CN116580115A - Spiral CT image iterative reconstruction method, device and storage medium - Google Patents

Spiral CT image iterative reconstruction method, device and storage medium Download PDF

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CN116580115A
CN116580115A CN202310318406.3A CN202310318406A CN116580115A CN 116580115 A CN116580115 A CN 116580115A CN 202310318406 A CN202310318406 A CN 202310318406A CN 116580115 A CN116580115 A CN 116580115A
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image
field data
data
initial
view field
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CN116580115B (en
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王小燕
张笛儿
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Sanuo Weisheng Medical Technology Yangzhou Co ltd
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Sanuo Weisheng Medical Technology Yangzhou Co ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation
    • G06T11/003Reconstruction from projections, e.g. tomography
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation
    • G06T11/003Reconstruction from projections, e.g. tomography
    • G06T11/008Specific post-processing after tomographic reconstruction, e.g. voxelisation, metal artifact correction

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Abstract

The embodiment of the application discloses a spiral CT image iterative reconstruction method, a device and a storage medium, wherein the spiral CT image iterative reconstruction method comprises the following steps: acquiring initial view field data by using spiral CT scanning; after the initial view field data is divided, the association relationship between the view field data and the corresponding image field data is obtained through an intermediate step; performing back projection operation on at least part of divided initial view field data to obtain an initial image in corresponding image field data, performing iterative reconstruction of intermediate steps, front projection, intermediate steps and back projection processes on the basis of the initial image according to the iterative priority order to obtain an updated image in the corresponding image field data, and sequentially outputting the completely reconstructed initial image and the updated image according to the iterative priority order, wherein the front projection and the back projection are 3D front projection of cone beams based on spiral CT; when the reconstruction of all the images is completed, the final image in the image domain data is output and stored.

Description

Spiral CT image iterative reconstruction method, device and storage medium
Technical Field
The application relates to the technical field of computer information processing, in particular to a spiral CT image iterative reconstruction method, a device and a storage medium.
Background
In recent years, with the continuous increase of processing capacity, iterative reconstruction technology has become a main image reconstruction mode of modern CT scanners. Iterative reconstruction generally reconstructs an image by iteratively optimizing an objective function, typically alternating forward and backward projections between the image domain and the projection data domain, until the objective function is minimized according to a convergence criterion.
However, the existing spiral reconstruction method has more artifacts, which results in low reconstructed image quality.
Disclosure of Invention
The embodiment of the application aims to provide a spiral CT image iterative reconstruction method, a device and a storage medium, which are used for solving the problem of low reconstructed image quality caused by more artifacts in the spiral reconstruction method in the prior art.
To achieve the above object, an embodiment of the present application provides a spiral CT image iterative reconstruction method, including: acquiring initial view field data by using spiral CT scanning;
after the initial view field data is divided, the association relationship between the view field data and the corresponding image field data is acquired through an intermediate step so as to identify the reconstructed image range of the view field;
performing back projection operation on at least part of the divided initial view field data to obtain an initial image in corresponding image field data, performing iterative reconstruction of intermediate steps, front projection, intermediate steps and back projection processes on the basis of the initial image according to an iterative priority order to obtain an updated image in corresponding image field data, and sequentially outputting the initial image and the updated image which are completely reconstructed according to the iterative priority order, wherein the front projection and the back projection are 3D front projection of cone beams based on spiral CT;
when the reconstruction of all the images is completed, the final image in the image domain data is output and stored.
Optionally, in the back projection, the image domain data is affected by view domain data, the view domain data being back projected onto an associated number of images in the image domain data;
in orthographic projection, view field data is affected by image field data, with several images in the image field data being orthographically projected onto the associated view field data.
Optionally, before sequentially outputting the initial image and the updated image which have been completely reconstructed according to the iteration priority order, the method further includes:
and judging whether the back projection of all view field data associated with the current image in the image field data is finished, and if so, outputting the initial image or the updated image which is completely reconstructed.
Optionally, the obtaining the initial image in the corresponding image domain data, based on the initial image according to the iteration priority order, performing iterative reconstruction of the flow of the intermediate step, the front projection, the intermediate step and the back projection to obtain the updated image in the corresponding image domain data, including:
at node 0, for set V in the initial view field data 1 Back-projection operation is performed on the data of (1) and is superimposed on the set G of image domain 0 in the image domain data 1 On, i.e. G 1 =G(V 1 ) And so on, at node 0, the loop progresses to set V i
When first appears on image field 0When a set G of the initial images on the image domain 0 is obtained 1 At node 1, the set G of the initial images on image field 0 1 Through the intermediate step processing, the orthographic projection operation is carried out to obtain an orthographic projection data set V on the view field 1 1 After the intermediate step treatment, the set V on the view field 1 1 Back projection operation is performed and superimposed on the set G of image fields 1 1 On, i.e. G 1 =G(V 1 );
When first appears on image field 1When a set G of the initial images on the image domain 0 is obtained 2
Priority back to node 1, node 1 repeats the foregoing operations for set G of image domain 1 2 Performing an image-domain inter-step, forward projection, view-domain inter-step, back projection, and superimposing onto the set G of image domains 1 2 On, when appearing on image field 1A kind of electronic device with a high-pressure air-conditioning systemWhen a set G of said updated images on image domain 1 is obtained, which has been completely reconstructed 1
And by analogy, recursively pushing the image to the node m according to the iteration priority order to obtain the final image which is completely reconstructed on the image domain m.
Optionally, for nodes k < m, set V over view field k i And the processing is released after the processing is completed, so that the memory space is saved.
Optionally, before the initial view field data is acquired by using a spiral CT scan, the method further includes: setting scanning parameters and reconstruction parameters to obtain pitch information.
In order to achieve the above object, the present application further provides a spiral CT image iterative reconstruction apparatus, including:
the scanning module is used for acquiring initial view field data by utilizing spiral CT scanning;
the data processing module is connected with the scanning module and is used for dividing the initial view field data and outputting the divided data in batches after acquiring the initial view field data sent by the scanning module;
the algorithm module is connected with the data processing module and used for acquiring the initial view field data sent by the data processing module in batches, acquiring the association relationship between the view field data and the corresponding image field data through an intermediate step so as to identify the reconstruction image range of the view field,
performing back projection operation on at least part of the divided initial view field data to obtain an initial image in the corresponding image field data, performing iterative reconstruction of intermediate steps, front projection, intermediate steps and back projection processes based on the initial image according to the iterative priority order to obtain an updated image in the corresponding image field data, and sequentially outputting the initial image and the updated image which are completely reconstructed according to the iterative priority order, wherein the front projection and the back projection are 3D front projection based on cone beams of spiral CT,
when the reconstruction of all the images is completed, the final image in the image domain data is output and stored.
To achieve the above object, the present application also provides a computer storage medium having stored thereon a computer program which, when executed by a machine, implements the steps of the method as described above.
The embodiment of the application has the following advantages:
the embodiment of the application provides a spiral CT image iterative reconstruction method, which comprises the following steps: acquiring initial view field data by using spiral CT scanning; after the initial view field data is divided, the association relationship between the view field data and the corresponding image field data is acquired through an intermediate step so as to identify the reconstructed image range of the view field; performing back projection operation on at least part of the divided initial view field data to obtain an initial image in corresponding image field data, performing iterative reconstruction of intermediate steps, front projection, intermediate steps and back projection processes on the basis of the initial image according to an iterative priority order to obtain an updated image in corresponding image field data, and sequentially outputting the initial image and the updated image which are completely reconstructed according to the iterative priority order, wherein the front projection and the back projection are 3D front projection of cone beams based on spiral CT; when the reconstruction of all the images is completed, the final image in the image domain data is output and stored.
By the method, the front projection and the back projection are both iterative reconstruction methods of 3D cone beam geometry, so that common artifacts in spiral reconstruction such as windmill artifacts can be reduced, and the image quality is improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those skilled in the art from this disclosure that the drawings described below are merely exemplary and that other embodiments may be derived from the drawings provided without undue effort.
FIG. 1 is a flowchart of a spiral CT image iterative reconstruction method provided by an embodiment of the present application;
fig. 2 is an overall logic schematic diagram of a spiral CT image iterative reconstruction method according to an embodiment of the present application;
fig. 3 is a schematic diagram of a spiral scanning principle of a spiral CT image iterative reconstruction method according to an embodiment of the present application;
fig. 4 is a schematic diagram of association between view domain data and image domain data in a spiral CT image iterative reconstruction method according to an embodiment of the present application;
fig. 5 is an iteration reconstruction priority schematic diagram of a spiral CT image iteration reconstruction method according to an embodiment of the present application;
FIG. 6a is a left half of an iterative reconstruction flow chart of a helical CT image iterative reconstruction method according to an embodiment of the present application;
fig. 6b is a right half of an iterative reconstruction flow chart of a spiral CT image iterative reconstruction method according to an embodiment of the present application;
fig. 7 is a block diagram of a spiral CT image iterative reconstruction device according to an embodiment of the present application.
Detailed Description
Other advantages and advantages of the present application will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the technical features of the different embodiments of the present application described below may be combined with each other as long as they do not collide with each other.
An embodiment of the present application provides a spiral CT image iterative reconstruction method, referring to fig. 1 and 2, fig. 1 is a flowchart of a spiral CT image iterative reconstruction method provided in an embodiment of the present application, and fig. 2 is an overall logic schematic diagram of a spiral CT image iterative reconstruction method provided in an embodiment of the present application, it should be understood that the method may further include additional blocks not shown and/or may omit the blocks shown, and the scope of the present application is not limited in this respect. The method comprises the following steps:
at step 101, initial view field data is acquired using a helical CT scan.
Specifically, referring to fig. 3, the helical scanning principle: after the scanning starts, the die body or the human body moves along the z direction along with the uniform speed of the scanning bed, and the scanning frame continuously rotates around the scanning bed until the scanning is finished. During the whole scanning process, the X-rays are continuously released by the ray source, the projection data are collected by the detector and returned along the channel, and the obtained information is continuous. The movement track of the ray source on the scanning frame relative to the die body or the human body is approximately a spiral line.
In some embodiments, prior to acquiring the initial view field data using a helical CT scan, further comprising: setting scanning parameters and reconstruction parameters to obtain pitch information.
Specifically, scanning is started, scanning parameters and reconstruction parameters are set, and information such as pitch and the like is obtained; and after the setting is finished, the scanning module works to acquire the initial view field data.
At step 102, after the initial view field data is divided, an association relationship between the view field data and the corresponding image field data is obtained through an intermediate step, so as to identify a reconstructed image range of the view field.
At step 103, performing back projection operation on at least part of the divided initial view field data to obtain an initial image in the corresponding image field data, performing iterative reconstruction of the processes of intermediate step, front projection, intermediate step and back projection based on the initial image according to the iterative priority order to obtain an updated image in the corresponding image field data, and sequentially outputting the initial image and the updated image which are completely reconstructed according to the iterative priority order, wherein the front projection and the back projection are 3D front projection of cone beams based on spiral CT.
At step 104, when the reconstruction of all images is completed, the final image in the image domain data is output and stored.
Specifically, the iterative reconstruction algorithm can be briefly expressed as: the method comprises the steps that after an initial image obtained after back projection operation is carried out on initial view field data is processed through a plurality of intermediate steps, view field data is obtained through front projection, after the view field data is processed through a plurality of intermediate steps, an updated image is obtained through back projection, and the process is an iteration step; and obtaining a final image after multi-step updating through the repeated iteration steps. The spiral 3D cone beam iterative reconstruction is characterized in that the front projection geometry and the back projection geometry in each iteration are consistent with the actual system geometry, namely the 3D front projection of the cone beam of the spiral CT.
Intermediate steps including "several intermediate steps" of the image and view domains, which are different due to the different kinds of iterative reconstruction algorithms and different computational formats, are not the scope of the present discussion. The iterative process related by the application is applicable to all iterative reconstruction algorithms following the intermediate step-orthographic projection-intermediate step-backprojection process described above.
Association of view field data with image field data referring to fig. 4, fig. 4 shows the association of view field data with image field data. The view field data are arranged according to sampling views to form a view field data sequence; the image domain data are arranged according to the number of images to form an image sequence. The left diagram shows a sequence of images associated with a view in a sequence of view data, e.g. data of a sample view (t) is associated with the n1 st to n2 nd images; the right image shows view field data associated with a certain image in the image sequence, e.g. view field data of (being influenced by) a certain image n for the (t 1) th to (t 2) th samples. The above-mentioned association relation is symmetrical to the front projection and back projection. In back projection, the association relationship means that the image domain data is affected by the view domain data, and in front projection, the association relationship means that the view domain data is affected by the image domain data.
The view field data of one sample view can affect multiple images (left side of fig. 4), and when the images are reconstructed by back projection, the view field data of one sample view needs to be back projected onto the associated multiple images. Also because an image is associated with view field data of multiple views (right side of fig. 4), a complete back projection reconstruction is completed for that image only if the back projection of all associated view field data for that image is completed.
Let us call the image sequence associated with view field data view (t) set G (t) = { n }, and the view field data sequence associated with the nth image set V (n), then there are:
V(n)={t;n∈G(t)}
(1)
for a segment of view field data sequence [ t1 t2], the image sequence associated therewith is a set of:
(2)
it is also possible to define a set of view field data sequences associated with a segment of the image sequence n1, n2,
(3)
it is not difficult to find:
(4)
in some embodiments, the obtaining the initial image in the corresponding image domain data, performing iterative reconstruction of the flow of the intermediate step, the front projection, the intermediate step and the back projection according to the iteration priority order based on the initial image to obtain the updated image in the corresponding image domain data, including:
at node 0, for set V in the initial view field data 1 Back-projection operation is performed on the data of (1) and is superimposed on the set G of image domain 0 in the image domain data 1 On, i.e. G 1 =G(V 1 ) And so on, at node 0, the cycle is followedThe ring progresses to set V i
When first appears on image field 0When a set G of the initial images on the image domain 0 is obtained 1 At node 1, the set G of the initial images on image field 0 1 Through the intermediate step processing, the orthographic projection operation is carried out to obtain an orthographic projection data set V on the view field 1 1 After the intermediate step treatment, the set V on the view field 1 1 Back projection operation is performed and superimposed on the set G of image fields 1 1 On, i.e. G 1 =G(V 1 );
When first appears on image field 1When a set G of the initial images on the image domain 0 is obtained 2
Priority back to node 1, node 1 repeats the foregoing operations for set G of image domain 1 2 Performing an image-domain inter-step, forward projection, view-domain inter-step, back projection, and superimposing onto the set G of image domains 1 2 On the image field 1When a set G of said updated images on image domain 1 is obtained, which has been completely reconstructed 1
And by analogy, recursively pushing the image to the node m according to the iteration priority order to obtain the final image which is completely reconstructed on the image domain m.
Specifically, referring to fig. 5, as shown in fig. 5, we consider the iterative process as m+1 nodes operating on data in turn, m being the number of iterations. The node 0 performs back projection operation on the initial view field data (i.e. corrected raw data) to obtain an initial image, and the nodes 1 to m perform front projection, back projection calculation and some intermediate steps on the image according to the priority order to obtain an updated image of each iteration step.
We divide the data sequence of the initial view field (view field 0) into several segments in order, V 1 V 2 V 3 .. each segment consists of a certain number of views (e.g. 1000 views). In fig. 5 we represent the set of these data sequences with solid line squares.
Node 0 begins working first, will pair set V 1 Back-projection operation is performed on the data of (2) and is superimposed on the set G of the image field 0 1 =G(V 1 ) And (3) upper part. In fig. 5, we use dashed arrows to represent the association of view field data with image fields in these operations. Note that at this point image set G 1 The image in the image is not reconstructed for the first time, because part of the image is also reconstructed with V 2 Associated, possibly even with V 3 Etc. more view field data associations. Node 0 will then aggregate V 2 Back projection operation is carried out on the data of the image set G 2 =G(V 2 ) And (3) upper part. And so on, loop progresses to set V i Until the first occurrenceIn the case of (2), this means that all are in contact with G 1 G, finishing processing the view field data related to the images in the image 1 The image in the image is completely reconstructed from the initial image, and the node 0 already processes the i-section initial view field data.
When the above situation occurs (i.e. first occurs on image field 0)In the case of (2) node 1 starts working and sets G on image domain 0 1 After the processing of the step between the image fields, the orthographic projection operation is carried out to obtain an orthographic projection data set V on the view field 1 1 . In fig. 5 we represent the set of these view field data sequences obtained by orthographic computation by a dashed square. Then the V is processed by the inter-view domain step, and then the V just obtained 1 Back projection operation is performed and superimposed on the set G of image fields 1 1 =G(V 1 ) And (3) upper part. Node 1 then pausesStopping running, returning to the node 0, and continuing back projection of the (i+1) th segment view field data by the node 0, and repeating the steps until the +.>In the case of (1), set G on image field 0 2 Has completed, and the priority is returned to node 1. Node 1 repeats the foregoing operation for set G of image fields 1 2 Performs an "image-domain-intermediate step", forward projection, a "view-domain-intermediate step", back projection, and superimposes onto the set G of image domains 1 2 =G(V 2 ) And (3) upper part. And so on, the loop progresses until +_appears on image field 1 as well>In the case of (1), at which time the priority is recursively drawn to node 2, node 2 pairs set G on image domain 1 1 Performs an "image-domain-intermediate step", forward projection, a "view-domain-intermediate step", back projection, and superimposes onto the set G of image domains 2 1 =G(V 1 ) And (3) upper part. And the like until all nodes complete the operation of all data, and the image domain m is the final output result.
In summary, each node k superimposes the backprojection result onto the image field k where it is located, and other nodes except the 0 th node obtain the orthographic projection data from the image field k-1. When the image field k first appears In the case of (2), the (k+1) th node starts to operate and sets G on the image field k j Do the "image-in-field step", forward projection, "view-in-field step", back projection, and superimpose onto the set G of image fields k+1 j =G(V j ) And (3) upper part.
The flow chart of the above method refers to fig. 6a and 6b. An important feature of the above procedure is that the intersection of adjacent sets over all image fields is not emptyThe collection of the liquid-liquid mixture is carried out,the intersection of adjacent sets on all view fields is an empty set,
in some embodiments, for nodes k < m, set V over view field k i And the processing is released after the processing is completed, so that the memory space is saved.
Specifically, memory and buffer management: for node 0, set V is processed i Thereafter, set V on view field 0 i Can be released. To node K>0, set V over view field k i The data is in a temporary intermediate state, represented by the dashed square in fig. 5. The data do not need to actually occupy memory, but rather the intermediate variable of each operation can repeatedly use the buffer space with fixed size, and even only the buffer space with single view size is enough. Image field k<After the ith section of data is processed by the node k, the image on m is the front part, namely { n;j>the image of the i } portion can be released. The image on image field m is the final output result and is not releasable. In summary, the iterative process only needs to save the intermediate data of a plurality of image domains, and hardly needs to save the view domain data. The above-described flow design is advantageous in saving memory space because the scale of the image domain data is much smaller than the scale of the view domain data.
By the method, a reconstruction workflow suitable for a 3D spiral iteration reconstruction method with both front projection and back projection being 3D cone beam geometry is provided. The advantages are that:
1. the front projection and the back projection are iterative reconstruction methods of 3D cone beam geometry, so that common artifacts in spiral reconstruction such as windmill artifacts can be reduced, and the image quality is improved.
2. The method solves the problem of complex association between the image and the projection data in the method, and has clear and efficient reconstruction algorithm flow and less occupied memory.
3. The reconstruction speed of the first image is ensured, the priority of the image which is more forward is ensured to be higher, and the use habit of a user is met.
Fig. 7 is a block diagram of a spiral CT image iterative reconstruction device according to an embodiment of the present application. The device comprises:
a scanning module 201, configured to acquire initial view field data by using spiral CT scanning;
the data processing module 202 is connected with the scanning module 201, and is configured to divide the initial view field data and output the divided data in batches after acquiring the initial view field data sent by the scanning module 201;
an algorithm module 203, coupled to the data processing module 202, for obtaining the initial view field data sent by the data processing module 202 in batches, obtaining association between the view field data and the corresponding image field data through an intermediate step, so as to identify a reconstructed image range of the view field,
performing back projection operation on at least part of the divided initial view field data to obtain an initial image in the corresponding image field data, performing iterative reconstruction of intermediate steps, front projection, intermediate steps and back projection processes based on the initial image according to the iterative priority order to obtain an updated image in the corresponding image field data, and sequentially outputting the initial image and the updated image which are completely reconstructed according to the iterative priority order, wherein the front projection and the back projection are 3D front projection based on cone beams of spiral CT,
when the reconstruction of all the images is completed, the final image in the image domain data is output and stored.
In some embodiments, the algorithm module 203 specifically includes:
in back projection, the image domain data is affected by view domain data, which is back projected onto a number of images associated in the image domain data;
in orthographic projection, view field data is affected by image field data, with several images in the image field data being orthographically projected onto the associated view field data.
In some embodiments, the algorithm module 203 specifically includes:
before sequentially outputting the initial image and the updated image which are completely reconstructed according to the iteration priority order, judging whether the back projection of all view field data associated with the current image in the image field data is completed or not, and if yes, outputting the initial image or the updated image which are completely reconstructed.
Reference is made to the foregoing method embodiments for specific implementation methods, and details are not repeated here.
The present application may be a method, apparatus, system, and/or computer program product. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for performing various aspects of the present application.
The computer readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.
The computer readable program instructions described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device.
Computer program instructions for carrying out operations of the present application may be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, c++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may be executed 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 case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present application are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information for computer readable program instructions, which can execute the computer readable program instructions.
Various aspects of the present application are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium having the instructions stored therein includes an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Note that all features disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic set of equivalent or similar features. Where used, further, preferably, still further and preferably, the brief description of the other embodiment is provided on the basis of the foregoing embodiment, and further, preferably, further or more preferably, the combination of the contents of the rear band with the foregoing embodiment is provided as a complete construct of the other embodiment. A further embodiment is composed of several further, preferably, still further or preferably arrangements of the strips after the same embodiment, which may be combined arbitrarily.
While the application has been described in detail in the foregoing general description and specific examples, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the application and are intended to be within the scope of the application as claimed.

Claims (10)

1. A spiral CT image iterative reconstruction method, comprising:
acquiring initial view field data by using spiral CT scanning;
after the initial view field data is divided, the association relationship between the view field data and the corresponding image field data is acquired through an intermediate step so as to identify the reconstructed image range of the view field;
performing back projection operation on at least part of the divided initial view field data to obtain an initial image in corresponding image field data, performing iterative reconstruction of intermediate steps, front projection, intermediate steps and back projection processes on the basis of the initial image according to an iterative priority order to obtain an updated image in corresponding image field data, and sequentially outputting the initial image and the updated image which are completely reconstructed according to the iterative priority order, wherein the front projection and the back projection are 3D front projection of cone beams based on spiral CT;
when the reconstruction of all the images is completed, the final image in the image domain data is output and stored.
2. The helical CT image iterative reconstruction method of claim 1, comprising:
in back projection, the image domain data is affected by view domain data, which is back projected onto a number of images associated in the image domain data;
in orthographic projection, view field data is affected by image field data, with several images in the image field data being orthographically projected onto the associated view field data.
3. The helical CT image iterative reconstruction method according to claim 1, further comprising, before sequentially outputting the initial image and the updated image that have been completely reconstructed in the iterative priority order:
and judging whether the back projection of all view field data associated with the current image in the image field data is finished, and if so, outputting the initial image or the updated image which is completely reconstructed.
4. The method according to claim 1, wherein the obtaining the initial image in the corresponding image domain data, performing iterative reconstruction of the flow of the intermediate step, the forward projection, the intermediate step and the backward projection based on the initial image according to the iteration priority order, to obtain the updated image in the corresponding image domain data, includes:
at node 0, for set V in the initial view field data 1 Back-projection operation is performed on the data of (1) and is superimposed on the set G of image domain 0 in the image domain data 1 On, i.e. G 1 =G(V 1 ) And so on, at node 0, the loop progresses to set V i
When first appears on image field 0When a set G of the initial images on the image domain 0 is obtained 1 At node 1, the set G of the initial images on image field 0 1 Through the intermediate step processing, the orthographic projection operation is carried out to obtain an orthographic projection data set V on the view field 1 1 After the intermediate step treatment, the set V on the view field 1 1 Back projection operation is performed and superimposed on the set G of image fields 1 1 On, i.e. G 1 =G(V 1 );
When first appears on image field 1When a set G of the initial images on the image domain 0 is obtained 2
Priority back to node 1, node 1 repeats the foregoing operations for set G of image domain 1 2 Performing an image-domain inter-step, forward projection, view-domain inter-step, back projection, and superimposing onto the set G of image domains 1 2 On the image field 1When a set G of said updated images on image domain 1 is obtained, which has been completely reconstructed 1
And by analogy, recursively pushing the image to the node m according to the iteration priority order to obtain the final image which is completely reconstructed on the image domain m.
5. The helical CT image iterative reconstruction method of claim 4, comprising:
for nodes k < m, set V over view field k i And the processing is released after the processing is completed, so that the memory space is saved.
6. The iterative reconstruction method of helical CT images according to claim 1, wherein,
before acquiring the initial view field data by using the spiral CT scan, the method further comprises: setting scanning parameters and reconstruction parameters to obtain pitch information.
7. A spiral CT image iterative reconstruction apparatus, comprising:
the scanning module is used for acquiring initial view field data by utilizing spiral CT scanning;
the data processing module is connected with the scanning module and is used for dividing the initial view field data and outputting the divided data in batches after acquiring the initial view field data sent by the scanning module;
the algorithm module is connected with the data processing module and used for acquiring the initial view field data sent by the data processing module in batches, acquiring the association relationship between the view field data and the corresponding image field data through an intermediate step so as to identify the reconstruction image range of the view field,
performing back projection operation on at least part of the divided initial view field data to obtain an initial image in the corresponding image field data, performing iterative reconstruction of intermediate steps, front projection, intermediate steps and back projection processes based on the initial image according to the iterative priority order to obtain an updated image in the corresponding image field data, and sequentially outputting the initial image and the updated image which are completely reconstructed according to the iterative priority order, wherein the front projection and the back projection are 3D front projection based on cone beams of spiral CT,
when the reconstruction of all the images is completed, the final image in the image domain data is output and stored.
8. The spiral CT image iterative reconstruction apparatus of claim 7, wherein the algorithm module specifically comprises:
in back projection, the image domain data is affected by view domain data, which is back projected onto a number of images associated in the image domain data;
in orthographic projection, view field data is affected by image field data, with several images in the image field data being orthographically projected onto the associated view field data.
9. The spiral CT image iterative reconstruction apparatus of claim 7, wherein the algorithm module specifically comprises:
before sequentially outputting the initial image and the updated image which are completely reconstructed according to the iteration priority order, judging whether the back projection of all view field data associated with the current image in the image field data is completed or not, and if yes, outputting the initial image or the updated image which are completely reconstructed.
10. A computer storage medium having stored thereon a computer program, which when executed by a machine performs the steps of the method according to any of claims 1 to 6.
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