CN111127581A - Image reconstruction method and device, CT (computed tomography) equipment and CT system - Google Patents
Image reconstruction method and device, CT (computed tomography) equipment and CT system Download PDFInfo
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- 238000007781 pre-processing Methods 0.000 claims description 53
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Abstract
The embodiment of the invention provides an image reconstruction method and device, CT equipment and a CT system. According to the embodiment of the invention, at least two sets of image construction parameter values required by CT image reconstruction are obtained in one image construction process, image construction pretreatment is carried out on CT scanning data to obtain pretreatment output data, image reconstruction is carried out on the pretreatment output data according to each set of image construction parameter values to obtain a plurality of reconstructed image sequences, each reconstructed image sequence corresponds to one set of image construction parameter value, and a plurality of sets of image construction parameter values share one image construction pretreatment process, so that the image construction time is reduced, and the image construction efficiency is improved.
Description
Technical Field
The invention relates to the technical field of medical image processing, in particular to an image reconstruction method and device, CT equipment and a CT system.
Background
CT (Computed Tomography) image reconstruction is a process of performing mathematical operation on CT scan data according to a certain algorithm, solving pixels in an image matrix, and then reconstructing an image. The imaging parameters are parameters used when constructing the image. By adopting different reconstruction parameter values, CT reconstructed images with different visual effects can be obtained.
In the related art, when the same group of CT scan data needs to be reconstructed by using different image-building parameter values, image building is performed for each group of reconstruction parameter values separately, image building needs to be performed for many times, the time consumption is long, and the image building efficiency is low.
Disclosure of Invention
In order to overcome the problems in the related art, the invention provides an image reconstruction method, an image reconstruction device, CT equipment and a CT system, and the image reconstruction efficiency is improved.
According to a first aspect of embodiments of the present invention, there is provided an image reconstruction method, including:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
According to a second aspect of embodiments of the present invention, there is provided an image reconstruction apparatus including:
the acquisition module is used for acquiring at least two sets of image construction parameter values required by CT image reconstruction in the process of image construction for one time;
the preprocessing module is used for carrying out image construction preprocessing on the CT scanning data to obtain preprocessing output data;
and the reconstruction module is used for constructing images based on the preprocessing output data respectively according to each set of image construction parameter values in the at least two sets of image construction parameter values to obtain a plurality of reconstructed image sequences, and each reconstructed image sequence corresponds to one set of image construction parameter values.
According to a third aspect of embodiments of the present invention, there is provided a CT apparatus including: the system comprises an internal bus, a memory, a processor and an external interface which are connected through the internal bus; the external interface is used for connecting a detector of the CT system, and the detector comprises a plurality of detector chambers and corresponding processing circuits;
the memory is used for storing machine readable instructions corresponding to control logic of image reconstruction;
the processor is configured to read the machine-readable instructions on the memory and perform the following operations:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
According to a fourth aspect of the embodiments of the present invention, there is provided a CT system, comprising a detector, a scanning bed and a CT apparatus, the detector comprising a plurality of detector chambers and corresponding processing circuitry; wherein:
the detector chamber is used for detecting X-rays passing through a scanned object and converting the X-rays into electric signals in the scanning process of the CT system;
the processing circuit is used for converting the electric signal into a pulse signal and acquiring energy information of the pulse signal;
the CT device is used for:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
According to a fifth aspect of embodiments of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, wherein the program when executed by a processor implements the operations of:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
according to the embodiment of the invention, at least two sets of image construction parameter values required by CT image reconstruction are obtained in one image construction process, image construction pretreatment is carried out on CT scanning data to obtain pretreatment output data, image reconstruction is carried out on the pretreatment output data according to each set of image construction parameter values to obtain a plurality of reconstructed image sequences, each reconstructed image sequence corresponds to one set of image construction parameter value, and a plurality of sets of image construction parameter values share one image construction pretreatment process, so that the image construction time is reduced, and the image construction efficiency is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the specification.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present specification and together with the description, serve to explain the principles of the specification.
Fig. 1 is a schematic diagram of a process of convolving a convolution kernel with an input image matrix according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating an image reconstruction method according to an embodiment of the present invention.
Fig. 3 is a functional block diagram of an image reconstruction apparatus according to an embodiment of the present invention.
Fig. 4 is a hardware configuration diagram of a CT apparatus according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of embodiments of the invention, as detailed in the following claims.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of embodiments of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used to describe various information in embodiments of the present invention, the information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, the first information may also be referred to as second information, and similarly, the second information may also be referred to as first information, without departing from the scope of embodiments of the present invention. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
The CT reconstruction process can be divided into three phases: the first stage is a process of performing pre-processing of image construction (i.e. the above mathematical operation processing) on CT scan data (also called raw data) acquired by CT scan, wherein the pre-processing of image construction is used for processing the CT scan data into pre-processing output data; the second stage is a process of processing the pre-processing output data by using the image construction parameters to obtain intermediate data of the image construction; the third stage is the process of constructing an image from the intermediate data.
The pre-imaging processing refers to a series of processing on CT scan data before processing using imaging parameters.
Wherein, the imaging parameter may be a convolution kernel. Fig. 1 shows the process of convolving a convolution kernel with a matrix of input images (denoted as the first image from the left in fig. 1, this image being referred to as the input image). In fig. 1, the original pixels are pixels in the input image, the target pixels (also referred to as new pixels) are pixels in the convolved output image (the third image from the left in fig. 1, which may also be referred to as an image matrix, which is referred to as an output image matrix), and the second image from the left in fig. 1 is a convolution kernel. Each pixel in the output image is a weighted average of the pixels in a small region of the input image, where the weights are defined by a function called a convolution kernel.
Currently, the imaging parameters may be other parameters besides convolution kernels. The embodiment of the invention does not limit the specific form or kind of the imaging parameter.
Since the data volume of the CT scan data is relatively large, the time required for pre-imaging processing of the CT scan data is also relatively long. In the related art, each image building needs to perform image building preprocessing on CT scan data, for example, n (n is a natural number) image building parameters need to perform image building n times, and n image building preprocessing processes are required, which takes a lot of time. Moreover, for the pre-processing output data obtained by the pre-processing of image construction, n times of image construction needs to store n pieces of pre-processing output data, and the storage space for storing one piece of pre-processing output data is occupied by n times of image construction, so that image construction resources are wasted.
The embodiment of the invention aims to improve the image construction efficiency under the condition that the same group of CT scanning data uses a plurality of sets of image construction parameter values for image construction.
The image reconstruction method according to an embodiment of the present invention will be described in detail below with reference to examples.
Fig. 2 is a flowchart illustrating an image reconstruction method according to an embodiment of the present invention. As shown in fig. 2, in this embodiment, the image reconstruction method may include:
s201, in one image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained.
S202, image construction preprocessing is carried out on the CT scanning data, and preprocessing output data are obtained.
S203, according to each set of image construction parameter values in the at least two sets of image construction parameter values, images are constructed based on the pre-processing output data respectively, and a plurality of reconstructed image sequences are obtained, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
The imaging parameter values may be different parameter values of the same parameter, such as different convolution kernels, or parameter values of different kinds of parameters.
The related art uses only one set of image-building parameter values in one image-building process. This embodiment uses at least two sets of imaging parameter values in one imaging procedure.
In the embodiment, at least two sets of image construction parameter values share one image construction pretreatment process, so that the times of image construction pretreatment are reduced, and the processing time is saved. For example, for n sets of imaging parameters, only one imaging preprocessing process is required in the embodiment, and only one copy of preprocessing output data obtained by the imaging preprocessing process needs to be stored, so that the storage space is saved.
In one exemplary implementation, the imaging parameter values may include convolution kernels.
In this embodiment, after at least two sets of image creation parameter values are multiplexed in the same image creation preprocessing process, the respective processing is performed independently.
For example. In one imaging process, n sets of imaging parameters require one pre-imaging process, and the processes after the n pre-imaging processes refer to the second stage and the third stage in the CT reconstruction process.
Note that, the step numbers in this embodiment are not used to limit the execution order of the steps, and for example, in another embodiment, step S202 may be executed before step S201.
In an exemplary implementation process, constructing an image based on the pre-processing output data according to each of at least two sets of imaging parameter values, respectively, to obtain a plurality of reconstructed image sequences may include:
convolving the pre-processing output data with a convolution kernel to obtain an output image matrix sequence;
and generating a reconstructed image sequence according to the output image matrix sequence.
According to the image reconstruction method provided by the embodiment of the invention, at least two sets of image construction parameter values required by CT image reconstruction are obtained in one image construction process, image construction pretreatment is carried out on CT scanning data to obtain pretreatment output data, image reconstruction is respectively carried out on the pretreatment output data according to each set of image construction parameter value to obtain a plurality of reconstructed image sequences, each reconstructed image sequence corresponds to one set of image construction parameter value, and a plurality of sets of image construction parameter values share one image construction pretreatment process, so that the image construction time is reduced, and the image construction efficiency is improved.
In addition, the image reconstruction method provided by the embodiment of the invention reduces the number of parts of pre-processing output data which need to be stored, saves the storage space and reduces the waste of image construction resources.
Based on the above method embodiment, the embodiment of the present invention further provides corresponding apparatus, device, and storage medium embodiments.
Fig. 3 is a functional block diagram of an image reconstruction apparatus according to an embodiment of the present invention. As shown in fig. 3, in this embodiment, the image reconstruction apparatus may include:
an obtaining module 310, configured to obtain at least two sets of image construction parameter values required by CT image reconstruction in one image construction process;
a preprocessing module 320, configured to perform image construction preprocessing on the CT scanning data to obtain preprocessing output data;
the reconstruction module 330 is configured to construct an image based on the pre-processing output data according to each of the at least two sets of imaging parameter values, to obtain a plurality of reconstructed image sequences, where each reconstructed image sequence corresponds to one set of imaging parameter value.
In one exemplary implementation, the imaging parameter values include convolution kernels.
In an exemplary implementation, the reconstruction module 330 may be specifically configured to:
convolving the pre-processing output data with a convolution kernel to obtain an output image matrix sequence;
and generating a reconstructed image sequence according to the output image matrix sequence.
The embodiment of the invention also provides the CT equipment. Fig. 4 is a hardware configuration diagram of a CT apparatus according to an embodiment of the present invention. As shown in fig. 4, the CT system includes: an internal bus 401, and a memory 402, a processor 403, and an external interface 404, which are connected through the internal bus, wherein,
the external interface 404 is configured to connect to a detector of a CT system, where the detector includes a plurality of detector chambers and corresponding processing circuits;
the memory 402 is used for storing machine readable instructions corresponding to control logic of image reconstruction;
the processor 403 is configured to read the machine-readable instructions in the memory 402 and execute the instructions to implement the following operations:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
In one exemplary implementation, the imaging parameter values include convolution kernels.
In an exemplary implementation process, according to each of the at least two sets of imaging parameter values, an image is constructed based on the pre-processing output data, respectively, to obtain a plurality of reconstructed image sequences, including:
convolving the pre-processing output data with a convolution kernel to obtain an output image matrix sequence;
and generating a reconstructed image sequence according to the output image matrix sequence.
The embodiment of the invention also provides a CT system, which comprises a detector, a scanning bed and CT equipment, wherein the detector comprises a plurality of detector chambers and corresponding processing circuits; wherein:
the detector chamber is used for detecting X-rays passing through a scanned object and converting the X-rays into electric signals in the scanning process of the CT system;
the processing circuit is used for converting the electric signal into a pulse signal and acquiring energy information of the pulse signal;
the CT device is used for:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
In one exemplary implementation, the imaging parameter values include convolution kernels.
In an exemplary implementation process, according to each of the at least two sets of imaging parameter values, an image is constructed based on the pre-processing output data, respectively, to obtain a plurality of reconstructed image sequences, including:
convolving the pre-processing output data with a convolution kernel to obtain an output image matrix sequence;
and generating a reconstructed image sequence according to the output image matrix sequence.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the program, when executed by a processor, implements the following operations:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
In one exemplary implementation, the imaging parameter values include convolution kernels.
In an exemplary implementation process, according to each of the at least two sets of imaging parameter values, an image is constructed based on the pre-processing output data, respectively, to obtain a plurality of reconstructed image sequences, including:
convolving the pre-processing output data with a convolution kernel to obtain an output image matrix sequence;
and generating a reconstructed image sequence according to the output image matrix sequence.
For the device and apparatus embodiments, as they correspond substantially to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, wherein the modules described as separate parts may or may not be physically separate, and the parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution in the specification. One of ordinary skill in the art can understand and implement it without inventive effort.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Other embodiments of the present description will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This specification is intended to cover any variations, uses, or adaptations of the specification following, in general, the principles of the specification and including such departures from the present disclosure as come within known or customary practice within the art to which the specification pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the specification being indicated by the following claims.
It will be understood that the present description is not limited to the precise arrangements described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present description is limited only by the appended claims.
The above description is only a preferred embodiment of the present disclosure, and should not be taken as limiting the present disclosure, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.
Claims (9)
1. An image reconstruction method, comprising:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
2. The method of claim 1, wherein the imaging parameter values comprise convolution kernels.
3. The method of claim 2, wherein constructing an image based on the pre-processing output data from each of the at least two sets of imaging parameter values, respectively, to obtain a plurality of reconstructed image sequences, comprises:
convolving the pre-processing output data with a convolution kernel to obtain an output image matrix sequence;
and generating a reconstructed image sequence according to the output image matrix sequence.
4. An image reconstruction apparatus, comprising:
the acquisition module is used for acquiring at least two sets of image construction parameter values required by CT image reconstruction in the process of image construction for one time;
the preprocessing module is used for carrying out image construction preprocessing on the CT scanning data to obtain preprocessing output data;
and the reconstruction module is used for constructing images based on the preprocessing output data respectively according to each set of image construction parameter values in the at least two sets of image construction parameter values to obtain a plurality of reconstructed image sequences, and each reconstructed image sequence corresponds to one set of image construction parameter values.
5. The apparatus of claim 4, wherein the imaging parameter value comprises a convolution kernel.
6. The apparatus of claim 5, wherein the reconstruction module is specifically configured to:
convolving the pre-processing output data with a convolution kernel to obtain an output image matrix sequence;
and generating a reconstructed image sequence according to the output image matrix sequence.
7. A CT apparatus, comprising: the system comprises an internal bus, a memory, a processor and an external interface which are connected through the internal bus; the external interface is used for connecting a detector of the CT system, and the detector comprises a plurality of detector chambers and corresponding processing circuits;
the memory is used for storing machine readable instructions corresponding to control logic of image reconstruction;
the processor is configured to read the machine-readable instructions on the memory and perform the following operations:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
8. A CT system comprising a detector, a scanning bed and a CT apparatus, the detector comprising a plurality of detector chambers and corresponding processing circuitry; wherein:
the detector chamber is used for detecting X-rays passing through a scanned object and converting the X-rays into electric signals in the scanning process of the CT system;
the processing circuit is used for converting the electric signal into a pulse signal and acquiring energy information of the pulse signal;
the CT device is used for:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
9. A computer-readable storage medium, having a computer program stored thereon, wherein the program when executed by a processor performs the operations of:
in the primary image building process, at least two sets of image building parameter values required by CT image reconstruction are obtained;
carrying out image construction pretreatment on CT scanning data to obtain pretreatment output data;
and according to each set of image construction parameter values in the at least two sets of image construction parameter values, constructing an image based on the pre-processing output data respectively to obtain a plurality of reconstructed image sequences, wherein each reconstructed image sequence corresponds to one set of image construction parameter values.
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