CN111462267A

CN111462267A - Method and system for acquiring X-ray projection data

Info

Publication number: CN111462267A
Application number: CN202010229949.4A
Authority: CN
Inventors: 崔凯; 马艳歌; 张娜; 牛杰; 冯娟
Original assignee: Shanghai United Imaging Healthcare Co Ltd
Current assignee: Shanghai United Imaging Healthcare Co Ltd
Priority date: 2020-03-27
Filing date: 2020-03-27
Publication date: 2020-07-28
Also published as: WO2021190276A1

Abstract

One or more embodiments of the present specification relate to a method and system for acquiring X-ray projection data, the method including: determining an energy spectrum of the incident X-rays; the energy spectrum reflects the number of photons of different energies in the incident X-ray; determining, based on the energy spectrum, two or more beamlets of different energies in the incident X-rays; determining one or more paths for the incident X-rays to traverse a digital phantom; for either path: acquiring path integrals of attenuation coefficients corresponding to different sub-beams under the path based on the spatial distribution of the attenuation coefficients of the digital die body to the different sub-beams; determining projection data of the incident X-rays traversing the digital phantom via a path based on an integral of the incident energy of each beamlet and its corresponding attenuation coefficient.

Description

Method and system for acquiring X-ray projection data

Technical Field

The present application relates to the field of medical imaging technologies, and in particular, to a method and a system for acquiring X-ray projection data.

Background

When reconstructing an image using projection data acquired by medical equipment such as Computed Tomography (CT), Digital Radiography (DR), Digital Subtraction Angiography (DSA), and the like, since X-rays used by the equipment are multi-energy, various artifacts such as a hardening artifact and a scattering artifact may occur in the reconstructed image, it is necessary to optimize the reconstructed image using an artifact removal Algorithm. In order to verify the quality of the hardening artifact removal algorithm, sometimes a digital phantom is used to simulate projection data acquired by a real device, namely projection data under multi-energy X-ray photography. However, most of the prior art is simulation algorithm based on single-energy X-ray, and the projection image reconstructed based on the single-energy forward projection algorithm has no artifact.

It is therefore desirable to have a multi-energy X-ray based orthographic projection algorithm for simulating multi-energy X-ray projection data using a digital phantom.

Disclosure of Invention

One embodiment of the present application provides a method for acquiring X-ray projection data. The method comprises the following steps:

determining an energy spectrum of the incident X-rays; the energy spectrum reflects the number of photons of different energies in the incident X-ray; determining, based on the energy spectrum, two or more beamlets of different energies in the incident X-rays; determining one or more paths for the incident X-rays to traverse a digital phantom; for either path: acquiring path integrals of attenuation coefficients corresponding to different sub-beams under the path based on the spatial distribution of the attenuation coefficients of the digital die body to the different sub-beams; determining projection data of the incident X-rays traversing the digital phantom via a path based on an integral of the incident energy of each beamlet and its corresponding attenuation coefficient.

One embodiment of the present application provides an acquisition system for X-ray projection data. The system comprises:

the energy spectrum determining module is used for determining the energy spectrum of the incident X-ray; the energy spectrum reflects the number of photons of different energies in the incident X-ray; a beamlet determination module for determining beamlets of two or more different energies in the incident X-rays based on the energy spectrum; a path determination module for determining one or more paths for the incident X-rays to traverse the digital phantom; the path integral acquisition module is used for acquiring path integrals of the attenuation coefficients corresponding to different sub-beams under the path based on the spatial distribution of the attenuation coefficients of the digital die body to different sub-beams; and the projection data determination module is used for determining the projection data of the incident X-ray passing through the digital phantom through the path based on the path integral of the incident energy of each sub-beam and the attenuation coefficient corresponding to the incident energy.

One of the embodiments of the present application provides an apparatus for acquiring X-ray projection data, which includes a processor configured to execute an acquisition method of X-ray projection data.

One of the embodiments of the present application provides a computer-readable storage medium, where the storage medium stores computer instructions, and after the computer reads the computer instructions in the storage medium, the computer executes an acquisition method of X-ray projection data.

Drawings

The present application will be further explained by way of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not intended to be limiting, and in these embodiments like numerals are used to indicate like structures, wherein:

FIG. 1 is a schematic diagram of an exemplary projection data acquisition system shown in accordance with some embodiments of the present application;

FIG. 2 is a block diagram of an X-ray projection data acquisition system according to some embodiments of the present application;

FIG. 3 is an exemplary flow chart of a method of acquiring X-ray projection data according to some embodiments of the present application;

FIG. 4 is a schematic illustration of an exemplary incident X-ray energy spectrum and photon intervals, shown in accordance with some embodiments of the present application;

FIG. 5A is a schematic illustration of the path of an exemplary incident X-ray through a digital phantom, according to some embodiments of the present application; and

fig. 5B is a schematic illustration of a spatial distribution of attenuation coefficients of an exemplary digital phantom for different beamlets, according to some embodiments of the present application.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments will be briefly introduced below. It is obvious that the drawings in the following description are only examples or embodiments of the application, from which the application can also be applied to other similar scenarios without inventive effort for a person skilled in the art. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

It should be understood that "system", "device", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.

As used in this application and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Flow charts are used herein to illustrate operations performed by systems according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.

FIG. 1 is a schematic diagram of an exemplary projection data acquisition system shown in accordance with some embodiments of the present application.

In some embodiments, the system for acquiring X-ray projection data may acquire simulated projection data of the multi-energy X-ray beam by using a digital phantom. As shown in fig. 1, projection data acquisition system 100 may include a processing device 110, a network 120, a terminal 130, and a storage device 140. The components in the projection data acquisition system 100 may be connected to each other in a variety of ways. For example, processing device 110 may be connected to storage device 140 via network 120. As another example, processing device 110 may be directly connected to storage device 140. As another example, the terminal 130 may be connected to the storage device 140 directly or via the network 120.

The processing device 110 may emulate a scanning system. The scanning system includes an analog source 111, a digital phantom 112, and an analog detector 113. The analog source 111 and the analog detector 113 may be oppositely disposed on either side of the digital phantom 112. Digital phantoms 112 may be used to simulate the subject. The subject to be examined, which is simulated by the digital phantom 112, can be an organism (e.g., a patient, an animal, an organ, etc.) or a non-organism (e.g., a phantom, a water phantom, etc.). The analog source 111 may simulate an X-ray tube emitting X-rays from different directions. Analog detector 113 includes a plurality of analog detection points, and in some embodiments, one or more incident X-rays may be determined by simulating a plurality of analog detection points of source 111 and analog detector 113. Each incident X-ray corresponds to one projection datum, e.g., three incident X-rays as shown in FIG. 1 correspond to three projection data. When data is reconstructed using projection data acquired by a medical apparatus, since X-rays used by the medical apparatus are generally multi-energy, various artifacts such as a hardening artifact and a scattering artifact may occur in a reconstructed image, and it is necessary to optimize the reconstructed image using an artifact removal algorithm. Some research institutions, schools, or other institutions do not have medical equipment such as CT, angiography (DSA), etc., but may use the scanning system simulated in the processing device 110 to acquire projection data substantially identical to projection data acquired by real medical equipment by the methods described in some embodiments of the present application in order to verify whether various artifact removal algorithms are valid. For a detailed method for acquiring projection data, please refer to fig. 3, which is not described herein again.

In some embodiments, the processing device 110 may be a Central Processing Unit (CPU), a Digital Signal Processor (DSP), a system on chip (SoC), a Microprocessor (MCU), or the like, or any combination thereof. 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 130 and/or the storage device 140 via the network 120. As another example, the processing device 110 may be directly coupled to the terminal 130 and/or the storage device 140 to access information and/or data stored therein. In some embodiments, the processing device 110 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, across clouds, multiple clouds, the like, or any combination thereof.

In some embodiments, the storage device 140 may obtain emulated projected data from the processing device 110 via the network 120. for another example, the processing device 110 may obtain user instructions from the terminal 130 via the network 120. in some embodiments, the network 120 may be any type of wired or wireless network, or combinations thereof.the network 120 may include a public network (e.g., the Internet), a private network (e.g., a local area network (L AN), a Wide Area Network (WAN)), a wired network (e.g., AN Ethernet), a wireless network (e.g., AN 802.11 network, a MAN-wireless network), a cellular network (e.g., a long term evolution network (L TE)), a frame relay network, a Virtual Private Network (VPN), a satellite network, a telephone network, a router, a hub, a switch, a MAN-computing server, or combinations thereof. as examples only, the network 120 may include a PSTN, a public switched access Network (NFC), a wireless access point (NFC/WLAN), a wireless access point (NFC/wireless access point, a WLAN) or a combination thereof, the Internet may include at least one or a wireless access point (NFC).

The terminal 130 includes a mobile device 131, a tablet computer 132, a notebook computer 133, etc., or any combination thereof. In some embodiments, the terminal 130 may interact with other components in the projection data acquisition system 100 via a network. For example, the terminal 130 may send one or more control instructions to the processing device 110 to control the processing device 110 to emulate according to the instructions. For another example, the terminal 130 may also receive simulation results of the processing device 110, for example, 200 pieces of projection data generated by 200 incident X-rays in different directions through a digital phantom simulating a human body. In some embodiments, mobile device 131 may include a smart-home device, a wearable device, a smart-mobile device, a virtual-reality device, an augmented-reality device, and the like, or any combination thereof. In some embodiments, the smart home devices may include smart lighting devices, control devices for smart appliances, smart monitoring devices, smart televisions, smart cameras, interphones, and the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart footwear, smart glasses, a smart helmet, a smart watch, a smart garment, a smart backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a Personal Digital Assistant (PDA), a gaming device, a navigation device, a point of sale (POS) device, or the like, or any combination thereof. In some embodiments, the virtual reality device may include a virtual reality helmet, virtual reality glasses, virtual reality eyeshields, augmented reality helmets, augmented reality glasses, augmented reality eyeshields, and the like, or any combination thereof. For example, the virtual reality device and/or the augmented reality device may include Google Glass, accumus Rift, Hololens, Gear VR, and the like. In some embodiments, the terminal 130 may operate the processing device 110 remotely. For example, the terminal 130 may operate the processing device 110 through a wireless connection. In some embodiments, the terminal 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 130 may receive data and/or information from the processing device 110. In some embodiments, the terminal 130 may be part of the processing device 110.

Storage device 140 may store data and/or instructions. In some embodiments, the storage device 140 may store data obtained from the processing device 110 and/or the terminal 130, such as energy spectrum data for different X-rays, spatial distribution of attenuation coefficients for rays of different energy levels from a digital phantom, geometric parameters of a digital phantom, coordinate point data, simulated projection data, and so forth. In some embodiments, the storage device 140 may store data and/or instructions that the processing device 110 may execute or perform the exemplary methods described in this disclosure. In some embodiments, storage device 140 may include mass storage, removable storage, volatile read-write memory, read-only memory (ROM), etc., or any combination thereof. Exemplary mass storage devices may include magnetic disks, optical disks, solid state drives, and the like. Exemplary removable memory may include flash memory disks, floppy disks, optical disks, memory cards, compact disks, magnetic tape, and the like. Exemplary volatile read and write memories can include Random Access Memory (RAM). Exemplary RAM may include Dynamic RAM (DRAM), Double Data Rate Synchronous Dynamic RAM (DDRSDRAM), Static RAM (SRAM), thyristor RAM (T-RAM), zero capacitance RAM (Z-RAM), and the like. Exemplary ROMs may include Mask ROM (MROM), Programmable ROM (PROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), compact disk ROM (CD-ROM), digital versatile disk ROM, and the like. In some embodiments, the storage device 140 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, across clouds, multiple clouds, the like, or any combination thereof.

In some embodiments, the storage device 140 may be connected to the network 120 for communication with at least one component of the projection data acquisition system 100 (e.g., the processing device 110 or the terminal 130). At least one component of the projection data acquisition system 100 may access 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 in communication with at least one component of the projection data acquisition system 100 (e.g., the processing device 110 or the terminal 130). In some embodiments, the storage device 140 may be part of the processing device 110.

FIG. 2 is a block diagram of an X-ray projection data acquisition system according to some embodiments of the present application.

As shown in fig. 2, the X-ray projection data acquisition system may include a spectrum determination module 210, a beamlet determination module 220, a path determination module 230, a path integral acquisition module 240, a projection data determination module 250, and a projection value determination module 260.

The energy spectrum determination module 210 may be used to determine the energy spectrum of the incident X-rays; the energy spectrum reflects the number of photons of different energies in the incident X-ray. For a detailed description of the determination of the energy spectrum of the incident X-rays, reference is made to fig. 3, which is not described in detail here.

The beamlet determination module 220 may be configured to determine beamlets of two or more different energies in the incident X-rays based on the energy spectrum. For a detailed description of determining two or more sub-beams of different energies in the incident X-ray based on the energy spectrum, reference may be made to fig. 3, which is not described herein again.

The path determination module 230 may be configured to determine one or more paths of the incident X-rays through the digital phantom. For a detailed description of determining one or more paths of the incident X-rays through the digital phantom, reference is made to fig. 3, which is not repeated here.

The path integral obtaining module 240 may be configured to obtain path integrals of attenuation coefficients corresponding to different beamlets under the path based on spatial distribution of attenuation coefficients of the digital phantom for different beamlets. For the spatial distribution of the attenuation coefficients of different sub-beams based on the digital phantom, the detailed description of obtaining the path integrals of the attenuation coefficients corresponding to the different sub-beams in the path can be referred to fig. 3, which is not described herein again.

The projection data determination module 250 may be configured to determine projection data of the incident X-rays traversing the digital phantom via a path based on an integral of the incident energy of each beamlet and an attenuation coefficient corresponding thereto. For a detailed description of determining projection data of the incident X-ray passing through the digital phantom via the path based on the path integrals of the incident energy of each beamlet and the attenuation coefficient corresponding thereto, refer to fig. 3, which is not repeated herein.

The projection value determination module 260 may be configured to, for either path: determining a sum of attenuation coefficients of the digital phantom on the path for reconstruction based on the incident energy of each beamlet and projection data of the incident X-rays traversing the digital phantom on the path. For a detailed description of determining the projection value of the digital phantom on the path based on the incident energy of each beamlet and the projection data of the incident X-ray passing through the digital phantom via the path, refer to fig. 3, which is not repeated herein.

It should be understood that the system and its modules shown in FIG. 2 may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory for execution by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided, for example, on a carrier medium such as a diskette, CD-or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules in this specification may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).

It should be noted that the above description of the system for acquiring X-ray projection data and the modules thereof is merely for convenience of description and should not be construed as limiting the scope of the present disclosure to the illustrated embodiments. It will be appreciated by those skilled in the art that, given the teachings of the present system, any combination of modules or sub-system configurations may be used to connect to other modules without departing from such teachings. For example, in some embodiments, for example, the energy spectrum determination module 210, the beamlet determination module 220, the path determination module 230, the path integral acquisition module 240, and the projection data determination module 250 disclosed in fig. 2 may be different modules in a system, or may be a module that implements the functions of two or more of the above modules. For example, the path determining module 230 and the path integral acquiring module 240 may be two modules, or one module may have both the functions of determining a path and acquiring a path integral of an attenuation coefficient. Such variations are within the scope of the present disclosure.

FIG. 3 is an exemplary flow chart of a method of acquiring X-ray projection data according to some embodiments of the present application.

In some embodiments, flow 300 may be performed by processing logic that may comprise hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (instructions run on a processing device to perform hardware simulation), etc., or any combination thereof. One or more steps of the process 300 for acquiring projection data shown in fig. 3 may be implemented in the system 100 shown in fig. 1. For example, one or more steps in flow 300 may be stored as instructions in storage device 150 and invoked and/or executed by processing device 110.

At step 310, the energy spectrum of the incident X-rays is determined. In particular, this step may be performed by the energy spectrum determination module 210.

In some embodiments, when scanning with a multi-energy X-ray of a certain kVp, the energy spectrum of the incident X-ray, which may reflect the number of photons of each energy in the X-ray, may be determined from the kVp value (peak kilovoltage). kVp is the unit of the peak tube voltage applied between the cathode and anode of the X-ray tube, measured in kilovolts, which is equal to the maximum photon energy in incident X-rays (in kev, kiloelectron volt). KeV is the energy unit required to accelerate an electron through a 1000v voltage difference and is also used as a photon energy unit. For example, applying a peak tube voltage of 80kVp between the cathode and anode of an X-ray tube can produce a maximum of 80KeV of photon energy in incident X-rays. In some embodiments, after determining that a peak tube voltage of 80kVp is applied between the cathode and the anode of the X-ray tube, the number of photons with energy ranging from 0 to 80KeV in the incident X-ray energy spectrum can be obtained by using a tamip (transition anode specific model) algorithm, and the calculation formula is as follows:

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

wherein, different photon energies (keV) correspond to different coefficients a 0-a 3, a 0-a 3 are generated by a tool and can be obtained by looking up a table. For example, for an incident X-ray with a photon energy of 50keV at 80kVp, the number of photons contained is: a0(50) + a1(50) × 80+ a2(50) × 80^2+ a3(50) × 80^3, a0(50) shows a parameter a0 corresponding to an energy of 50 keV. In the process of simulating projection data, different peak tube voltages can be selected according to requirements, and then the corresponding X-ray energy spectrum is determined.

Step 320, determining two or more sub-beams of different energies in the incident X-rays based on the energy spectrum. In particular, this step may be performed by the beamlet determination module 220.

In some embodiments, two or more beamlets in the incident X-rays and their incident energies may be determined based on the energy spectrum acquired in step 310.

In some embodiments, the energy spectrum may be divided into two or more photon intervals with different energies according to the same energy interval, and the smaller the energy interval for dividing the photon intervals, the closer to the real situation is, so the simulation effect may be better, but the data acquired at the same time may be more, the corresponding calculation amount may be increased, and 1KeV may be generally used as the energy interval. The energy spectrum of the incident X-rays generated with the tube voltage of 80kVp illustrated in step 310 is taken as an example: the energy peak of a photon in the energy spectrum can be determined to be 80KeV, and here 20KeV is taken as an energy interval for convenience of description, the energy spectrum can be divided into 4 photon intervals itl 1-itl 4 as shown in fig. 4. In some embodiments, other ways to divide the photon interval may be used, and are not limited by the description herein. In some embodiments, all photons of the incident X-ray having energy in a photon interval form a beamlet, and thus the photon intervals correspond to beamlets one to one. For example: as shown in fig. 4, beamlet 1 corresponds to photon interval itl1, beamlet 2 corresponds to photon interval itl2, beamlet 3 corresponds to photon interval itl3, and beamlet 4 corresponds to photon interval itl 4.

In some embodiments, the total photon energy for each photon interval may be determined as the incident energy of the beamlet corresponding to each photon interval.

In some embodiments, the energy spectrum determined in step 310 may reflect the number of photons of different energies in the incident X-ray, and therefore, the number of photons in photon intervals itl 1-itl 4 may be determined according to the energy spectrum according to the calculation method in step 310 as: lnum1, lnum2, lnum3 and lnum 4. In still other embodiments, the energy sum of each photon in a photon interval may be calculated according to the energy spectrum, that is, the total energy of each photon is obtained by calculating the product of the energy of each photon in the photon interval and the number of corresponding photons, and then the total energy of each photon is summed to obtain the incident energy of the beamlet corresponding to the photon interval. Since the photon energy reflected by the energy spectrum is continuous, in some embodiments, the product of the equivalent energy of the photon interval and the total number of photons in the photon interval can be used as the total photon energy of the photon interval, and can be used as the incident energy of the beamlet corresponding to the photon interval. In some embodiments, the average energy of a photon interval may be calculated as the equivalent energy of that photon interval. Taking the photon interval itl2 in fig. 4 as an example, the equivalent energy of a photon in the photon interval may be (20+40)/2 ═ 30 (KeV).

Therefore, the incident energy I of the beamlets 1 to 4 as shown in FIG. 4_a～I_dRespectively as follows: lnum1 (0+20)/2, lnum2 (20+40)/2, lnum3 (40+60)/2 and

lnum4*(60+80)/2。

at step 330, one or more paths of the incident X-rays through the digital phantom are determined. In particular, this step may be performed by the path determination module 230.

In some embodiments, a digital phantom may be used to mimic the scanned object, which has a fixed spatial geometry and spatial distribution of attenuation coefficients. The spatial geometry may be represented by a set of two-dimensional (e.g., the digital phantom is an ideal flat plate structure) point coordinates or three-dimensional (e.g., the digital phantom is a three-dimensional structure) point coordinates, and the spatial distribution of the attenuation coefficient may be expressed as the attenuation coefficient corresponding to each point coordinate in the digital phantom. In some embodiments, the digital phantom has different attenuation coefficients for different energies of X-rays. The parameters associated with the digital motifs may be pre-designed and stored in a database (e.g., in the storage device 140).

In some embodiments, in order to acquire projection data of incident X-rays, the incident X-rays need to be passed through a digital phantom. In some embodiments, there may be one or more paths for incident X-rays through the digital phantom. For example, if the person in question needs a projection datum, a path of the incident X-ray through the digital phantom can be determined. As another example, if the associated person requires 100 projection data, then 100 paths of incident X-rays through the digital phantom may be determined. In some embodiments, as shown in FIG. 5A, the coordinates of the X-ray source, the digital phantom, and the analog detector may be determined by an analog coordinate system to determine the relative positions of the three. In some embodiments, the analog detector has one or more analog detection points, for example, the analog detector shown in FIG. 5A has 5 analog detection points. It will be appreciated that in this coordinate system, the coordinates of the X-ray source, each point on the digital phantom, and each analog detection point on the analog detector can be uniquely determined. In some embodiments, a straight line may be drawn from the X-ray source to each of the one or more simulated detection points (the straight line equation may be determined based on the coordinates of the X-ray source and the coordinates of the simulated detection points) to obtain one or more straight lines. The portion of the one or more lines intersecting the digital motif may be taken as one or more paths. For example, if a straight line is drawn from the source to the analog detection site 5, as shown in FIG. 5A, which intersects the digital phantom at points A and B, the straight line between points A and B can be taken as a path.

Step 340, acquiring path integrals of the attenuation coefficients corresponding to the different sub-beams under the path based on the spatial distribution of the attenuation coefficients of the digital phantom for the different sub-beams. In particular, this step may be performed by the path integral acquisition module 240.

In some embodiments, the attenuation coefficients of the digital phantom for different beamlets may be set to be different. For the sake of illustration, it is assumed that the attenuation coefficients of the digital phantom vary only in the xoy plane and do not vary in the z direction. At this time, the spatial distribution of the attenuation coefficient of the digital phantom may be equivalent to a two-dimensional distribution, and as shown in fig. 5B, a section of the digital phantom parallel to the xoy plane may be arbitrarily taken, and the section may be divided into a plurality of grids representing pixels. In some embodiments, the attenuation coefficient of each voxel may be the same for the same beamlet, e.g., the object under examination is a non-biological object such as water, wood, etc. In some embodiments, the attenuation coefficient may be different for each voxel for the same beamlet, e.g., the object under examination is a patient, an animal, etc. In some embodiments, the attenuation coefficients for different beamlets are different for the same voxel. Therefore, the attenuation coefficient corresponding to each voxel can be expressed as μ_ijWherein the first subscript i indicates the number of the beamlet and the second subscript j indicates the number of the voxel, the spatial distribution of attenuation coefficients corresponding to the beamlets 1-4 as shown in fig. 5B can be formed. In some embodiments, the path integral of the attenuation coefficient for a beamlet may be expressed as the sum of the attenuation coefficients of all pixels through which the beamlet passes under a given path. For example, the path integral of the attenuation coefficient corresponding to beamlet 1 as shown in fig. 5B may be expressed as: mu.s₁₁+μ₁₅+μ₁₆+μ₁₇+μ₁₁₁+μ₁₁₂. In some embodiments, the path integral of the attenuation coefficient for a beamlet may be expressed as the sum of the products of the attenuation coefficient for the beamlet for each voxel that the beamlet passes through and the length of each voxel that the incident X-ray passes through at a given path. For example, the length of each pixel through which incident X-rays pass as shown in FIG. 5B may be represented by l_iWhere the index i denotes the number of voxels, the path integral of the corresponding attenuation coefficient can be expressed as: l₁μ₁₁+l₅μ₁₅+l₆μ₁₆+l₇μ₁₇+l₁₁μ₁₁₁+l₁₂μ₁₁₂. In some embodiments, the path integrals of the attenuation coefficients corresponding to the sub-beams may also be expressed in other ways, which are not limited by the description herein. In some embodiments, the attenuation coefficient of each voxel for the respective beamlet may be set manually in accordance with the subject being digitally phantom-simulated, and thus a known parameter. For example: if the subject to be tested is a human body, various organs (for example, bones, blood, liver, etc.) of the human body can be simulated by setting different attenuation coefficients. In some embodiments, the length of each voxel of the digital phantom through which the incident X-ray passes may be determined based on the intersection of the given path with the respective voxel of the digital phantom. As can be seen from step 330, the coordinates of the given path and digital phantom are known, and thus, the length of each voxel of the digital phantom through which the incident X-ray passes can also be calculated as a known parameter. In summary, the path integrals of the attenuation coefficients corresponding to different beamlets under a given path may be obtained based on the spatial distribution of the attenuation coefficients for different beamlets of the digital phantom.

Step 350, determining projection data of the incident X-ray passing through the digital phantom via a path based on the path integral of the incident energy of each beamlet and the attenuation coefficient corresponding thereto. In particular, this step may be performed by the projection data determination module 250.

In some embodiments, projection data for an incident X-ray traversing the digital phantom via a given path may be determined based on the path integrals of the incident energy of each beamlet acquired in step 320 and the attenuation coefficient of each beamlet acquired in step 340. In some embodiments, the projection data may be the energy of the X-rays detected on the detector after the incident X-rays have passed through the subject. In an implementation of the present description, an analog radiation source, a digital phantom, and an analog detector are used to simulate the actual scanning equipment and the object, acquiring projection data. The method comprises the following specific steps:

and (I) calculating the product of the incident energy of each sub-beam and the natural index of the path integral of the attenuation coefficient corresponding to the incident energy of each sub-beam to obtain sub-projection data of each sub-beam passing through the digital phantom through the path. For example, the beamlet 1 shown in FIG. 4 follows the path shown in FIG. 5A through the digital phantom with its corresponding sub-projection data I₁Can be as follows:

wherein, I_aRepresenting the incident energy of the beamlet 1. By analogy, the sub-projection data I corresponding to the sub-beams 2 to 4 can be obtained through calculation₂～I₄。

And (II) superposing the sub-projection data to obtain the projection data of the incident X-ray passing through the digital phantom through the path. In some embodiments, the plurality of sub-projection data acquired in the above step may be added as projection data of an incident X-ray traversing the digital phantom via a given path. For example: the incident X-ray shown in fig. 4 traverses the digital phantom along the path shown in fig. 5A, and the projection data I may be: i is₁+I₂+I₃+I₄。

In some embodiments, for any path of an incident X-ray through a digital phantom, a sum of attenuation coefficients of the digital phantom on that path may be determined for reconstruction based on the incident energy of each beamlet and projection data of the incident X-ray through the digital phantom via that path. In some embodiments, the sum of the incident energies of the beamlets may be calculated as the incident energy of the incident X-ray, and then the incident energy may be summedAnd performing division operation on the projection data acquired in the step, and taking a natural logarithm of the value of the projection data as a projection value of the digital motif on the path. For example: the incident X-ray shown in fig. 4 follows the path shown in fig. 5A through the digital phantom, and the corresponding projection values may be: ln ((I)_a+I_b+I_c+I_d)÷(I₁+I₂+I₃+I₄)). If the sum of the attenuation coefficients (for image reconstruction) that can be obtained using the existing method of computing projection values based on monoenergetic X-rays is: l₁μ₁+l₅μ₅+ l₆μ₆+l₇μ₇+l₁₁μ₁₁+l₁₂μ₁₂Wherein the attenuation coefficient for each pixel in the digital motif is the same for all incident beamlets.

In summary, the projection values calculated by using the projection data acquired by the method described in this specification represent the spatial distribution of the attenuation coefficients of the digital phantom for the sub-beams of different energies, and are closer to the projection values calculated based on the projection data obtained by the actual device.

It should be noted that the above description related to the flow 300 is only for illustration and explanation, and does not limit the applicable scope of the present application. Various modifications and changes to flow 300 will be apparent to those skilled in the art in light of this disclosure. However, such modifications and variations are intended to be within the scope of the present application. For example, step 320 may be split into two steps 320_1 and 320_2, with two or more beamlets in the incident X-rays being determined in step 320_1 and the incident energy of each beamlet being determined in step 320_ 2.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered merely illustrative and not restrictive of the broad application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. 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 places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.

Moreover, those skilled in the art will appreciate that aspects of the present application may be illustrated and described in terms of several patentable species or situations, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereon. Accordingly, various aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for operation of portions of the present application may be written in any one or more programming languages, including AN object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, a conventional programming language such as C, Visual Basic, Fortran 2003, Perl, COBO L2002, PHP, ABAP, a dynamic programming language such as Python, Ruby, and Groovy, or other programming languages, and the like.

Additionally, the order in which elements and sequences of the processes described herein are processed, the use of alphanumeric characters, or the use of other designations, is not intended to limit the order of the processes and methods described herein, unless explicitly claimed. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, 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 all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

The entire contents of each patent, patent application publication, and other material cited in this application, such as articles, books, specifications, publications, documents, and the like, are hereby incorporated by reference into this application. Except where the application is filed in a manner inconsistent or contrary to the present disclosure, and except where the claim is filed in its broadest scope (whether present or later appended to the application) as well. It is noted that the descriptions, definitions and/or use of terms in this application shall control if they are inconsistent or contrary to the statements and/or uses of the present application in the material attached to this application.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present application. Other variations are also possible within the scope of the present application. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the present application can be viewed as being consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to only those embodiments explicitly described and depicted herein.

Claims

1. A method of acquiring X-ray projection data, comprising:

determining an energy spectrum of the incident X-rays; the energy spectrum reflects the number of photons of different energies in the incident X-ray;

determining, based on the energy spectrum, two or more beamlets of different energies in the incident X-rays;

determining one or more paths for the incident X-rays to traverse a digital phantom;

for either path:

acquiring path integrals of attenuation coefficients corresponding to different sub-beams under the path based on the spatial distribution of the attenuation coefficients of the digital die body to the different sub-beams;

determining projection data of the incident X-rays traversing the digital phantom via a path based on an integral of the incident energy of each beamlet and its corresponding attenuation coefficient.

2. The method of claim 1, wherein said determining, based on said energy spectrum, two or more beamlets of different energies in said incident X-rays comprises:

dividing the energy spectrum into two or more photon intervals with different energies, wherein the photon intervals correspond to the sub-beams one to one;

and determining the total photon energy of each photon interval as the incident energy of the sub-beam corresponding to each photon interval.

3. The method of claim 1, wherein determining one or more paths of the incident X-rays through a digital phantom comprises:

determining the relative positions of an X-ray source, a digital mold body and an analog detector; wherein the analog detector has one or more analog detection points thereon;

respectively making a straight line from the X-ray source to one or more simulation detection points to obtain one or more straight lines;

and the part of the one or more straight lines intersected with the digital die body is the one or more paths.

4. The method of claim 1, wherein determining projection data of the incident X-rays traversing the digital phantom via a path based on an integral of the incident energy of each beamlet and an attenuation coefficient corresponding thereto comprises:

calculating the product of the incident energy of each sub-beam and the natural index of the path integral of the attenuation coefficient corresponding to the incident energy of each sub-beam to obtain sub-projection data of each sub-beam passing through the digital phantom through the path;

and superposing the sub-projection data to obtain the projection data of the incident X-ray passing through the digital phantom through the path.

5. The method of claim 1, further comprising, for any path:

determining a sum of attenuation coefficients of the digital phantom on the path for reconstruction based on the incident energy of each beamlet and projection data of the incident X-rays traversing the digital phantom on the path.

6. An acquisition system for X-ray projection data, the system comprising:

the energy spectrum determining module is used for determining the energy spectrum of the incident X-ray; the energy spectrum reflects the number of photons of different energies in the incident X-ray;

a beamlet determination module for determining beamlets of two or more different energies in the incident X-rays based on the energy spectrum;

a path determination module for determining one or more paths for the incident X-rays to traverse the digital phantom;

the path integral acquisition module is used for acquiring path integrals of the attenuation coefficients corresponding to different sub-beams under the path based on the spatial distribution of the attenuation coefficients of the digital die body to different sub-beams;

and the projection data determination module is used for determining the projection data of the incident X-ray passing through the digital phantom through the path based on the path integral of the incident energy of each sub-beam and the attenuation coefficient corresponding to the incident energy.

7. The system of claim 6, wherein the beamlet determination module is further to:

8. The system of claim 6, wherein the path determination module is further to:

9. The system of claim 6, wherein the projection data determination module is further to:

10. The system of claim 6, further comprising:

a projection value determination module to, for any path:

11. An apparatus for acquiring X-ray projection data, comprising a processor, wherein the processor is configured to perform the method for acquiring X-ray projection data according to any one of claims 1 to 5.

12. A computer-readable storage medium storing computer instructions which, when read by a computer, cause the computer to perform the method of acquiring X-ray projection data according to any one of claims 1 to 5.