WO2021190276A1

WO2021190276A1 - Systems and methods for projection data simulation

Info

Publication number: WO2021190276A1
Application number: PCT/CN2021/079302
Authority: WO
Inventors: Kai CUI; Yan'ge MA; Na Zhang; Jie NIU; Juan FENG
Original assignee: Shanghai United Imaging Healthcare Co., Ltd.
Priority date: 2020-03-27
Filing date: 2021-03-05
Publication date: 2021-09-30
Also published as: CN111462267A

Abstract

Systems and methods for simulating projection data relating to an imaging device are disclosed. The system may obtain a simulation model(700) including a simulated source(710), a simulated detector(730), and a digital phantom(750) including a plurality of elements. The system may determine a plurality of initial energy levels based on an energy spectrum corresponding to the radiation source. The system may also determine a plurality of ray paths based on the simulated source and the simulated detector. For each of the plurality of ray paths, the system may further determine, based on the plurality of initial energy levels, a plurality of attenuated energy levels that traverse at least a portion of the plurality of elements and determine, based on the plurality of attenuated energy levels and the plurality of initial energy levels, one of the simulated projection values of the projection data.

Description

SYSTEMS AND METHODS FOR PROJECTION DATA SIMULATION

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority of Chinese Patent Application No. 202010229949.4, filed on March 27, 2020, the contents of which are hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure relates to the field of medical imaging technology, and in particular, to systems and methods for projection data simulation.

BACKGROUND

A medical imaging device, such as a computed tomography (CT) device, a digital radiography (DR) device, or a digital subtraction angiography (DSA) device, is widely used to obtain projection data of an object (e.g., a patient or a portion thereof) using an X-ray beam. The projection data of the patient may be reconstructed to generate an image of the object, e.g., for diagnosis, treatment, and/or research purposes.

SUMMARY

In an aspect of the present disclosure, a method for simulating projection data relating to an imaging device is provided in the present disclosure. The imaging device may include a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object. The method may be implemented on a computing device including at least one processor and at least one storage device. The method may include obtaining a simulation model relating to the imaging device. The simulation model may include a simulated source for simulating the radiation source, a simulated detector for simulating the detector, and a digital phantom including a plurality of elements for simulating the object. The method may determine, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding to the simulated source. The method may also determine, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom. The each ray path may correspond to one of simulated projection values of the projection data. The one of the simulated rays may include components of the plurality of initial energy levels. For each of the plurality of ray paths, the method may further determine, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverse at least a portion of the plurality of elements, wherein each of the plurality of attenuated energy levels corresponds to one of the plurality of initial energy levels and determine, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data that corresponds to the ray path.

In some embodiments 1, the obtaining a simulation model relating to the imaging device may include obtaining a position of the object relative to the imaging device; and determining the simulation model based on the position of the object relative to the imaging device.

In some embodiments, the determining, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding the simulated source may include obtaining a value of voltage peak corresponding to the radiation source; determining, based on the value of voltage peak, the energy spectrum corresponding to the radiation source; dividing the energy spectrum into a plurality of intervals each of which corresponds to one of the plurality of initial energy levels; and determining the plurality of initial energy levels based on the plurality of intervals.

In some embodiments, the simulated detector may include a plurality of simulated detection points. The determining, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom may include determining a line that passes through the simulated source and one of the plurality of simulated detection points; and designating a portion of the line that traverses the digital phantom as one of the plurality of ray paths.

In some embodiments, for each of the plurality of ray paths, the determining, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverses at least a portion of the plurality of elements may include determining one or more elements of the plurality of elements through which the ray path traverses; and for each of the plurality of initial energy levels, determining one or more attenuation coefficients each of which corresponds to one of the one or more elements for the initial energy level, and determining, based on the one or more attenuation coefficients, an attenuated energy level corresponding to the initial energy level as one of the plurality of attenuated energy levels that correspond to the ray path.

In some embodiments 5, the determining, based on the one or more attenuation coefficients, an attenuated energy level corresponding to the initial energy level as one of the plurality of attenuated energy levels that correspond to the ray path may include determining, based on the one or more attenuation coefficients, an amount of attenuation corresponding to the initial energy level and the ray path; and determining, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels that correspond to the ray path.

In some embodiments, the determining, based on the one or more attenuation coefficients, an amount of attenuation corresponding to the initial energy level and the ray path may include determining the amount of attenuation corresponding to the initial energy level and the ray path based on the one or more attenuation coefficients and the one or more elements.

In some embodiments, the determining, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels corresponding to the ray path may include determining, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels corresponding to the ray path.

In some embodiments, the determining, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data corresponding to the ray path may include determining an initial energy corresponding to the simulated projection value by summing the plurality of initial energy levels; determining an attenuated energy corresponding to the simulated projection value by summing the plurality of attenuated energy levels corresponding to the ray path; and determining, based on the attenuated energy corresponding to the ray path and the initial energy, the one of the simulated projection values of the projection data corresponding to the ray path.

In some embodiments, the method further include generating, based on the simulated projection values of the projection data, a simulated image relating to the object using a reconstruction algorithm.

In another aspect of the present disclosure, a system for simulating projection data relating to an imaging device is provided. The imaging device may include a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object. The system may also include a storage device storing a set of instructions and at least one processor in communication with the storage device. When executing the set of instructions, the at least one processor may be configured to cause the system to perform following operations. The operations may include obtaining a simulation model includes a simulated source for simulating the radiation source, a simulated detector for simulating the detector, and a digital phantom including a plurality of elements for simulating the object. The operations may include determining, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding to the simulated source. The operations may also include determining, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom. The each ray path may correspond to one of simulated projection values of the projection data. The one of the simulated rays may include components of the plurality of initial energy levels. The operations may further include, for each of the plurality of ray paths, determining, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverse at least a portion of the plurality of elements; and determining, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data that corresponds to the ray path. Each of the plurality of attenuated energy levels may correspond to one of the plurality of initial energy levels.

In another aspect of the present disclosure, a system for simulating projection data relating to an imaging device is provided. The imaging device may include a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object. The system may include an obtaining module, an initial energy level determination module, a ray path determination module, an attenuated energy level determination module, and a simulated projection value determination module. The obtaining module may be configured to obtain a simulation model relating to the imaging device. The simulation model may include a simulated source for simulating the radiation source, a simulated detector for simulating the detector, and a digital phantom including a plurality of elements for simulating the object. The initial energy level determination module may be configured to determine, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding to the simulated source. The ray path determination module may be configured to determine, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom. The each ray path may correspond to one of simulated projection values of the projection data. The one of the simulated rays may include components of the plurality of initial energy levels. The attenuated energy level determination module may be configured to for each of the plurality of ray paths, determining, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverse at least a portion of the plurality of elements. Each of the plurality of attenuated energy levels corresponds to one of the plurality of initial energy levels. The simulated projection value determination module may be configured to for each of the plurality of ray paths, determine, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data that corresponds to the ray path.

In another aspect of the present disclosure, a non-transitory computer readable medium is provided. The non-transitory computer readable medium may include executable instructions that, when executed by at least one processor, direct the at least one processor to perform a method for simulating projection data relating to an imaging device. The imaging device may include a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object. The method may include obtaining a simulation model relating to the imaging device. The simulation model may include a simulated source for simulating the radiation source, a simulated detector for simulating the detector, and a digital phantom including a plurality of elements for simulating the object. The method may determine, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding to the simulated source. The method may also determine, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom. The each ray path may correspond to one of simulated projection values of the projection data. The one of the simulated rays may include components of the plurality of initial energy levels. For each of the plurality of ray paths, the method may further determine, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverse at least a portion of the plurality of elements, wherein each of the plurality of attenuated energy levels corresponds to one of the plurality of initial energy levels and determine, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data that corresponds to the ray path.

Additional features will be set forth in part in the description which follows, and in part will become apparent 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 the present disclosure may be realized and attained by practice or use of various aspects of the methodologies, instrumentalities, and combinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in detail of exemplary embodiments. These exemplary embodiments are described in detail with reference to the drawings. These embodiments are not limiting, and in these embodiments, the same number indicates the same structure, wherein:

FIG. 1 is a schematic diagram illustrating an exemplary simulation system according to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary computing device according to some embodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary mobile device according to some embodiments of the present disclosure;

FIG. 4 is a block diagram illustrating an exemplary processing device according to some embodiments of the present disclosure;

FIG. 5 is a flowchart illustrating an exemplary process for simulating projection data relating to an imaging device according to some embodiments of the present disclosure;

FIG. 6 is a schematic diagram illustrating an exemplary energy spectrum according to some embodiments of the present disclosure;

FIG. 7 is a schematic diagram illustrating an exemplary ray path in a simulated model according to some embodiments in the present disclosure;

FIG. 8 is a flowchart illustrating an exemplary process for determining a plurality of initial energy levels according to some embodiments of the present disclosure;

FIG. 9 is a schematic diagram illustrating an exemplary division of an energy spectrum according to some embodiments of the present disclosure;

FIG. 10 is a schematic diagram illustrating exemplary spatial distributions of attenuation coefficients corresponding to a digital phantom according to some embodiments of the present disclosure; and

FIG. 11 is a flowchart illustrating an exemplary process for determining an amount of attenuation corresponding to an initial energy level and a ray path according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are set forth by way of examples in order to provide a thorough understanding of the relevant disclosure. However, it should be apparent to those skilled in the art that the present disclosure may be practiced without such details. In other instances, well-known methods, procedures, systems, components, and/or circuitry have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring aspects of the present disclosure. Various modifications to the disclosed embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the present disclosure. Thus, the present disclosure is not limited to the embodiments shown, but to be accorded the widest scope consistent with the claims.

The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used herein, the singular forms “a, ” “an, ” and “the” may be intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprise, ” “comprises, ” and/or “comprising, ” “include, ” “includes, ” and/or “including, ” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It will be understood that the term “system, ” “engine, ” “unit, ” “module, ” and/or “block” used herein are one method to distinguish different components, elements, parts, sections or assembly of different levels in ascending order. However, the terms may be displaced by another expression if they achieve the same purpose.

Generally, the word “module, ” “unit, ” or “block, ” as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions. A module, a unit, or a block described herein may be implemented as software and/or hardware and may be stored in any type of non-transitory computer-readable medium or another storage device. In some embodiments, a software module/unit/block may be compiled and linked into an executable program. It will be appreciated that software modules can be callable from other modules/units/blocks or from themselves, and/or may be invoked in response to detected events or interrupts. Software modules/units/blocks configured for execution on computing devices (e.g., processor 210 as illustrated in FIG. 2) may be provided on a computer-readable medium, such as a compact disc, a digital video disc, a flash drive, a magnetic disc, or any other tangible medium, or as a digital download (and can be originally stored in a compressed or installable format that needs installation, decompression, or decryption prior to execution) . Such software code may be stored, partially or fully, on a storage device of the executing computing device, for execution by the computing device. Software instructions may be embedded in firmware, such as an EPROM. It will be further appreciated that hardware modules/units/blocks may be included in connected logic components, such as gates and flip-flops, and/or can be included of programmable units, such as programmable gate arrays or processors. The modules/units/blocks or computing device functionality described herein may be implemented as software modules/units/blocks but may be represented in hardware or firmware. In general, the modules/units/blocks described herein refer to logical modules/units/blocks that may be combined with other modules/units/blocks or divided into sub-modules/sub-units/sub-blocks despite their physical organization or storage. The description may be applicable to a system, an engine, or a portion thereof.

It will be understood that when a unit, engine, module or block is referred to as being “on, ” “connected to, ” or “coupled to, ” another unit, engine, module, or block, it may be directly on, connected or coupled to, or communicate with the other unit, engine, module, or block, or an intervening unit, engine, module, or block may be present unless the contextclearlyindicatesotherwise. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.

These and other features, and characteristics of the present disclosure, as well as the methods of operation and functions of the related elements of structure and the combination of parts and economies of manufacture, may become more apparent upon consideration of the following description with reference to the accompanying drawings, all of which form a part of this disclosure. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended to limit the scope of the present disclosure. It is understood that the drawings are not to scale.

The term “modality” as used herein broadly refers to an imaging or treatment method or technology that gathers, generates, processes, and/or analyzes imaging information of a subject or treatments the subject. The subject may include a biological object and/or a non-biological object. The biological subject may be a human being, an animal, a plant, or a portion thereof (e.g., a cell, a tissue, an organ, etc. ) . In some embodiments, the subject may be a man-made composition of organic and/or inorganic matters that are with or without life. The term “object” or “subject” are used interchangeably in the present disclosure.

The term “image” in the present disclosure is used to collectively refer to image data (e.g., scan data, projection data) and/or images of various forms, including a two-dimensional (2D) image, a three-dimensional (3D) image, a four-dimensional (4D) , etc. The term “pixel” and “voxel” in the present disclosure are used interchangeably to refer to an element of an image. The term “region, ” “location, ” and "area" in the present disclosure may refer to a location of an anatomical structure shown in the image or an actual location of the anatomical structure existing in or on a target subject's body, since the image may indicate the actual location of a certain anatomical structure existing in or on the target subject's body. In some embodiments, an image of an object may be referred to as the object for brevity. Segmentation of an image of an object may be referred to as segmentation of the object. For example, segmentation of an organ refers to segmentation of a region corresponding to the organ in an image.

As the medical imaging device with an X-ray source may emit a poly-energetic X-ray beam including photons within a wide distribution of an energy spectrum, a reconstructed image may have multiple artifacts (e.g., a hardening artifact, a scatter artifact, etc. ) . For instance, as lower-energy photons may be preferentially absorbed compared to higher-energy photons when an X-ray beam passes through an object, the X-ray beam may gradually become harder as its mean energy increases, which leads to beam-hardening phenomenon. An image that is reconstructed based on projection data acquired by the medical imaging device may have hardening artifacts due to the beam-hardening phenomenon. The reconstructed image may need to be processed by removing the beam-hardening (BH) artifacts using a BH artifact removal algorithm to generate an optimized image. For researching and/or optimizing the BH artifact removal algorithm, an effect of the BH artifact removal algorithm needs to be verified. In some embodiments, the reconstructed image may have other artifacts (e.g., scattering artifacts, metal artifacts, etc. ) besides the BH artifacts. It is difficult to verify the effect of the BH artifact removal algorithm by directly comparing the reconstructed image and the optimized image.

By simulating projection data, a simulated image may be reconstructed based on the simulated projection data. The simulated image may be processed using the BH artifact removal algorithm to generate a simulated optimized image. In such cases, the effect of the BH artifact removal algorithm may be verified based on the simulated image and the simulated reconstructed image, as the simulated image may have fewer other artifacts except for the HB artifact removal algorithm. In some embodiments, some institutions such as scientific research institutions and schools may have no medical imaging device to obtain a true reconstructed image. By simulating projection data acquired by the medical imaging device, the institutions may use simulated image reconstructed based on the simulated projection data for research purposes (e.g., researching the effect of the BH artifact removal algorithm) .

If a simulation algorithm is constructed by assuming that an X-ray beam traversing an object is mono-energetic, simulated projection data may differ from the projection data, and in turn a simulated image reconstructed based on the simulated projection data may differ from an image reconstructed based on the projection data resulting from the X-ray beam traversing the object. For instance, the simulated image may lack a hardening artifact corresponding to the hardening effect of the poly-energetic X-ray beam traversing the object.

Therefore, it is desirable to provide effective systems and methods for simulating projection data of a poly-energetic X-ray beam, which can improve the accuracy of simulating the projection data.

An aspect of the present disclosure relates to systems and methods for simulating projection data relating to an imaging device (e.g., the medical imaging device disclosed elsewhere in the present disclosure) . The imaging device may include a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object. The system may obtain a simulation model relating to the imaging device. The simulation model may include a simulated source for simulating the radiation source, a simulated detector for simulating the detector, and a digital phantom including a plurality of elements for simulating the object. The system may determine, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding to the simulated source. The system may also determine, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom. The each ray path may correspond to one of simulated projection values of the projection data. A simulated ray may include components corresponding to the plurality of initial energy levels. For each of the plurality of ray paths, the system may determine, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverses at least a portion of the plurality of elements. Each of the plurality of attenuated energy levels may correspond to one of the plurality of initial energy levels. Further, for each of the plurality of ray paths, the system may determine, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data corresponding to the ray path.

According to some embodiments of the present disclosure, for each of the plurality of energy levels, the digital phantom may correspond to a spatial distribution of attenuation coefficients corresponding to the energy level. A simulated projection value may be determined based on the plurality of distributions of attenuation coefficients corresponding to the plurality of energy levels such that the simulated projection values are close to or substantially consistent with actual projection values of the projection data acquired by the imaging device, thereby obtaining a simulated image reconstructed based on the simulated projection values close to or substantially consistent with an actual image reconstructed based on the actual projection values Further, the simulated image may be used to verify an effect of an artifact removal algorithm, thereby facilitating the development, calibration, verification, and/or improvement of an imaging technique including, e.g., an imaging device, an image reconstruction algorithm, etc.

FIG. 1 is a schematic diagram illustrating an exemplary simulation system according to some embodiments of the present disclosure. The simulation system 100 may be configured to simulate projection data and/or image relating to an imaging device. As used herein, the imaging device may be for non-invasive biomedical imaging/treatment, such as for disease diagnostic, disease therapy, or research purposes. In some embodiments, the imaging device may include a single modality device and/or a multi-modality device. The single modality device may include, for example, an X-ray imaging device, a computed tomography (CT) device, a digital radiography (DR) device, a digital subtraction angiography (DSA) device, or the like, or any combination thereof. The multi-modality device may include, for example, an X-ray and imaging-magnetic resonance imaging (X-ray-MRI) device, a positron emission tomography and X-ray imaging (PET-X-ray) device, a single photon emission computed tomography and X-ray imaging (SPECT-X-ray) device, a PET-CT device, an MRI-CT device, a DSA-MRI device, an image-guided radiotherapy (IGRT) device (e.g., a CT guided RT device, an X-ray guided RT device, etc. ) , etc. For illustration purposes, the present disclosure is described in connection with a CT device. The imaging device may be configured to perform a scan on an object. The object may be biological or non-biological. The biological object may be a human being, an animal, a plant, or a portion thereof (e.g., a cell, a tissue, an organ, etc. ) . The non-biological object may include a man-made object such as a body phantom or a water phantom. In some embodiments, the object may include a man-made composition of organic and/or inorganic matters that are with or without life. In some embodiments, the imaging device may include a scanner with a radiation source and a detector. The radiation source may be configured to emit radiation rays towards the object. The detector may be configured to detect at least a portion of the radiation rays that have traversed the object. It should be noted that the simulation system described below is merely provided for illustration purposes, and not intended to limit the scope of the present disclosure.

As illustrated, the simulation system 100 may include a processing device 110, a network 120, a terminal device 130, and a storage device 140. The components of the simulation system 100 may be connected in one or more of various ways. Merely by way of example, the processing device 110 may be connected to the storage device 140 through the network 120. As another example, the processing device 110 may be connected to the storage device 140 directly. As a further example, the terminal device 130 may be connected to the processing device 110 directly or through the network 120.

In some embodiments, the processing device 110 may process data and/or information obtained from the terminal device 130, the storage device 140, or other components of the simulation system 100. For example, the processing device 110 may simulate the imaging device by a simulated model. The simulated model may include a simulated source 111, a simulated detector 113, a digital phantom 112, etc. The simulated source 111 may be configured to simulate the radiation source of the imaging device. The simulated detector 113 may be configured to simulate the detector of the imaging device. The digital phantom 112 may be configured to simulate the object to be scanned and/or imaged by the imaging device. For example, the digital phantom 112 may simulate the anatomy of a patient to be imaged by setting a spatial distribution of a property, e.g., attenuation coefficients. The simulated source 111 and the simulated detector 113 may be arranged on opposite sides of the digital phantom 112 according to actual arrangements of the radiation source and the detector during a scan to be performed on the object. For example, relative positions between the simulated source 111, the simulated detector 113, and the digital phantom 112 may be the same as those between the radiation source, the detector, and the object. More descriptions regarding the simulated model may be found elsewhere in the present disclosure (e.g., FIG. 5 and the description thereof) .

As another example, the processing device 110 may determine a plurality of initial energy levels corresponding to the simulate source based on an energy spectrum corresponding to the radiation source. As still another example, the processing device 110 may determine a plurality of ray paths based on the simulated model. For each of the ray paths, the processing device 110 may determine a plurality of attenuated energy levels corresponding to the ray path. As further another example, for each of the ray path, the processing device 110 may determine one of simulated projection values of projection data acquired by the imaging device based on the initial energy levels and the attenuated energy levels corresponding to the ray path. In some embodiments, the processing device 110 may include a central processing unit (CPU) , a digital signal processor (DSP) , a system on a chip (SoC) , a microcontroller unit (MCU) , or the like, or any combination thereof. In some embodiments, the processing device 110 may include a computer, a user console, a single server or a server group, etc. The server group may be centralized or distributed. In some embodiments, the processing device 110 may be local or remote. For example, the processing device 110 may access information and/or data stored in the terminal device 130, and/or the storage device 140 via the network 120. As another example, the processing device 110 may be directly connected to the terminal device 130 and/or the storage device 140 to access stored information and/or data. In some embodiments, the processing device 110 may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof. In some embodiments, the processing device 110 or a portion of the processing device 110 may be integrated into the terminal device 130. In some embodiments, the processing device 110 may be implemented by a computing device 200 including one or more components as described in FIG. 2.

The network 120 may include any suitable network that can facilitate the exchange of information and/or data for the simulation system 100. In some embodiments, one or more components (e.g., the processing device 110, the storage device 140, the terminal device 130) of the simulation system 100 may communicate information and/or data with one or more other components of the simulation system 100 via the network 120. For example, the processing device 110 may obtain data from the storage device 140 via the network 120. As another example, the terminal device 130 may receive a simulated image from the processing device 110 via the network 120. In some embodiments, one or more components (e.g., the processing device 110, the storage device 140, the terminal device 130) of the simulation system 100 may communicate information and/or data with one or more external resources such as an external database of a third party, etc. For example, the processing device 110 may obtain a simulation model directly from an external database. The network 120 may be and/or include a public network (e.g., the Internet) , a private network (e.g., a local area network (LAN) , a wide area network (WAN) ) ) , a wired network (e.g., an Ethernet network) , a wireless network (e.g., an 802.11 network, a Wi-Fi network) , a cellular network (e.g., a Long Term Evolution (LTE) network) , a frame relay network, a virtual private network ( “VPN” ) , a satellite network, a telephone network, routers, hubs, switches, server computers, and/or any combination thereof. Merely by way of example, the network 120 may include a cable network, a wireline network, a fiber-optic network, a telecommunications network, an intranet, a wireless local area network (WLAN) , a metropolitan area network (MAN) , a public telephone switched network (PSTN) , a Bluetooth ^TM network, a ZigBee ^TM network, a near field communication (NFC) network, or the like, or any combination thereof. In some embodiments, the network 120 may include one or more network access points. For example, the network 120 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 the simulation system 100 may be connected to the network 120 to exchange data and/or information.

The terminal device 130 may include a mobile device 131, a tablet computer 132, a laptop computer 133, or the like, or any combination thereof. In some embodiments, the mobile device 131 may include a smart home device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home device may include a smart lighting device, a control device of an intelligent electrical apparatus, a smart monitoring device, a smart television, a smart video camera, an interphone, or the like, or any combination thereof. In some embodiments, the wearable device may include a bracelet, a footgear, eyeglasses, a helmet, a watch, clothing, a backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the smart mobile device may include a mobile phone, a personal digital assistant (PDA) , a gaming device, a navigation device, a point of sale (POS) device, a desktop, or the like, or any combination thereof. In some embodiments, the virtual reality device and/or the augmented reality device may include a virtual reality helmet, virtual reality glasses, a virtual reality patch, an augmented reality helmet, augmented reality glasses, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or the augmented reality device may include a Google Glass ^TM, an Oculus Rift ^TM, a Hololens ^TM, a Gear VR ^TM, etc. In some embodiments, the terminal device 130 may operate the processing device 110 remotely. For example, the terminal device 130 may operate the processing device 110 via a wireless connection. In some embodiments, the terminal device 130 may receive information and/or instructions input by a user, and send the received information and/or instructions to the processing device 110 or the storage device 140 via the network 120. In some embodiments, the terminal device 130 may receive data and/or information from the processing device 110. In some embodiments, the terminal device 130 may be part of the processing device 110.

The storage device 140 may store data, instructions, and/or any other information. In some embodiments, the storage device 140 may store data obtained from the processing device 110 and/or the terminal device 130. For example, the storage device 140 may store energy spectrums corresponding to X-rays emitted from different radiation sources, spaces distributions of attenuation coefficients in a digital phantom corresponding to different energy levels, geometric parameters of the digital phantom, coordinate data, simulated projection data, or the like, or any combination thereof. In some embodiments, the storage device 140 may store data and/or instructions that the processing device 110 may execute or use to perform exemplary methods/systems described in the present disclosure. In some embodiments, the storage device 140 may include a mass storage device, a removable storage device, a volatile read-and-write memory, a read-only memory (ROM) , or the like, or any combination thereof. Exemplary mass storage devices may include a magnetic disk, an optical disk, a solid-state drive, etc. Exemplary removable storage devices may include a flash drive, a floppy disk, an optical disk, a memory card, a zip disk, a magnetic tape, etc. Exemplary volatile read-and-write memories may include a random access memory (RAM) . Exemplary RAM may include a dynamic RAM (DRAM) , a double date rate synchronous dynamic RAM (DDR SDRAM) , a static RAM (SRAM) , a thyristor RAM (T-RAM) , and a zero-capacitor RAM (Z-RAM) , etc. Exemplary ROM may include a mask ROM (MROM) , a programmable ROM (PROM) , an erasable programmable ROM (EPROM) , an electrically erasable programmable ROM (EEPROM) , a compact disk ROM (CD-ROM) , and a digital versatile disk ROM, etc. In some embodiments, the storage device 140 may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof.

In some embodiments, the storage device 140 may be connected to the network 120 to communicate with one or more other components (e.g., the processing device 110, the terminal device 130) of the simulation system 100. One or more components of the simulation system 100 may access the data or instructions stored in the storage device 140 via the network 120. In some embodiments, the storage device 140 may be directly connected to or communicate with one or more other components (e.g., the processing device 110, the terminal device 130) of the simulation system 100. In some embodiments, the storage device 140 may be part of the processing device 110.

It should be noted that the above description of the simulation system 100 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. For example, the simulation system 100 may include one or more additional components and/or one or more components of the simulation system 100 described above may be omitted. Additionally or alternatively, two or more components of the simulation system 100 may be integrated into a single component. A component of the simulation system 100 may be implemented on two or more sub-components.

FIG. 2 is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary computing device according to some embodiments of the present disclosure. The computing device 200 may be used to implement any component of the simulation system 100 as described herein. For example, the processing device 110 and/or the terminal device 130 may be implemented on the computing device 200, respectively, via its hardware, software program, firmware, or a combination thereof. Although only one such computing device is shown for convenience, the computer functions relating to the simulation system 100 as described herein may be implemented in a distributed fashion on a number of similar platforms, to distribute the processing load. As illustrated in FIG. 2, the computing device 200 may include a processor 210, a storage 220, an input/output (I/O) 230, and a communication port 240.

The processor 210 may execute computer instructions (e.g., program codes) and perform functions of the processing device 110 in accordance with techniques described herein. The computer instructions may include, for example, routines, programs, objects, components, signals, data structures, procedures, modules, and functions, which perform particular functions described herein. In some embodiments, the processor 210 may perform instructions obtained from the terminal device 130 and/or the storage device 140. In some embodiments, the processor 210 may include one or more hardware processors, such as a microcontroller, a microprocessor, a reduced instruction set computer (RISC) , an application-specific integrated circuits (ASICs) , an application-specific instruction-set processor (ASIP) , a central processing unit (CPU) , a graphics processing unit (GPU) , a physics processing unit (PPU) , a microcontroller unit, a digital signal processor (DSP) , a field-programmable gate array (FPGA) , an advanced RISC machine (ARM) , a programmable logic device (PLD) , any circuit or processor capable of executing one or more functions, or the like, or any combinations thereof.

Merely for illustration, only one processor is described in the computing device 200. However, it should be noted that the computing device 200 in the present disclosure may also include multiple processors. Thus operations and/or method steps that are performed by one processor as described in the present disclosure may also be jointly or separately performed by the multiple processors. For example, if in the present disclosure the processor of the computing device 200 executes both operation A and operation B, it should be understood that operation A and operation B may also be performed by two or more different processors jointly or separately in the computing device 200 (e.g., a first processor executes operation A and a second processor executes operation B, or the first and second processors jointly execute operations A and B) .

The storage 220 may store data/information obtained from the processing device 110, the terminal device 130, the storage device 140, or any other component of the simulation system 100. In some embodiments, the storage 220 may include a mass storage device, a removable storage device, a volatile read-and-write memory, a read-only memory (ROM) , or the like, or any combination thereof. In some embodiments, the storage 220 may store one or more programs and/or instructions to perform exemplary methods described in the present disclosure.

The I/O 230 may input or output signals, data, and/or information. In some embodiments, the I/O 230 may enable user interaction with the processing device 110. In some embodiments, the I/O 230 may include an input device and an output device. Exemplary input devices may include a keyboard, a mouse, a touch screen, a microphone, a camera capturing gestures, or the like, or a combination thereof. Exemplary output devices may include a display device, a loudspeaker, a printer, a projector, a 3D hologram, a light, a warning light, or the like, or a combination thereof. Exemplary 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) , or the like, or a combination thereof.

The communication port 240 may be connected with a network (e.g., the network 120) to facilitate data communications. The communication port 240 may establish connections between the processing device 110, the terminal device 130, or the storage device 140. The connection may be a wired connection, a wireless connection, or a combination of both that enables data transmission and reception. The wired connection may include an electrical cable, an optical cable, a telephone wire, or the like, or any combination thereof. The wireless connection may include a Bluetooth network, a Wi-Fi network, a WiMax network, a WLAN, a ZigBee network, a mobile network (e.g., 3G, 4G, 5G) , or the like, or any combination thereof. In some embodiments, the communication port 240 may be a standardized communication port, such as RS232, RS485, etc. In some embodiments, the communication port 240 may be a specially designed communication port. For example, the communication port 240 may be designed in accordance with the digital imaging and communications in medicine (DICOM) protocol.

FIG. 3 is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary mobile device according to some embodiments of the present disclosure. In some embodiments, one or more components (e.g., a terminal device 130 and/or the processing device 110) of the simulation system 100 may be implemented on the mobile device 300.

As illustrated in FIG. 3, 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, an I/O 350, a memory 360, and a storage 390. In some embodiments, any other suitable component, including but not limited to a system bus or a controller (not shown) , may also be included in the mobile device 300. In some embodiments, a mobile operating system 370 (e.g., iOS, Android, Windows Phone) and one or more applications 380 may be loaded into the memory 360 from the storage 390 in order to be executed by the CPU 340. The applications 380 may include a browser or any other suitable mobile apps for receiving and rendering information relating to image processing or other information from the processing device 110. User interactions with the information stream may be achieved via the I/O 350 and provided to the processing device 110 and/or other components of the simulation system via the network 120.

To implement various modules, units, and their functionalities described in the present disclosure, computer hardware platforms may be used as the hardware platform (s) for one or more of the elements described herein. The hardware elements, operating systems and programming languages of such computers are conventional in nature, and it is presumed that those skilled in the art are adequately familiar therewith to adapt those technologies to generate an image as described herein. A computer with user interface elements may be used to implement a personal computer (PC) or another type of work station or terminal device, although a computer may also act as a server if appropriately programmed. It is believed that those skilled in the art are familiar with the structure, programming and general operation of such computer equipment and as a result, the drawings should be self-explanatory.

FIG. 4 is a block diagram illustrating an exemplary processing device according to some embodiments of the present disclosure. As illustrated in FIG. 4, the processing device 110 may include an obtaining module 410, an initial energy level determination module 420, a ray path determination module 430, an attenuated energy level determination module 440, and a projection value determination module 450.

The obtaining module 410 may be configured to obtain data/information from one or more components of the simulation system 100. For example, the obtaining module 410 may obtain a simulation model relating to an imaging device from a storage device as disclosed elsewhere in the present disclosure. The simulation model may include a simulate source, a digital phantom, and a simulated detector, details of which may be found elsewhere in the present disclosure (e.g., FIG. 1, FIG. 5, FIG. 7 and the descriptions thereof) . As another example, the obtaining module 410 may obtain parameters relating to a scan to be performed on an object using the imaging device. The parameters relating to the scan may include structural parameters of the radiation source and the detector, physical parameters (e.g., the shape, the size, etc. ) of the object, position information of the radiation source, the detector, and/or the object, scan parameters (e.g., the voltage peak corresponding to the radiation source, a scan duration, a scan interval, etc. ) of the scan, or the like, or any combination thereof. As still another example, the obtaining module 410 may obtain an energy spectrum corresponding to a radiation source of the imaging device. More descriptions regarding the obtaining operation may be found elsewhere in the present disclosure (e.g., FIG. 5 and the description thereof) .

The initial energy level determination module 420 may be configured to determine a plurality of initial energy levels corresponding to the simulated source. For example, the initial energy level determination module 420 may determine, based on the energy spectrum corresponding to the radiation source, the plurality of initial energy levels. For example, the initial energy level determination module 420 may divide the energy spectrum into a plurality of intervals. The initial energy level determination module 420 may determine the plurality of initial energy intervals based on the plurality of intervals. More descriptions regarding the determination of the plurality of initial energy levels may be found elsewhere in the present disclosure (e.g., operation 520, FIG. 9, and the descriptions thereof) .

The ray path determination module 430 may be configured to determine a plurality of ray paths each of which one of simulated rays emitted by the simulated source traverses the digital phantom. For example, the ray path determination module 430 may determine the plurality of ray paths based on the simulated source and the simulated detector (e.g., a plurality of simulated detection points of the simulated detector) . More descriptions regarding the determination of the plurality of ray paths may be found elsewhere in the present disclosure (e.g., operation 530, FIG. 7, and the descriptions thereof) .

The attenuated energy level determination module 440 may be configured to determine a plurality of attenuated energy levels corresponding to each of the plurality of ray paths. For example, for each of the plurality of ray paths, the attenuated energy level determination module 440 may determine a portion of a plurality of elements of the digital phantom which the ray path traverses. For each of the plurality of initial energy levels, the attenuated energy level determination module 440 may determine one or more attenuation coefficients each of which corresponds to one of the portion of the plurality of elements. The attenuated energy level determination module 440 may determine based on the one or more attenuation coefficients, an attenuated energy level corresponding to the initial energy level as one of the plurality of attenuated energy levels that correspond to the ray path. More descriptions regarding the determination of the plurality of attenuated energy levels corresponding to each of the plurality of ray paths may be found elsewhere in the present disclosure (e.g., operation 540 and the description thereof) .

The projection value determination module 450 may be configured to determine simulated projection values of projection data corresponding to the plurality of ray paths. For example, for each of the plurality of ray paths, the projection value determination module 450 may determine an initial energy corresponding to the simulated projection value by summing the plurality of initial energy levels and determine an attenuated energy corresponding to one of the simulated projection values by summing the plurality of attenuated energy levels corresponding to the ray path. The projection value determination module 450 may determine the one of the simulated projection values based on the initial energy and the attenuated energy. More descriptions regarding the determination of the simulated projection values may be found elsewhere in the present disclosure (e.g., operation 550 and the description thereof) .

It should be understood that the modules of the processing device 110 shown in FIG. 2 can be implemented in various ways. For example, the modules may be implemented by hardware, software, or a combination of software and hardware. The hardware can be realized by dedicated logic, and the software can be stored in a storage device and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art can understand that the above-mentioned modules can be implemented using computer-executable instructions and/or included in processor control codes. For example, the processor control codes may be provided by a carrier medium such as a disk, CD or DVD-ROM, a memory such as a read-only memory (a firmware) programmable memory, or a data carrier such as an optical or electronic signal carrier. The modules in the present disclosure may be implemented by hardware, software, or a combination of the hardware and software (e.g., a firmware) . The hardware may include a very large-scale integrated circuit or gate array, a semiconductor (e.g., a logic chip, a transistor, etc. ) , hardware circuits of a programmable hardware device (e.g., a field-programmable gate array, a programmable logic device, etc. ) . The software may be executed by various types of processors. The modules in the processing device 110 may be connected to or communicated with each other via a wired connection or a wireless connection. The wired connection may include a metal cable, an optical cable, a hybrid cable, or the like, or any combination thereof. The wireless connection may include a Local Area Network (LAN) , a Wide Area Network (WAN) , a Bluetooth, a ZigBee, a Near Field Communication (NFC) , or the like, or any combination thereof.

It should be noted that the above description regarding the processing device 110 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. In some embodiments, two or more of the modules of the processing device 110 may be combined into a single module, and any one of the modules may be divided into two or more units. For example, the

modules

420, 430, 440, and 450 may be different modules in the processing device 110, or be integrated into a single module that can execute functions of two or more modules thereof. For instance, the attenuated energy level determination module 440 and the projection value determination module 450 may be integrated into a single module that can execute functions of the

modules

440 and 450. In some embodiments, the processing device 110 may include one or more additional modules. For example, the processing device 110 may include a storage module (not shown) used for storing data. As another example, the processing device 110 may include a reconstruction module for generating a simulated image based on the simulated projection values of the projection data using a reconstruction algorithm.

FIG. 5 is a flowchart illustrating an exemplary process for simulating projection data relating to an imaging device according to some embodiments of the present disclosure. In some embodiments, process 500 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., the storage device 140, the storage 220, and/or the storage 390) . The processing device 110 (e.g., the processor 210, the CPU 340, and/or one or more modules illustrated in FIG. 4) may execute the set of instructions, and when executing the instructions, the processing device 110 may be configured to perform the process 500. The operations of the illustrated process presented below are intended to be illustrative. In some embodiments, the process 500 may be accomplished with one or more additional operations not described and/or without one or more of the operations discussed. Additionally, the order of the operations of process 500 illustrated in FIG. 5 and described below is not intended to be limiting.

In 510, the processing device 110 (e.g., the obtaining module 410) may obtain a simulation model relating to the imaging device.

As described in FIG. 1, the imaging device may be configured to perform a scan on an object to acquire projection data of the object. The imaging device may include a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object. In some embodiments, the radiation source may be poly-energetic, e.g., including an X-ray tube. That is, the radiation rays (e.g., X-rays) emitted by the radiation source may include photons corresponding to a plurality of energy levels (also referred to as photon energies) . In some embodiments, different radiation sources may correspond to different voltage peaks. As used herein, a voltage peak refers to a maximum voltage applied between the cathode and anode of the X-ray tube of the radiation source during the scan performed on the object. A unit of the voltage peak may include a kilovolt peak (kVp) . In some embodiments, the plurality energy levels may relate to the voltage peak corresponding to the radiation source. For example, a maximum energy level (also referred to as a maximum photon energy) of the plurality of energy levels may correspond to the voltage peak. A unit of the maximum energy level may include a kiloelectron volt (keV) . The keV may be an energy unit that is needed by an electron being accelerated to pass through a voltage difference of 1000 v. A unit of an energy level may include a keV, a Gray (Gy) , etc. For instance, when the cathode and anode of the X-ray tube is applied by the voltage peak of 80 kVp, a maximum energy level of the plurality of energy levels may be 80 keV. A range of the plurality of energy levels may be from 0 keV to 80 keV (0～80 keV) . In some embodiments, the detector may include a plurality of detection units each of which can detect a projection value. The plurality of projection values may form the projection data.

The simulated model relating to the imaging device may be configured to simulate the imaging device. The simulated model may include a simulated source (e.g., the simulated source 111) , a simulated detector (e.g., the simulated detector 113) , and a digital phantom (e.g., the digital phantom 112) as described in FIG. 1. In some embodiments, the processing device 110 may obtain parameters relating to the scan to be performed on the object. The processing device 110 may determine the simulated model based on the parameters relating to the scan to be performed on the object. The parameters relating to the scan to be performed on the object may include structural parameters of the radiation source and the detector, physical parameters (e.g., the shape, the size, etc. ) of the object, position information of the radiation source, the detector, and/or the object, scan parameters (e.g., the voltage peak corresponding to the radiation source, a scan duration, a scan interval, etc. ) of the scan, or the like, or any combination thereof. For example, the processing device 110 may determine the simulated source 111, the simulated detector 113, and the digital phantom 112 based on the structural parameters of the radiation source, the structure parameters of the detector, and the physical parameters of the object respectively. As another example, the processing device 110 may determine a position of the object relative to the imaging device (e.g., relative positions of the simulated source 111, the simulated detector 113, and the digital phantom 112) based on the position information of the radiation source, the detector, and/or the object. The processing device 110 may determine positions of the digital phantom 112 relative to the simulated source 111 and the simulated detector 113 based on the position of the object relative to the imaging device. In some embodiments, the digital phantom 112 may include a plurality of elements (e.g., simulated voxels or pixels) . For example, if the object is a 3D object, the 3D object may be divided into a plurality of voxels and the digital phantom may be a 3D digital phantom (e.g., with a 3D structure) . The processing device 110 may divide the 3D digital phantom into a plurality of simulated voxels corresponding to the plurality of voxels. Alternatively, if the object is a 2D object, the 2D object may be divided into a plurality of pixels and the digital phantom may be a 2D digital phantom (e.g., a digital phantom of a panel structure) . The processing device 110 may divide the 2D digital phantom into a plurality of simulated pixels corresponding to the plurality of pixels. In some embodiments, the simulated detector 113 may include a plurality of simulated detection points each of which corresponds to one of simulated projection values of the projection data. The processing device 110 may determine the plurality of simulated detection points based on the plurality of detection units of the detector. For example, for each of the plurality of detection units, the processing device 110 may determine a point on the detection unit (e.g., a center of the detection unit, a point on a corner of the detector unit) . The processing device 110 may determine one of the plurality of simulated detection points based on the point on the detection units.

In some embodiments, the simulated model relating to the imaging device may be stored in a storage device (e.g., the storage device 140, the storage 220, the storage 390, or an external resource) . The processing device 110 may obtain or retrieve the simulated model from the storage device. In some embodiments, the simulated model may correspond to a coordinate system (e.g., an orthogonal coordinate system) in which positions of one or more components of the simulated model may be determined. More descriptions regarding the coordinate system may be found elsewhere in the present disclosure (e.g., FIG. 8 and the descriptions thereof) .

In 520, the processing device 110 (e.g., the initial energy level determination module 420) may determine, based on an energy spectrum corresponding to the radiation source of the imaging device, a plurality of initial energy levels corresponding to the simulated source of the simulation model.

As used herein, the energy spectrum of a radiation ray that the radiation source emits (or referred to as the energy spectrum corresponding to the radiation source) may reflect the number (or count) of photons for one of a plurality of energy levels of the radiation ray. That is, the energy spectrum may correspond to the plurality of energy levels. For illustration purposes, FIG. 6 is a schematic diagram illustrating an exemplary energy spectrum according to some embodiments of the present disclosure. As shown in FIG. 6, the energy spectrum 600 may correspond to 100 kVp. The energy spectrum 600 may include a plurality of energy levels within 0～100 keV.

In some embodiments, different voltage peaks may correspond to different energy spectrums. The processing device 110 may obtain a value of voltage peak corresponding to the radiation source. The processing device 110 may determine, based on the value of the voltage peak, the energy spectrum corresponding to the radiation source. As the simulated source is used to simulate the radiation source which is poly-energetic, the simulated source may be poly-energetic similarly including the plurality of initial energy levels. The more similar the plurality of the initial energy levels are to the plurality of energy levels, the more similar the simulated source may be to the radiation source and the better the simulation effect may be. However, the more the number (or count) of levels of the plurality of the initial energy levels are involved to simulate the energy spectrum, the larger the computation amount of the simulation process may be. In some embodiments, the processing device 110 may divide the energy spectrum into a plurality of intervals, which can reduce a computation amount during the simulation process. Further, the processing device 110 may determine the plurality of initial energy levels based on the plurality of intervals. More descriptions regarding the determination of the plurality of initial energy levels may be found elsewhere in the present disclosure (e.g., FIG. 7 and the description thereof) .

In 530, the processing device 110 (e.g., the ray path determination module 430) may determine, based on the simulated source and the simulated detector of the simulation model, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom.

As used herein, a simulated ray may be defined to include components (e.g., simulated photons) of the plurality of initial energy levels. Alternatively, a simulated ray may be defined to include a plurality of simulated sub-rays each of which corresponding to one of the plurality of initial energy levels. A simulated ray may correspond to a ray path. A ray path may correspond to one of simulated projection values of the projection data. For example, if the projection data includes 100 projection values, there may be 100 ray paths and 100 simulated rays. In some embodiments, the processing device 110 may determine the plurality of ray paths based on the simulated source and the plurality of simulated detection points of the simulated detector. For example, the processing device 110 may determine a line that passes through the simulated source and one of the plurality of simulated detection points. The processing device 110 may designate a portion of the line that traverses the digital phantom as one of the plurality of ray paths.

For illustration purposes, FIG. 7 is a schematic diagram illustrating an exemplary ray path in a simulated model according to some embodiments in the present disclosure. As shown in FIG. 7, the simulated model 700 may include a simulated source 710, a digital phantom 720, and a simulated detector 730. The simulated model 700 may correspond to a coordinate system 740. The coordinate system 740 may include an x-axis, a y-axis, and a z-axis. The simulated detector 730 may include five simulated detection points (SDPs) denotes as SDP 1, SDP 2, SDP 3, SDP 4, and SDP 5 corresponding to five ray paths. The processing device 110 may obtain coordinates of the simulated source 710, the five simulated detection points, and the digital phantom 720 in the coordinate system 740. For example, for the simulated detection point SDP 5, the processing device 110 may determine a line 750 which passes through the simulated source 810 and the simulated detection point SDP 5 based on coordinates of the simulated source 810 and the simulated detection point SDP 5. The processing device 110 may determine coordinates of two intersection points (e.g., point A and point B as shown in FIG. 7) of the line 750 with two surfaces of the digital phantom 820 in the coordinate system 840 to determine a dotted segment AB. The processing device 110 may designate the dotted segment AB as one of the five ray paths.

In 540, for each of the plurality of ray paths, the processing device 110 (e.g., the attenuated energy level determination module 440) may determine, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path.

For a specific energy level, each of the plurality of elements of the digital phantom may correspond to an attenuation coefficient such that the digital phantom may correspond to a spatial distribution of attenuation coefficients corresponding to the plurality of elements. For different energy levels, the digital phantom may correspond to different spatial distributions of attenuation coefficients corresponding to the different energy levels. In some embodiments, for a specific energy level, attenuation coefficients corresponding to the plurality of elements may be the same or different. For example, if the digital phantom corresponds to a homogeneous object (e.g., a non-biological object such as a water phantom, a wood phantom, or a metal phantom) , the attenuation coefficients corresponding to the plurality of elements may be the same. As another example, if the digital phantom corresponds to a nonhomogeneous object (e.g., a biological object such a patient or an animal) , the attenuation coefficients corresponding to the plurality of elements may be different. Alternatively, attenuation coefficients corresponding to a first portion of the plurality of elements may be the same, and attenuation coefficients corresponding to a second portion of the plurality of elements may be different. For example, if the digital phantom corresponds to a patient, first attenuation coefficients corresponding to the bone of the patient may be the same, second attenuation coefficients corresponding to the fat tissue of the patient may be the same, and third attenuation coefficients corresponding to the liver of the patient may be the same. The first attenuation coefficient, the second attenuation coefficient, and the third attenuation coefficient may be different. In some embodiments, attenuation coefficients corresponding to different energy levels and different materials may be pre-stored in a storage device disclosed elsewhere in the present disclosure. The processing device 120 may determine a material of a portion of the object that each element of the digital phantom corresponds to (also referred to as a material corresponsding to each element for brevity) . For a specifc energy level, the processing device 110 may obtain an attenuation coefficient corresponding to the material corresponding to the each element from the storage device to determine a spatial distribution of attenuation coefficeints corresponding to the digital phantom. More descriptions regarding the spatial distribution of coefficients may be found elsewhere in the present disclosure (e.g., FIG. 10 and the description thereof) .

In some embodiments, for each of the plurality of ray paths, the processing device 110 may identify one or more elements of the plurality of elements which the ray path traverses. For each of the plurality of initial energy levels, the processing device 110 may obtain a spatial distribution of attenuation coefficients corresponding to the initial energy level. The processing device 110 may determine, based on the spatial distribution of attenuation coefficients corresponding to the initial energy level, one or more coefficients each of which corresponds to one of the one or more elements for the initial energy interval. The processing device 110 may determine, based on the one or more attenuation coefficients, an attenuated energy level corresponding to the initial energy level as one of the plurality of attenuated energy levels corresponding to the ray path. For example, the processing device 110 may determine, based on the one or more attenuation coefficients, an amount of attenuation corresponding to the initial energy and the ray path. The processing device 110 may determine, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels corresponding to the ray path. More descriptions regarding the determination of the attenuated energy level corresponding to the initial energy level and the ray path may be found elsewhere in the present disclosure (e.g., FIG. 11 and the description thereof) .

In 550, for each of the plurality of ray paths, the processing device 110 (e.g., the simulated projection value determination module 450) may determine, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of simulated projection values of the projection data corresponding to the ray path.

In some embodiments, the processing device 110 may determine an initial energy corresponding to the simulated projection value by summing the plurality of initial energy levels. The processing device 110 may determine an attenuated energy corresponding to the simulated projection value by summing the plurality of attenuated energy levels corresponding to the ray path. The processing device 110 may determine, based on the initial energy and the attenuated energy, the one of the simulated projection values of the projection data corresponding to the ray path. For example, the processing device 110 may determine the one of the simulated projection values of the projection data corresponding to the ray path as a natural logarithm of a value of the initial energy divided by the attenuated energy. Accordingly, the processing device 110 may determine the simulated projection values of the projection data corresponding to the plurality of ray paths.

As described in connection with FIG. 10, the processing device 110 may determine an initial energy as I _a+I _b+I _c+I _d, wherein I _a, I _b, I _c, and I _d are initial energy levels corresponding to a ray path. The processing device 110 may determine an attenuated energy as I ₁+I ₂+I ₃+I ₄, wherein I ₁, I ₂, I ₃, and I ₄ are attenuated energy levels corresponding to the initial energy levels I _a, I _b, I _c, and I _d respectively. The processing device 110 may determine a simulated projection value corresponding to the ray path in FIG. 10 as

It should be noted that the above description regarding the process 500 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. In some embodiments, one or more operations of the process 500 may be omitted and/or one or more additional operations may be added. For example, a storing operation may be added elsewhere in the process 500. In the storing operation, the processing device 110 may store information and/or data (e.g., the simulated projection values of the projection data, the attenuated energy levels, the initial energy levels, etc. ) associated with the simulation system 100 in a storage device disclosed elsewhere in the present disclosure. As another example, an additional operation for generating, based on the simulated projection values of the projection data a simulated image relating to the object using a reconstruction algorithm may be added after operation 550. Exemplary reconstruction algorithms may include a Filter Back Projection (FBP) algorithm, an Algebraic Reconstruction Technique (ART) , a Local Reconstruction Algorithm (LocalRA) , an iterative reconstruction algorithm, or the like, or any combination thereof. The simulated image may further be used for research (e.g., researching and/or optimizing an artifact removal algorithm) or other purposes (e.g., display) . In some embodiments, two or more operations in the process 500 may be combined as a single operation, or an operation in the process 500 may be divided into at least two sub-operations. For example,

operations

540 and 550 may be combined as a single operation. As another example, the operation 520 may be divided into two sub-operations. In one of the sub-operations, the processing device 110 may divide the energy spectrum into a plurality of intervals. In the other of the sub-operations, the processing device 110 may determine the plurality of initial energy levels based on the plurality of intervals.

FIG. 8 is a flowchart illustrating an exemplary process for determining a plurality of initial energy levels according to some embodiments of the present disclosure. In some embodiments, process 800 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., the storage device 140, the storage 220, and/or the storage 390) . The processing device 110 (e.g., the processor 210, the CPU 340, and/or one or more modules illustrated in FIG. 4) may execute the set of instructions, and when executing the instructions, the processing device 110 may be configured to perform the process 800. The operations of the illustrated process presented below are intended to be illustrative. In some embodiments, the process 800 may be accomplished with one or more additional operations not described and/or without one or more of the operations discussed. Additionally, the order of the operations of process 800 illustrated in FIG. 8 and described below is not intended to be limiting. In some embodiments, the operation 520 may be achieved by one or more operations of the process 800.

In 810, the processing device 110 (e.g., the initial energy level determination module 420) may obtain a value of voltage peak corresponding to a radiation source.

In some embodiments, the processing device 110 may obtain the value of the voltage peak (e.g., 80 kVp, 100 kVp, 120 kVp, etc. ) from a storage device disclosed elsewhere in the present disclosure.

In 820, the processing device 110 (e.g., the initial energy level determination module 420) may determine, based on the value of voltage peak, an energy spectrum corresponding to the radiation source.

In some embodiments, the processing device 110 may determine the number (or count) of photons corresponding to each of the plurality of energy levels based on the voltage peak according to, e.g., a tungsten anode spectra model interpolating polynomial (TASMIP) algorithm. The processing device 110 may determine the energy spectrum based on numbers of photons corresponding to the plurality of energy levels. For example, the TASMIP algorithm may be expressed as Equation (1) below:

q (keV) =a0 (keV) +a1 (keV) *kVp+a2 (keV) *kVp^2+a3 (keV) *kVp^3, (1)

where q (eV) denotes the number (or count) of photons corresponding to a specific energy level of the plurality of energy levels, a0 (keV) , a1 (keV) , a2 (keV) , and a3 (keV) denote a set of coefficients corresponding to the specific energy level, kVp denotes the value of the voltage peak corresponding to the radiation source. The set of coefficients may reflect a relationship between the number (or count) of photons corresponding to the specific energy level and the value of the voltage peak corresponding to the radiation source. Different energy levels may correspond to different sets of coefficients. The different sets of coefficients may be pre-generated and stored with corresponding energy levels as a table or list. The processing device 110 may obtain the set of coefficients corresponding to the specific energy level in the table by looking up the table. Taking the voltage peak of 80 kVp as an example, the plurality of energy levels corresponding to 80 kVp may be 0～80 keV. For an energy level of 50 keV, the number (or count) of photons corresponding to 50 keV may be equal to a0 (50) +a1 (50) *80+a2 (50) *80^2+a3 (50) *80^3, wherein a0 (50) , a1 (50) , a2 (50) , and a3 (50) denote a set of coefficients corresponding to 50 keV. Further, the processing device 110 may determine the energy spectrum corresponding to 80 kVp based on the numbers of photons corresponding to the plurality of energy levels.

In some embodiments, different energy spectrums and corresponding voltage peaks may be pre-stored in a storage device disclosed elsewhere in the present disclosure. The processing device 110 may obtain the energy spectrum based on the voltage peak directly from the storage device (e.g., by a table look-up manner) .

In 830, the processing device 110 (e.g., the initial energy level determination module 420) may divide the energy spectrum into a plurality of intervals.

In some embodiments, the processing device 110 may divide the energy spectrum into a plurality of intervals according to a specific energy interval. The specific energy interval may include any value of KeV such as 1 KeV, 5 KeV, 10 KeV, 15 KeV, 20 KeV, etc. ) . The smaller the specific energy interval is, the more similar the simulated source may be to the radiation source and the more complex the computation may be. For example, for the specific energy level of 1 KeV, the plurality of energy levels corresponding to 80 kVp may include 80 intervals. As another example, for the specific energy level of 10 KeV, the plurality of energy levels corresponding to 80 kVp may include 8 intervals.

For illustration purposes, FIG. 9 is a schematic diagram illustrating an exemplary division of an energy spectrum according to some embodiments of the present disclosure. As shown in FIG. 9, a radiation source 910 corresponding to 80 kVp may emit X-rays including photons corresponding to energy levels of 0-80 KeV. The specific energy level may be 20 KeV, such that the energy spectrum may be divided into 4 intervals denoted by itl1 (0-20 KeV) , itl2 (20-40 KeV) , itl3 (40-60 KeV) , and itl4 (60-80 KeV) , respectively. Photons within one of the 4 intervals may be regarded as forming a sub-ray, such that the X-rays may be divided into 4 sub-rays denoted by sub-ray 1, sub-ray 2, sub-ray 3, and sub-4, respectively. The sub-ray 1 may correspond to the interval itl1, the sub-ray 2 may correspond to the interval itl2, the sub-ray 3 may correspond to the interval itl3, and the sub-ray 4 may correspond to the interval itl4.

In 840, the processing device 110 (e.g., the initial energy level determination module 420) may determine the plurality of initial energy levels based on the plurality of intervals.

In some embodiments, each of the plurality of intervals may correspond to one of the plurality of initial energy levels. As the energy spectrum reflects the number of photons corresponding to each of the plurality of energy levels, the processing device 110 may designate a total energy of photons in each of the plurality of intervals as one of the plurality of initial energy levels. For example, for each of the plurality of intervals, the processing device 110 may determine the number (or count) of photons in each energy level within the interval based on the energy spectrum. The processing device 110 may determine the total energy of photons in the interval by summing a total energy of photons in each energy level within the interval. For the interval itl1 shown in FIG. 7, the processing device 110 may determine the number (or count) of photons in each energy level within 0-20 KeV based on the energy spectrum corresponding to 80 kVp. For each energy level within 0-20 KeV, the processing device 110 may determine a total energy of photons in the energy level by multiplying the energy level and the number (or count) of photons in the energy level. Alternatively, for each energy level within 0-20 KeV, the processing device 110 may determine a total energy of photons in the energy level by multiplying a photon dose corresponding to the energy level and the number of photons in the energy level. As used herein, a photon dose corresponding to an energy level refers to a dosage (e.g., a value of Gy) of a single photon with the energy level. Different energy levels may correspond to different photon doses, which can be pre-stored in a storage device disclosed elsewhere in the present disclosure. Further, the processing device 110 may determine a total energy of photons in the interval itl1 by summing the total energy of photons in each energy level within 0-20 KeV. Similarly, the processing device 110 may determine a total energy of photons in each of the intervals tl2, itl3, and itl4. The processing device 110 may designate the four total energies of photons in the intervals itl1, itl2, itl3, and itl4 as four initial energy levels.

In some embodiments, as the energy spectrum reflects a plurality of energy levels, the processing device 110 may determine a total energy of photons in each of the plurality of intervals based on a total number (or count) of photons in the interval and an equivalent energy level of the interval. As used herein, an equivalent energy of an interval may refer to an average or medium energy level of the energy levels within the interval. For example, for the intervals of itl1～itl4 shown in FIG. 7, the processing device 110 may determine the numbers (or counts) of photons in the intervals itl1～itl4 denoted by lnum1, lnum2, lnum 3, and lnum 4, respectively, based on the energy spectrum. For the interval itl 2, the processing device 110 may determine an equivalent energy level of the interval itl2 based on an average of a minimum energy level and maximum energy level in the interval itl2, i.e., (20+40) /2=30 (KeV) . The processing device 110 may determine a total energy of photons in the interval itl2 by multiplying the number of photons in the interval itl2 and the equivalent energy level of the interval itl2, i.e., lnum2× (20+40) /2 (KeV) . Similarly, the processing device 110 may determine total energies corresponding to the intervals itl1, itl2, and itl3 as lnum1× (0+20) /2 (KeV) , lnum3× (40+60) /2 (KeV) , and lnum4× (60+80) /2 (KeV) , respectively. Further, the processing device 110 may designate lnum1× (0+20) /2 (KeV) , lnum2× (20+40) /2 (KeV) , lnum3× (40+60) /2 (KeV) , and lnum4× (60+80) /2 (KeV) as the four initial energy levels.

It should be noted that the above descriptions regarding the

processes

700 and 800 are merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. The operations of the illustrated process presented above are intended to be illustrative. In some embodiments, the process 800 may be accomplished with one or more additional operations not described and/or without one or more of the operations discussed. In some embodiments, at least two operations in the process 800 may be achieved in one operation and/or one operation in the process 800 may be achieved by two sub-operations.

FIG. 10 is a schematic diagram illustrating exemplary spatial distributions of attenuation coefficients corresponding to a digital phantom according to some embodiments of the present disclosure. The digital phantom may include a cube structure similar to the digital phantom 720 as shown in FIG. 7. The digital phantom may be divided into 4×4 simulated voxels along the x-axis and the y-axis. In such occasions, a spatial distribution of attenuation coefficients may be equivalent to a 2D distribution on the xz plane. The simulated voxels may be denoted by serial numbers of 1, 2, 3, ..., 16. A simulated ray corresponding to a ray path (not shown) may pass through

voxels

1, 5, 6, 7, 11, and 12. The ray path may pass through the voxel 1 with a path length l ₁, pass through the voxel 5 with a path length l ₅, pass through the voxel 6 with a path length l ₆, pass through the voxel 7 with a path length l ₇, pass through the voxel 11 with a path length l ₁₁, and pass through the voxel 12 with a path length l ₁₂. The values of the path lengths may be determined based on coordinates of the ray path and coordinates of the digital phantom. The simulated ray may be regarded as including four simulated sub-rays denoted by serial numbers of 1, 2, 3, and 4. The four simulated sub-rays may correspond to different initial energy levels (e.g., denoted by I _a, I _b, I _c, and I _d, respectively) such that the four simulated sub-rays may correspond to different spatial distributions of attenuation coefficients. The simulated sub-ray 1 corresponding to I _a may correspond to a spatial distribution 1010 of attenuation coefficients, the simulated sub-ray 2 corresponding to I _b may correspond to a spatial distribution 1020 of attenuation coefficients, the simulated sub-ray 3 corresponding to I _c may correspond to a spatial distribution 1030 of attenuation coefficients, and the simulated sub-ray 4 corresponding to I _d may correspond to a spatial distribution 1040 of attenuation coefficients. An attenuation coefficient in a spatial distribution of attenuated coefficients may be denoted by μ _ij, wherein i denotes a serial number corresponding to a simulated sub-ray and j denotes a serial number corresponding to a voxel.

FIG. 11 is a flowchart illustrating an exemplary process for determining an amount of attenuation corresponding to an initial energy level and a ray path according to some embodiments of the present disclosure. In some embodiments, process 1100 may be implemented as a set of instructions (e.g., an application) stored in a storage device (e.g., the storage device 140, the storage 220, and/or the storage 390) . The processing device 110 (e.g., the processor 210, the CPU 340, and/or one or more modules illustrated in FIG. 4) may execute the set of instructions, and when executing the instructions, the processing device 110 may be configured to perform the process 1100. The operations of the illustrated process presented below are intended to be illustrative. In some embodiments, the process 1100 may be accomplished with one or more additional operations not described and/or without one or more of the operations discussed. Additionally, the order of the operations of process 1100 illustrated in FIG. 11 and described below is not intended to be limiting. In some embodiments, a portion of the operation 540 may be achieved by the process 1100.

In 1110, the processing device 110 (e.g., the attenuated energy level determination module 440) may determine an amount of attenuation corresponding to the initial energy level and the ray path.

In some embodiments, an amount of attenuation corresponding to an initial energy level may be expressed by an attenuation integral corresponding to the initial energy level. The processing device 110 may determine an attenuation integral corresponding to the initial energy level based on the one or more attenuation coefficients and the one or more elements. For example, for the initial energy level, the processing device 110 may determine the one or more attenuation coefficients each of which corresponds to one of one or more elements through which the ray path traverses. The processing device 110 may determine the attenuation integral corresponding to the initial energy level based on a sum of the attenuation coefficients. For the initial energy level I _a corresponding to the simulated sub-ray 1 as shown in FIG. 10, the processing device 110 may determine one or more coefficients being μ ₁₁, μ ₁₅, μ ₁₆, μ ₁₇, μ ₁₁₁, and μ ₁₁₂. The processing device 110 may determine an attenuation integral corresponding to the initial energy level I _a as - (μ ₁₁+μ ₁₅ +μ ₁₆ +μ ₁₇ + μ ₁₁₁ + μ ₁₁₂) .

As another example, for the initial energy level, the processing device 110 may determine the one or more attenuation coefficients each of which corresponds to one of the one or more elements and the path length of the element when the ray path passes through the element. For the initial energy level, each of the one or more elements may correspond to one of the one or more attenuation coefficients and one of the one or more path lengths. The processing device 110 may determine the attenuation integral corresponding to the initial energy level based on a sum of products each of which is determined by multiplying an attenuation coefficient and the corresponding path length of one of the one or more elements along the ray path. For the initial energy level I _a corresponding to the simulated sub-ray 1 as shown in FIG. 10, the processing device 110 may determine the one or more attenuation coefficients being μ ₁₁, μ ₁₅, μ ₁₆, μ ₁₇, μ ₁₁₁, and μ ₁₁₂, and the one or more path lengths being l ₁, l ₅, l ₆, l ₇, l ₁₁, and l ₁₂. The processing device 110 may determine an attenuation integral corresponding to the initial energy level I _a as - (l ₁μ ₁₁ +l ₅μ ₁₅ +l ₆μ ₁₆ + l ₇μ ₁₇ + l ₁₁μ ₁₁₁ +l ₁₂μ ₁₁₂) .

As still another example, the processing device 110 may determine the one or more attenuation coefficients each of which corresponds to one of the one or more elements, and one or more sizes (e.g., an area or a volume) each of which corresponds to one of the one or more elements. For the initial energy level, each of the one or more elements may correspond to one of the one or more attenuation coefficients and one of the one or more sizes. The processing device 110 may determine the attenuation integral corresponding to the initial energy level based on a sum of products each of which is determined by multiplying the attenuation coefficient and the corresponding size of one of the one or more elements along the ray path.

In 1120, the processing device 110 (e.g., the attenuated energy level determination module 440) may determine, based on the initial energy level and the amount of attenuation, an attenuated energy level corresponding to the initial energy level as one of the plurality of attenuated energy levels corresponding to the ray path.

In some embodiments, the processing device 110 may determine the attenuated energy level corresponding to the initial energy level by multiplying the initial energy and a natural exponent of the attenuation integral as the one of the plurality of attenuated energy levels corresponding to the ray path. For example, attenuated energy levels corresponding to simulated sub-rays as shown in FIG. 9 may be denoted by I ₁, I ₂, I ₃, and I ₄, respectively. The processing device 110 may determine the attenuated energy level I ₁ corresponding to the initial energy level I _a as

Similarly, the processing device 110 may determine the attenuated energy levels I ₂, I ₃, and I ₄.

It should be noted that the above description regarding the process 1100 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure.

Having thus described the basic concepts, it may be rather apparent to those skilled in the art after reading this detailed disclosure that the foregoing detailed disclosure is intended to be presented by way of example only and is not limiting. Various alterations, improvements, and modifications may occur and are intended to those skilled in the art, though not expressly stated herein. These alterations, improvements, and modifications are intended to be suggested by this disclosure and are within the spirit and scope of the exemplary embodiments of this disclosure.

Moreover, certain terminology has been used to describe embodiments of the present disclosure. For example, the terms “one embodiment, ” “an embodiment, ” and/or “some embodiments” mean that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, it is emphasized and should be appreciated that two or more references to “an embodiment” or “one embodiment” or “an alternative embodiment” in various portions of this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures or characteristics may be combined as suitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects of the present disclosure may be illustrated and described herein in any of a number of patentable classes or context including any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof. Accordingly, aspects of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc. ) or combining software and hardware implementation that may all generally be referred to herein as a “unit, ” “module, ” or “system. ” Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer-readable media having computer-readable program code embodied thereon.

A non-transitory computer-readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including electromagnetic, optical, or the like, or any suitable combination thereof. A computer-readable signal medium may be any computer-readable medium that is not a computer-readable storage medium and that may communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable signal medium may be transmitted using any appropriate medium, including wireless, wireline, optical fiber cable, RF, or the like, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object-oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET, Python or the like, conventional procedural programming languages, such as the "C" programming language, Visual Basic, Fortran, Perl, COBOL, PHP, ABAP, dynamic programming languages such as Python, Ruby, and Groovy, or other programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN) , or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider) or in a cloud computing environment or offered as a service such as a Software as a Service (SaaS) .

Furthermore, the recited order of processing elements or sequences, or the use of numbers, letters, or other designations, therefore, is not intended to limit the claimed processes and methods to any order except as may be specified in the claims. Although the above disclosure discusses through various examples what is currently considered to be a variety of useful embodiments of the disclosure, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover modifications and equivalent arrangements that are within the spirit and scope of the disclosed embodiments. For example, although the implementation of various components described above may be embodied in a hardware device, it may also be implemented as a software-only solution, e.g., an installation on an existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description of embodiments of the present disclosure, various features are sometimes grouped together in a single embodiment, figure, or description thereof to streamline the disclosure aiding in the understanding of one or more of the various inventive embodiments. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed object matter requires more features than are expressly recited in each claim. Rather, inventive embodiments lie in less than all features of a single foregoing disclosed embodiment.

In some embodiments, the numbers expressing quantities, properties, and so forth, used to describe and claim certain embodiments of the application are to be understood as being modified in some instances by the term “about, ” “approximate, ” or “substantially. ” For example, “about, ” “approximate” or “substantially” may indicate ±20%variation of the value it describes, unless otherwise stated. Accordingly, in some embodiments, the numerical parameters set forth in the written description and attached claims are approximations that may vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the application are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable.

Each of the patents, patent applications, publications of patent applications, and other material, such as articles, books, specifications, publications, documents, things, and/or the like, referenced herein is hereby incorporated herein by this reference in its entirety for all purposes, excepting any prosecution file history associated with same, any of same that is inconsistent with or in conflict with the present document, or any of same that may have a limiting effect as to the broadest scope of the claims now or later associated with the present document. By way of example, should there be any inconsistency or conflict between the description, definition, and/or the use of a term associated with any of the incorporated material and that associated with the present document, the description, definition, and/or the use of the term in the present document shall prevail.

In closing, it is to be understood that the embodiments of the application disclosed herein are illustrative of the principles of the embodiments of the application. Other modifications that may be employed may be within the scope of the application. Thus, by way of example, but not of limitation, alternative configurations of the embodiments of the application may be utilized in accordance with the teachings herein. Accordingly, embodiments of the present application are not limited to that precisely as shown and described.

Claims

A method for simulating projection data relating to an imaging device that includes a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object, the method being implemented on a computing device including at least one processor and at least one storage device, comprising:

obtaining a simulation model relating to the imaging device, wherein the simulation model includes a simulated source for simulating the radiation source, a simulated detector for simulating the detector, and a digital phantom including a plurality of elements for simulating the object;

determining, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding to the simulated source;

determining, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom, wherein

the each ray path corresponds to one of simulated projection values of the projection data, and

the one of the simulated rays includes components of the plurality of initial energy levels;

for each of the plurality of ray paths,

determining, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverse at least a portion of the plurality of elements, wherein each of the plurality of attenuated energy levels corresponds to one of the plurality of initial energy levels; and

determining, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data that corresponds to the ray path.
The method of claim 1, wherein the obtaining a simulation model relating to the imaging device includes:

obtaining a position of the object relative to the imaging device; and

determining the simulation model based on the position of the object relative to the imaging device.
The method of claim 1 or 2, wherein the determining, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding the simulated source includes:

obtaining a value of voltage peak corresponding to the radiation source;

determining, based on the value of voltage peak, the energy spectrum corresponding to the radiation source;

dividing the energy spectrum into a plurality of intervals each of which corresponds to one of the plurality of initial energy levels; and

determining the plurality of initial energy levels based on the plurality of intervals.
The method of any one of claims 1-3, wherein the simulated detector includes a plurality of simulated detection points, and the determining, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom includes:

determining a line that passes through the simulated source and one of the plurality of simulated detection points; and

designating a portion of the line that traverses the digital phantom as one of the plurality of ray paths.
The method of any one of claims 1-4, wherein for each of the plurality of ray paths, the determining, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverses at least a portion of the plurality of elements includes:

determining one or more elements of the plurality of elements through which the ray path traverses;

for each of the plurality of initial energy levels,

determining one or more attenuation coefficients each of which corresponds to one of the one or more elements for the initial energy level; and

determining, based on the one or more attenuation coefficients, an attenuated energy level corresponding to the initial energy level as one of the plurality of attenuated energy levels that correspond to the ray path.
The method of claim 5, wherein the determining, based on the one or more attenuation coefficients, an attenuated energy level corresponding to the initial energy level as one of the plurality of attenuated energy levels that correspond to the ray path includes:

determining, based on the one or more attenuation coefficients, an amount of attenuation corresponding to the initial energy level and the ray path; and

determining, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels that correspond to the ray path.
The method of claim 6, wherein the determining, based on the one or more attenuation coefficients, an amount of attenuation corresponding to the initial energy level and the ray path includes:

determining the amount of attenuation corresponding to the initial energy level and the ray path based on the one or more attenuation coefficients and the one or more elements.
The method of claim 7, wherein the determining, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels corresponding to the ray path includes:

determining, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels corresponding to the ray path.
The method of any one of claims 1-8, wherein the determining, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data corresponding to the ray path includes:

determining an initial energy corresponding to the simulated projection value by summing the plurality of initial energy levels;

determining an attenuated energy corresponding to the simulated projection value by summing the plurality of attenuated energy levels corresponding to the ray path; and

determining, based on the attenuated energy corresponding to the ray path and the initial energy, the one of the simulated projection values of the projection data corresponding to the ray path.
The method of any one of claims 1-9, further comprising:

generating, based on the simulated projection values of the projection data, a simulated image relating to the object using a reconstruction algorithm.
A system for simulating projection data relating to an imaging device that includes a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object, the system comprising:

a storage device storing a set of instructions; and

at least one processor in communication with the storage device, wherein when executing the set of instructions, the at least one processor is configured to cause the system to perform operations including:

obtaining a simulation model relating to the imaging device, wherein the simulation model includes a simulated source for simulating the radiation source, a simulated detector for simulating the detector, and a digital phantom including a plurality of elements for simulating the object;

determining, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding to the simulated source;

determining, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom, wherein

the each ray path corresponds to one of simulated projection values of the projection data, and

the one of the simulated rays includes components of the plurality of initial energy levels;

for each of the plurality of ray paths,

determining, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverse at least a portion of the plurality of elements, wherein each of the plurality of attenuated energy levels corresponds to one of the plurality of initial energy levels; and

determining, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data that corresponds to the ray path.
The system of claim 11, wherein the obtaining a simulation model relating to the imaging device includes:

obtaining a position of the object relative to the imaging device; and

determining the simulation model based on the position of the object relative to the imaging device.
The system of claim 11 or 12, wherein the determining, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding the simulated source includes:

obtaining a value of voltage peak corresponding to the radiation source;

determining, based on the value of voltage peak, the energy spectrum corresponding to the radiation source;

dividing the energy spectrum into a plurality of intervals each of which corresponds to one of the plurality of initial energy levels; and

determining the plurality of initial energy levels based on the plurality of intervals.
The system of any one of claims 11-13, wherein the simulated detector includes a plurality of simulated detection points, and the determining, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom includes:

determining a line that passes through the simulated source and one of the plurality of simulated detection points; and

designating a portion of the line that traverses the digital phantom as one of the plurality of ray paths.
The system of any one of claims 11-14, wherein for each of the plurality of ray paths, the determining, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverses at least a portion of the plurality of elements includes:

determining one or more elements of the plurality of elements through which the ray path traverses;

for each of the plurality of initial energy levels,

determining one or more attenuation coefficients each of which corresponds to one of the one or more elements for the initial energy level; and

determining, based on the one or more attenuation coefficients, an attenuated energy level corresponding to the initial energy level as one of the plurality of attenuated energy levels that correspond to the ray path.
The system of claim 15, wherein the determining, based on the one or more attenuation coefficients, an attenuated energy level corresponding to the initial energy level as one of the plurality of attenuated energy levels that correspond to the ray path includes:

determining, based on the one or more attenuation coefficients, an amount of attenuation corresponding to the initial energy level and the ray path; and

determining, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels that correspond to the ray path.
The system of claim 16, wherein the determining, based on the one or more attenuation coefficients, an amount of attenuation corresponding to the initial energy level and the ray path includes:

determining the amount of attenuation corresponding to the initial energy level and the ray path based on the one or more attenuation coefficients and the one or more elements.
The system of claim 17, wherein the determining, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels corresponding to the ray path includes:

determining, based on the amount of attenuation, the attenuated energy level corresponding to the initial energy level as the one of the plurality of attenuated energy levels corresponding to the ray path.
The system of any one of claims 11-18, wherein the determining, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data corresponding to the ray path includes:

determining an initial energy corresponding to the simulated projection value by summing the plurality of initial energy levels;

determining an attenuated energy corresponding to the simulated projection value by summing the plurality of attenuated energy levels corresponding to the ray path; and

determining, based on the attenuated energy corresponding to the ray path and the initial energy, the one of the simulated projection values of the projection data corresponding to the ray path.
The system of any one of claims 11-19, further comprising:

generating, based on the simulated projection values of the projection data, a simulated image relating to the object using a reconstruction algorithm.
A system for simulating projection data relating to an imaging device that includes a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object, the system comprising:

an obtaining module configured to obtain a simulation model relating to the imaging device, wherein the simulation model includes a simulated source for simulating the radiation source, a simulated detector for simulating the detector, and a digital phantom including a plurality of elements for simulating the object;

an initial energy level determination module configured to determine, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding to the simulated source;

a ray path determination module configured to determine, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom, wherein

the each ray path corresponds to one of simulated projection values of the projection data, and

the one of the simulated rays includes components of the plurality of initial energy levels; and

an attenuated energy level determination module configured to for each of the plurality of ray paths, determining, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverse at least a portion of the plurality of elements, wherein each of the plurality of attenuated energy levels corresponds to one of the plurality of initial energy levels; and

a simulated projection value determination module configured to for each of the plurality of ray paths, determine, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data that corresponds to the ray path.
A non-transitory computer readable medium, comprising executable instructions that, when executed by at least one processor, direct the at least one processor to perform a method for simulating projection data relating to an imaging device that includes a radiation source configured to emit radiation rays towards an object and a detector configured to detect at least a portion of the radiation rays that have traversed the object, the method comprising:

obtaining a simulation model relating to the imaging device, wherein the simulation model includes a simulated source for simulating the radiation source, a simulated detector for simulating the detector, and a digital phantom including a plurality of elements for simulating the object;

determining, based on an energy spectrum corresponding to the radiation source, a plurality of initial energy levels corresponding to the simulated source;

determining, based on the simulated source and the simulated detector, a plurality of ray paths along each of which one of simulated rays emitted by the simulated source traverses the digital phantom, wherein

the each ray path corresponds to one of simulated projection values of the projection data, and

the one of the simulated rays includes components of the plurality of initial energy levels;

for each of the plurality of ray paths,

determining, based on the plurality of initial energy levels, a plurality of attenuated energy levels corresponding to the ray path that traverse at least a portion of the plurality of elements, wherein each of the plurality of attenuated energy levels corresponds to one of the plurality of initial energy levels; and

determining, based on the plurality of attenuated energy levels corresponding to the ray path and the plurality of initial energy levels, one of the simulated projection values of the projection data that corresponds to the ray path.