integer grids in a reference Cartesian coordinate system. The multiple non-integer grids in the reference Cartesian coordinate system may correspond to multiple integer grids in a polar coordinate system.

[0134] For example, processing device 120 can obtain multiple element values ​​for multiple elements at multiple non-integer grids in a reference Cartesian coordinate system according to equation (11): (11), in, Represents the element value at an integer grid position in polar coordinates; This refers to the element value at a non-integer grid location in the Cartesian coordinate system. This refers to the element value at an integer grid location in the Cartesian coordinate system. This refers to interpolation operations (e.g., trilinear interpolation).

[0135] The processing device 120 can obtain multiple element values ​​of multiple elements at multiple integer grids in the polar coordinate system based on multiple element values ​​of multiple elements at multiple non-integer grids in the reference Cartesian coordinate system. For example, the transformation relationship between the element coordinates at non-integer grids in the reference Cartesian coordinate system and the element coordinates at integer grids in the polar coordinate system can be determined according to equations (12)-(14): (12), (13) (14) in, This refers to the distance between the focal point of the X-ray tube in the medical device and the rotation center of the medical device's frame; This refers to the coordinates of an element in a polar coordinate system at an integer grid position; ( ), ( ), ( ()) refers to the element coordinates at non-integer grid points in the reference Cartesian coordinate system. Therefore, the element value at a non-integer grid point in the reference Cartesian coordinate system () ) may be related to the value of an element at an integer grid location in polar coordinates. The same. According to equation (11), the element values ​​of elements at non-integer grids in the reference Cartesian coordinate system can be determined by performing interpolation on the element values ​​of multiple elements at multiple integer grids in the reference Cartesian coordinate system. In some embodiments, the transformation relationship between the element values ​​in the reference Cartesian coordinate system and the element values ​​in the polar coordinate system can be stored in the storage device of the medical system 100 (e.g., storage device 130).

[0136] Furthermore, the processing device 120 can determine the processed initial image based on multiple element values ​​of multiple elements at multiple integer grid locations in a polar coordinate system. For example, the processing device 120 can determine the processed initial image by combining multiple element values ​​of multiple elements at multiple integer grid locations in a polar coordinate system.

[0137] According to some embodiments of this application, for each of the multiple projection angles of a medical device, the processing device 120 can transform an image (e.g., an initial image) from a Cartesian coordinate system (e.g., the initial Cartesian coordinate system) corresponding to the projection angle (e.g., the initial projection angle) to a reference Cartesian coordinate system corresponding to a reference projection angle. Therefore, for each of the multiple projection angles of the medical device, the interpolation operation in step 720 and the coordinate transformation operation in step 720 can be performed on the image in both the polar coordinate system and the reference Cartesian coordinate system. This can improve the calculation speed of the coordinate transformation operation and the interpolation operation, thereby improving the efficiency of image reconstruction.

[0138] In some embodiments, the reference coordinate system may be omitted.

[0139] In some embodiments, the processing device 120 can determine the processed initial image by directly transforming the initial image from the initial coordinate system to the target coordinate system.

[0140] In some embodiments, the processing device 120 can obtain multiple element values ​​of multiple elements at multiple grids in a target coordinate system based on multiple element values ​​of multiple elements at multiple grids in an initial coordinate system. In some embodiments, the transformation relationship between the element values ​​of elements in the initial coordinate system and the element values ​​in the target coordinate system can be determined by the transformation relationship, and different projection angles can correspond to different transformation coefficients. In some embodiments, the transformation relationship between the element values ​​of elements in the initial coordinate system and the element values ​​of elements in the target coordinate system can be stored in the storage device of the medical system 100 (e.g., storage device 130).

[0141] In some embodiments, the processing device 120 may determine the processed initial image based on multiple element values ​​of multiple elements at multiple grid locations in the target coordinate system. For example, the processing device 120 may determine the processed initial image by combining multiple element values ​​of multiple elements at multiple grid locations in the target coordinate system.

[0142] In some embodiments, the processing device 120 can also transform multiple element values ​​of multiple elements in the initial coordinate system into multiple element values ​​in the target coordinate system based on coordinate mapping relationships, fitting algorithms, interpolation operations, etc., to determine the processed initial image.

[0143] In some embodiments, the processing device 120 may determine the processed initial image based on multiple element values ​​of multiple elements in the target coordinate system. For example, the processing device 120 may determine the processed initial image by combining multiple element values ​​of multiple elements in the target coordinate system.

[0144] It should be noted that the above description is for illustrative purposes only and is not intended to limit the scope of this application. Various changes and modifications can be made by those skilled in the art based on the teachings of this application. However, these changes and modifications do not depart from the scope of this application. In some embodiments, step 710 may be omitted. For example, the processing device 120 may generate a Cartesian coordinate system corresponding to each of a plurality of projection angles of the medical device. For each projection angle, the processing device 120 may determine the transformation relationship between the element coordinates in the Cartesian coordinate system corresponding to the projection angle and the element coordinates in the polar coordinate system.

[0145] Figure 8 This is a flowchart illustrating an exemplary process for determining a second differential image according to some embodiments of this application. In some embodiments, process 800 may be executed by medical system 100. For example, process 800 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., storage device 130, storage device 220, and / or memory 390). In some embodiments, processing device 120 (e.g., processor 210 of computing device 200, CPU 340 of mobile device 300, and / or...) Figure 4 One or more modules shown can execute this set of instructions and can be instructed to execute process 800 accordingly. The operation of the process shown below is intended to illustrate the problem. In some embodiments, process 800 can be implemented by one or more additional operations not described and / or one or more operations not discussed. Furthermore, Figure 8 The order of operations of process 800 shown and described below is not intended to be limiting. In some embodiments, one or more operations of process 800 may be performed to achieve, as in combination Figure 6 At least a portion of step 650.

[0146] In step 810, the processing device 120 (e.g., the determination module 430) can determine the third difference image by transforming the first difference image from the target coordinate system to the reference coordinate system.

[0147] For illustrative purposes only and without limiting the scope of this application, the following description uses the Cartesian coordinate system as the initial coordinate system and the polar coordinate system as the target coordinate system as an example.

[0148] In some embodiments, for each integer grid in a plurality of integer grids in a reference Cartesian coordinate system, the processing device 120 may determine a plurality of corresponding non-integer grids in the reference Cartesian coordinate system. The plurality of corresponding non-integer grids in the reference Cartesian coordinate system may correspond to a plurality of integer grids in a polar coordinate system. In some embodiments, the distance between each of the integer grids and each of the plurality of corresponding non-integer grids may be less than a distance threshold.

[0149] As an example only, for an integer grid in the reference Cartesian coordinate system, the processing device 120 can determine the eight corresponding non-integer grids in the reference Cartesian coordinate system according to equations (15)-(22): (15) (16) (17) (18) (19) (20) (twenty one), (twenty two), in, Represents an integer grid in the reference Cartesian coordinate system; , , , , , , and This refers to multiple corresponding non-integer grids in the referenced Cartesian coordinate system; ,and In the reference Cartesian coordinate system, referring to the integer grid With multiple corresponding non-integer grids and The distance between each of them.

[0150] Processing device 120 can determine multiple element values ​​of multiple elements at multiple corresponding non-integer grids in a reference Cartesian coordinate system based on multiple element values ​​of multiple elements at multiple integer grids in a polar coordinate system. For example, processing device 120 can determine multiple element values ​​of multiple elements at multiple integer grids in a polar coordinate system based on equations (23)-(25). The element coordinates at a given location determine the corresponding non-integer grid in the reference Cartesian coordinate system. The coordinates of the element at: (twenty three), (twenty four), (25) in, This refers to the distance between the focal point of the X-ray tube in the medical device and the rotation center of the medical device's frame; Represents the coordinates of an element at an integer grid position in polar coordinates; This refers to the coordinates of an element at the corresponding non-integer grid position in the reference Cartesian coordinate system. Therefore, the element value at a non-integer grid position in the reference Cartesian coordinate system can be the same as the element value at an integer grid position in the polar coordinate system.

[0151] Processing device 102 can determine the element values ​​of integer grids in the reference Cartesian coordinate system by performing interpolation operations on multiple element values ​​of multiple elements at multiple corresponding non-integer grids in the reference Cartesian coordinate system. For example, processing device 102 can determine the element values ​​of integer grids in the reference Cartesian coordinate system according to equation (26): (26) Where n refers to the number (or count) of the corresponding non-integer grids in the reference Cartesian coordinate system (e.g., 8), and m is less than n.

[0152] Furthermore, the processing device 120 can determine the third difference image based on multiple element values ​​of multiple elements at multiple integer grids in a reference Cartesian coordinate system. For example, the processing device 120 can determine the third difference image by combining multiple element values ​​of multiple elements at multiple integer grids in a reference Cartesian coordinate system.

[0153] In step 820, the processing device 120 (e.g., the determination module 430) can determine the second difference image by transforming the third difference image from the reference coordinate system to the initial coordinate system.

[0154] For illustrative purposes only and without limiting the scope of this application, the following description uses the Cartesian coordinate system as the initial coordinate system and the polar coordinate system as the target coordinate system as an example.

[0155] In some embodiments, the processing device 120 can obtain multiple element values ​​of multiple elements at multiple grids (e.g., integer grids) in an initial Cartesian coordinate system by performing interpolation operations on multiple element values ​​of multiple elements at multiple grids (e.g., integer grids) in a reference Cartesian coordinate system. For example, the processing device 120 can obtain multiple element values ​​of multiple elements at multiple non-integer grids in a reference Cartesian coordinate system by performing interpolation operations on multiple element values ​​of multiple elements at multiple integer grids in a reference Cartesian coordinate system. The multiple non-integer grids in the reference Cartesian coordinate system may correspond to multiple integer grids in the initial coordinate system. The processing device 120 can obtain multiple element values ​​of multiple elements at multiple integer grids in the initial Cartesian coordinate system based on the multiple element values ​​of multiple elements at multiple non-integer grids in the reference Cartesian coordinate system.

[0156] Furthermore, the processing device 120 can determine the second difference image based on multiple element values ​​of multiple elements at multiple grids (e.g., integer grids) in the initial Cartesian coordinate system. For example, the processing device 120 can determine the second difference image by combining multiple element values ​​of multiple elements at multiple integer grids in the initial Cartesian coordinate system.

[0157] It should be noted that the above description is for illustrative purposes only and is not intended to limit the scope of this application. Various changes and modifications can be made by those skilled in the art based on the teachings of this application. However, these changes and modifications do not depart from the scope of this application.

[0158] Having described the basic concepts, it will be clear to those skilled in the art upon reading this detailed disclosure that the above detailed disclosure is merely illustrative and not limiting. Various changes, modifications, and alterations can be made, and such changes, modifications, and alterations are intended for those skilled in the art, although not expressly stated herein. These changes, modifications, and alterations are intended to be made by this application and are within the spirit and scope of the exemplary embodiments of this application.

[0159] Furthermore, certain terms have been used to describe embodiments of this application. For example, the terms "one embodiment," "embodiment," and / or "some embodiments" mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in at least one embodiment of this application. Therefore, it should be emphasized and understood that references to "one embodiment" or "an alternative embodiment" two or more times in various parts of this application do not necessarily refer to the same embodiment. Moreover, specific features, structures, or characteristics may be appropriately combined in one or more embodiments of this application.

[0160] Furthermore, those skilled in the art will understand that certain aspects of this application can be illustrated and described in any of a variety of patentable classes or backgrounds, including any new and useful methods, machines, manufactures, or compositions of matter, or any new and useful improvements thereof. Therefore, certain aspects of this application can be implemented entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or in a combination of software and hardware, and are generally referred to herein as “modules,” “units,” “components,” “devices,” or “systems.” Additionally, certain aspects of this application can take the form of a computer program product contained in one or more computer-readable media, which contains computer-readable program code.

[0161] Computer-readable signal media may include propagating data signals containing computer-readable program code, for example, in baseband or as part of a carrier wave. Such propagating signals may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination thereof. A computer-readable signal medium may be a computer-readable medium other than any non-computer-readable storage medium and may communicate, propagate, or transmit programs for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on a computer-readable signal medium may be transmitted using any suitable medium, including wireless, wired, fiber optic cable, RF, etc., or any suitable combination thereof.

[0162] The computer program code used to perform the operations of various aspects of this application may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, and similar languages; traditional procedural programming languages ​​such as the "C" programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP; dynamic programming languages ​​such as Python, Ruby, and Groovy; or other programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet through an Internet service provider) or in a cloud computing environment, or provided as a service such as Software as a Service (SaaS).

[0163] Furthermore, the order or sequence of the listed processing elements, or the numbers, letters, or other names used, are not intended to limit the claimed processes and methods to any order, unless otherwise specified in the claims. Although the foregoing disclosure has discussed various useful embodiments now considered to be of this application by way of various examples, it should be understood that these details are for this purpose only, and the appended claims are not limited to the disclosed embodiments, but are instead intended to cover modifications and equivalent arrangements within the spirit and scope of the disclosed embodiments. For example, while the implementation of the various components described above can be implemented in a hardware device, it can also be implemented in software only, such as installed on an existing server or mobile device.

[0164] Similarly, it should be understood that in the above description of the embodiments of this application, various features are sometimes combined in one embodiment, figure, or related description in order to simplify the application and facilitate understanding of one or more embodiments. However, this manner of description should not be construed as indicating that the claimed subject matter requires more features than expressly recited in each claim. Rather, the subject matter of the claims lies in some, not all, of the features in the single embodiments described above.

Claims

1. A method for image reconstruction, implemented on a computing device including at least one processor and at least one storage device, comprising: Acquire raw biodata collected by medical devices; Get the initial image; as well as According to the image reconstruction algorithm, a target image is generated based on the original raw data and the initial image, including: A processed initial image is determined by transforming the initial image from an initial coordinate system to a target coordinate system, wherein multiple element values ​​in the processed initial image are represented by multiple grids in the target coordinate system, which is determined based on the structure of the detector of the medical device; and The target image is generated based on the processed initial image.

2. The method according to claim 1, characterized in that, Generating the target image based on the processed initial image includes: The first difference image is determined based on the processed initial image; A second difference image is determined by transforming the first difference image from the target coordinate system to the initial coordinate system, wherein multiple element values ​​in the second difference image are represented by multiple grids in the initial coordinate system; and The target image is generated based on the second difference image.

3. The method according to claim 2, characterized in that, Determining the first difference image based on the processed initial image includes: First projection data is determined by performing a forward projection operation on the processed initial image; Based on the first projection data and the original raw data, determine the second projection data; and The first difference image is determined by performing a backprojection operation on the second projection data.

4. The method according to claim 1, characterized in that, The raw data corresponds to multiple initial projection angles. The process of transforming the initial image from the initial coordinate system to the target coordinate system to determine the processed initial image includes: The second-processed initial image is determined by transforming the initial image from the initial coordinate system to the reference coordinate system, wherein the reference coordinate system corresponds to a reference projection angle; and The processed initial image is determined by transforming the second processed initial image from the reference coordinate system to the target coordinate system.

5. The method according to claim 2, characterized in that, The step of determining the second difference image by transforming the first difference image from the target coordinate system to the initial coordinate system includes: A third difference image is determined by transforming the first difference image from the target coordinate system to the reference coordinate system; and The second difference image is determined by transforming the third difference image from the reference coordinate system to the initial coordinate system.

6. The method according to claim 5, characterized in that, The origin of the reference coordinate system is located at the rotation center of the frame of the medical device, and the first axis of the reference coordinate system is the same as the first axis of the target coordinate system.

7. The method according to claim 1, characterized in that, The target coordinate system includes at least a polar coordinate system.

8. The method according to claim 1, characterized in that: The detector of the medical device includes multiple detector units, which include at least one row of detector units arranged along a first direction and at least one column of detector units arranged along a second direction. The origin of the target coordinate system is located at the focal point of the X-ray tube of the medical device. The first axis of the target coordinate system extends along the line connecting the origin and one of the multiple detector units. The second axis of the target coordinate system is the angular direction between the line connecting the origin and one of the detector units in the at least one row of detector units and the first axis. The third axis of the target coordinate system is the angular direction between the line connecting one of the plurality of detector units and the origin and the plane formed by the first axis and the second axis.

9. The method according to claim 8, characterized in that, In the target coordinate system, the size of each of the plurality of grids is related to the size of each of the plurality of detector elements.

10. The method according to claim 9, characterized in that: The width of each of the plurality of grids along the second axis direction of the target coordinate system is related to the width of the corresponding detector element along the first direction, and The height of each of the multiple grids along the third axis of the target coordinate system is related to the height of the corresponding detector unit along the second direction.

11. The method according to claim 10, characterized in that, The length of each of the plurality of grids along the first axis of the target coordinate system is substantially the same as the width of each of the plurality of grids along the second axis of the target coordinate system.

12. The method according to claim 10, characterized in that, The farther the mesh is from the origin of the target coordinate system along the first axis, the smaller the angle between the two sides of the mesh along the second axis, or the smaller the angle between the two sides of the mesh along the third axis.

13. The method according to claim 10, characterized in that, The width of the detector unit along the first direction is an integer multiple of the width of the corresponding grid along the second axis direction of the target coordinate system, or the height of the detector unit along the second direction is an integer multiple of the height of the corresponding grid along the third axis direction of the target coordinate system.

14. The method according to claim 9, characterized in that, The projected edges of the multiple grids on the detector plane coincide with or are parallel to the edges of the detector.

15. The method according to claim 4, characterized in that, The step of transforming the initial image from the initial coordinate system to the reference coordinate system to determine the second-processed initial image includes: By performing interpolation operations on multiple element values ​​of multiple elements at multiple grids in the initial coordinate system, multiple element values ​​of multiple elements at multiple grids in the reference coordinate system are obtained; and The initial image after the second processing is determined based on the element values ​​of the multiple elements at the multiple grids in the reference coordinate system.

16. The method according to claim 4, characterized in that, The step of determining the processed initial image by transforming the second processed initial image from the reference coordinate system to the target coordinate system includes: By performing interpolation operations on multiple element values ​​of multiple elements at multiple integer grids in the reference coordinate system, multiple element values ​​of multiple elements at multiple non-integer grids in the reference coordinate system are obtained, wherein the multiple non-integer grids in the reference reference system correspond to multiple integer grids in the target coordinate system. Based on the element values ​​of the plurality of elements at the plurality of non-integer grids in the reference coordinate system, obtain the plurality of meta-values ​​of the plurality of elements at the plurality of integer grids in the target coordinate system; and The processed initial image is determined based on the element values ​​of the plurality of elements at the plurality of integer grids in the target coordinate system.

17. The method according to claim 5, characterized in that, The step of determining the third difference image by transforming the first difference image from the target coordinate system to the reference coordinate system includes: For each integer grid in the plurality of integer grids in the reference coordinate system Determine a plurality of corresponding non-integer grids in the reference coordinate system, wherein the plurality of corresponding non-integer grids in the reference coordinate system correspond to a plurality of integer grids in the target coordinate system; Based on the element values ​​of multiple elements at multiple integer grid locations in the target coordinate system, determine the element values ​​of multiple elements at multiple corresponding non-integer grid locations in the reference coordinate system; and The element values ​​of the integer grid in the reference coordinate system are determined by performing interpolation operations on the element values ​​of the plurality of elements at the plurality of corresponding non-integer grids in the reference coordinate system; and The third difference image is determined based on the element values ​​of multiple elements at multiple integer grids in the reference coordinate system.

18. The method according to claim 5, characterized in that, The step of determining the second difference image by transforming the third difference image from the reference coordinate system to the initial coordinate system includes: By performing interpolation operations on multiple element values ​​at multiple grid locations in the reference coordinate system, multiple element values ​​at multiple grid locations in the initial coordinate system are obtained; and The second difference image is determined based on the element values ​​of the plurality of elements at the plurality of grids in the initial coordinate system.

19. The method according to claim 1, characterized in that, The image reconstruction algorithm includes an iterative reconstruction algorithm.

20. A system for image reconstruction, comprising: At least one storage device, including a set of instructions; as well as At least one processor is configured to communicate with the at least one storage device, wherein, when executing the instruction set, the at least one processor is configured to instruct the system to perform operations including: Acquire raw biodata collected by medical devices; Obtain the initial image; and According to the image reconstruction algorithm, a target image is generated based on the original raw data and the initial image, including: A processed initial image is determined by transforming the initial image from an initial coordinate system to a target coordinate system, wherein multiple element values ​​in the processed initial image are represented by multiple grids in the target coordinate system, which is determined based on the structure of the detector of the medical device; and The target image is generated based on the processed initial image.

21. The system according to claim 20, characterized in that, Generating the target image based on the processed initial image includes: The first difference image is determined based on the processed initial image; A second difference image is determined by transforming the first difference image from the target coordinate system to the initial coordinate system, wherein multiple element values ​​in the second difference image are represented by multiple grids in the initial coordinate system; and The target image is generated based on the second difference image.

22. The method according to claim 21, characterized in that, The method of determining the first difference image based on the processed initial image includes: First projection data is determined by performing a forward projection operation on the processed initial image; Based on the first projection data and the original raw data, determine the second projection data; and The first difference image is determined by performing a backprojection operation on the second projection data.

23. The system according to claim 20, characterized in that, The raw data corresponds to multiple initial projection angles. The process of transforming the initial image from the initial coordinate system to the target coordinate system to determine the processed initial image includes: The second-processed initial image is determined by transforming the initial image from the initial coordinate system to the reference coordinate system, wherein the reference coordinate system corresponds to a reference projection angle; and The processed initial image is determined by transforming the second processed initial image from the reference coordinate system to the target coordinate system.

24. The system according to claim 21, characterized in that, The step of determining the second difference image by transforming the first difference image from the target coordinate system to the initial coordinate system includes: A third difference image is determined by transforming the first difference image from the target coordinate system to the reference coordinate system; and The second difference image is determined by transforming the third difference image from the reference coordinate system to the initial coordinate system.

25. The system according to claim 24, characterized in that, The origin of the reference coordinate system is located at the rotation center of the frame of the medical device, and the first axis of the reference coordinate system is the same as the first axis of the target coordinate system.

26. The system according to claim 20, characterized in that, The target coordinate system includes at least a polar coordinate system.

27. The system according to claim 20, characterized in that: The detector of the medical device includes multiple detector units, which include at least one row of detector units arranged along a first direction and at least one column of detector units arranged along a second direction. The origin of the target coordinate system is located at the focal point of the X-ray tube of the medical device. The first axis of the target coordinate system extends along the line connecting the origin and one of the multiple detector units. The second axis of the target coordinate system is the angular direction between the line connecting the origin and one of the detector units in the at least one row of detector units and the first axis. The third axis of the target coordinate system is the angular direction between the line connecting one of the plurality of detector units and the origin and the plane formed by the first axis and the second axis.

28. The system according to claim 27, characterized in that, In the target coordinate system, the size of each of the plurality of grids is related to the size of each of the plurality of detector elements.

29. The system according to claim 28, characterized in that: The width of each of the plurality of grids along the second axis direction of the target coordinate system is related to the width of the corresponding detector element along the first direction, and The height of each of the multiple grids along the third axis of the target coordinate system is related to the height of the corresponding detector unit along the second direction.

30. The system according to claim 29, characterized in that, The length of each of the plurality of grids along the first axis of the target coordinate system is approximately the same as the width of each of the plurality of grids along the second axis of the target coordinate system.

31. The system according to claim 29, characterized in that, The farther the mesh is from the origin of the target coordinate system along the first axis, the smaller the angle between the two sides of the mesh along the second axis, or the smaller the angle between the two sides of the mesh along the third axis.

32. The system according to claim 29, characterized in that, The width of the detector unit along the first direction is an integer multiple of the width of the corresponding grid along the second axis direction of the target coordinate system, or the height of the detector unit along the second direction is an integer multiple of the height of the corresponding grid along the third axis direction of the target coordinate system.

33. The system according to claim 28, characterized in that, The projected edges of the multiple grids on the detector plane coincide with or are parallel to the edges of the detector.

34. The system according to claim 23, characterized in that, The step of transforming the initial image from the initial coordinate system to the reference coordinate system to determine the second-processed initial image includes: By performing interpolation operations on multiple element values ​​of multiple elements at multiple grids in the initial coordinate system, multiple element values ​​of multiple elements at multiple grids in the reference coordinate system are obtained; and The initial image after the second processing is determined based on the element values ​​of the multiple elements at the multiple grids in the reference coordinate system.

35. The system according to claim 23, characterized in that, The step of determining the processed initial image by transforming the second processed initial image from the reference coordinate system to the target coordinate system includes: By performing interpolation operations on multiple element values ​​of multiple elements at multiple integer grids in the reference coordinate system, multiple element values ​​of multiple elements at multiple non-integer grids in the reference coordinate system are obtained, wherein the multiple non-integer grids in the reference reference system correspond to multiple integer grids in the target coordinate system. Based on the element values ​​of the plurality of elements at the plurality of non-integer grids in the reference coordinate system, obtain the plurality of meta-values ​​of the plurality of elements at the plurality of integer grids in the target coordinate system; and The processed initial image is determined based on the element values ​​of the plurality of elements at the plurality of integer grids in the target coordinate system.

36. The system according to claim 24, characterized in that, The step of determining the third difference image by transforming the first difference image from the target coordinate system to the reference coordinate system includes: For each integer grid in the plurality of integer grids in the reference coordinate system Determine a plurality of corresponding non-integer grids in the reference coordinate system, wherein the plurality of corresponding non-integer grids in the reference coordinate system correspond to a plurality of integer grids in the target coordinate system; Based on the element values ​​of multiple elements at multiple integer grid locations in the target coordinate system, determine the element values ​​of multiple elements at multiple corresponding non-integer grid locations in the reference coordinate system; and The element values ​​of the integer grid in the reference coordinate system are determined by performing interpolation operations on the element values ​​of the plurality of elements at the plurality of corresponding non-integer grids in the reference coordinate system; and The third difference image is determined based on the element values ​​of multiple elements at multiple integer grids in the reference coordinate system.

37. The system according to claim 24, characterized in that, The step of determining the second difference image by transforming the third difference image from the reference coordinate system to the initial coordinate system includes: By performing interpolation operations on multiple element values ​​at multiple grid locations in the reference coordinate system, multiple element values ​​at multiple grid locations in the initial coordinate system are obtained; and The second difference image is determined based on the element values ​​of the plurality of elements at the plurality of grids in the initial coordinate system.

38. The system according to claim 20, characterized in that, The image reconstruction algorithm includes an iterative reconstruction algorithm.

39. A non-transitory computer-readable medium comprising a set of instructions for image reconstruction, characterized in that, When executed by at least one processor, the instructions instruct the at least one processor to implement a method comprising: Acquire raw biodata collected by medical devices; Obtain the initial image; and According to the image reconstruction algorithm, a target image is generated based on the original raw data and the initial image, including: A processed initial image is determined by transforming the initial image from an initial coordinate system to a target coordinate system, wherein multiple element values ​​in the processed initial image are represented by multiple grids in the target coordinate system, which is determined based on the structure of the detector of the medical device; and The target image is generated based on the processed initial image.

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