CN113935936A - Method and device for reconstructing fault fusion image - Google Patents
Method and device for reconstructing fault fusion image Download PDFInfo
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Abstract
The embodiment of the application provides a method and a device for reconstructing a fault fusion image, wherein the method comprises the following steps of; loading a predetermined auxiliary file into the GPU; acquiring a tomosynthesis image sequence, wherein the tomosynthesis image sequence is obtained by shooting by a suspension type tomosynthesis X-ray machine; and carrying out fault fusion reconstruction on the fault fusion image sequence according to the auxiliary file by utilizing the GPU to obtain a three-dimensional reconstruction image, wherein the predetermined auxiliary file is used for accelerating the process of fault fusion reconstruction. By implementing the embodiment, the three-dimensional reconstruction image can be rapidly and accurately synthesized.
Description
Technical Field
The application relates to the technical field of image processing, in particular to a method and a device for reconstructing a tomosynthesis image.
Background
Currently, in the field of medical device technology, medical dr (digital radio) and ct (computed tomography) imaging technologies play a very important role in the field of medical diagnosis. The DR is a mature medical apparatus, has short imaging and shooting time, low dosage and high spatial resolution, is widely applied to clinical diagnosis, and is one of the indispensable important components of a hospital diagnosis system. However, the image formed by DR is a two-dimensional plane image, which has missed diagnosis and the like for the inspection of different structural parts of the human body, and has insufficient response capability to pathological changes of a microstructure, and the position which cannot replace the advantage of CT tomography is not available, CT has great advantage in pathological change observation of a microstructure and multi-layer structure inspection compared with DR, but during CT inspection, the imaging shooting dose is large, the cost is relatively high, the cost is increased while the body of a patient is damaged, the economic expenditure is increased, the CT inspection time is long, the diagnosis efficiency is reduced, and CT easily generates serious artifacts for the inspection of metal implant parts of the human body, thereby affecting clinical diagnosis. And CT has certain limitation on standing shooting and certain limitation on aspects such as clinical examination and scientific research requirements.
With the development of computer technology and X-ray flat panel detector technology, the application field of medical X-ray machines has changed greatly due to the appearance of Digital Tomography (DTS), and the development of the medical X-ray machines from initial two-dimensional fluoroscopy to later tomographic examination of the head, chest, limbs, digestive tract, etc. The tomosynthesis image reconstruction is one of important components in a digital tomosynthesis imaging system, the imaging quality and the reconstruction speed of the tomosynthesis image reconstruction are important indexes for measuring the performance of the tomosynthesis imaging system, the traditional film tomosynthesis image can only reconstruct the tomosynthesis image of a certain layer, the DTS technology can obtain multi-layer reconstructed images through one-time scanning, the shooting dose is lower, and the lung scanning is much lower than the CT thin-layer scanning; and DTS formation of image receives metal artifact interference less, is fit for metal implant postoperative rehabilitation inspection to shoot the position unrestricted, but also can carry out the shooting inspection of heavy burden position such as vertical position by the horizontal position shooting. Compared with CT, DTS imaging spatial resolution has great advantages, and can realize lesion examination of lung nodules, gastrointestinal radiography, orthopedics and other fine structures. With the continuous improvement of DTS technology, the clinical application of DTS technology is more extensive. However, the existing X-ray machine cannot well realize tomosynthesis imaging, and has low accuracy and a small application range.
Disclosure of Invention
The embodiment of the application aims to provide a method and a device for reconstructing a tomosynthesis image, which can accurately and quickly realize tomosynthesis imaging and synthesize a three-dimensional reconstruction image.
In a first aspect, an embodiment of the present application provides a tomosynthesis image reconstruction method, including:
loading a predetermined auxiliary file into the GPU;
acquiring a tomosynthesis image sequence, wherein the tomosynthesis image sequence is obtained by shooting by a suspension type tomosynthesis X-ray machine;
and carrying out fault fusion on the fault fusion image sequence by utilizing the GPU according to the auxiliary file to obtain a three-dimensional reconstruction image, wherein the predetermined auxiliary file is used for accelerating the fault fusion process.
In the implementation process, the predetermined auxiliary file is loaded in the GPU, the tomosynthesis image sequence is acquired, a large amount of calculation processing is required in the tomosynthesis process, and the time of the tomosynthesis process is reduced because the auxiliary file is predetermined. Based on the embodiment, the three-dimensional reconstruction image can be synthesized quickly and accurately.
Further, after the step of acquiring a tomosynthesis image sequence, the method further comprises:
preprocessing the tomosynthesis image sequence;
the pretreatment comprises the following steps: dark field, gain, dead pixel elimination, detector delay, normalization and noise removal.
In the implementation process, the quality of the fault fusion image sequence is improved, and the definition of the three-dimensional reconstruction image can be improved.
Further, the step of tomosynthesis of the sequence of tomosynthesis images according to the auxiliary file comprises:
the method comprises the following steps: according to the auxiliary file, correcting the geometric error of the tomosynthesis image sequence to obtain a corrected tomosynthesis image sequence, wherein the geometric error is caused by the mechanical error of the tomosynthesis X-ray machine;
step two: processing the corrected tomosynthesis image sequence by using a filtering back projection method according to the auxiliary file to obtain a filtered tomosynthesis image sequence;
step three: according to the auxiliary file, carrying out weight assignment on each fault fusion image in the filtered fault fusion image sequence to obtain a weight fault fusion image sequence;
step four: according to the auxiliary file, each tomosynthesis image in the weighted tomosynthesis image sequence is cut to obtain a cut tomosynthesis image sequence;
step five: and according to the auxiliary file, carrying out translation and difference calculation on the cut fault fusion image sequence to obtain the three-dimensional reconstruction image.
In the implementation process, according to the auxiliary file, mechanical error correction, filtering back projection, weight assignment, cutting, translation and difference value calculation are respectively carried out on the tomosynthesis image sequence, and finally a high-quality, clear and high-quality three-dimensional reconstruction image is obtained.
Further, the number of the GPUs is more than or equal to four, and the step two, the step three, the step four and the step five are completed by using different GPUs.
In the implementation process, image fusion reconstruction is a project with huge calculation amount, and multiple steps are distributed in different GPUs to be completed, so that the operation efficiency can be improved.
Further, the auxiliary file includes: a geometry calibration file comprising mechanical error correction coefficients for the suspended tomosynthesis X-ray machine;
the step of correcting the geometric error of the tomosynthesis image sequence according to the auxiliary file to obtain a corrected tomosynthesis image sequence includes:
and correcting the geometric error of the fault fusion image sequence according to the geometric calibration file to obtain a corrected fault fusion image sequence.
In the implementation process, the geometric calibration file comprises a mechanical error correction coefficient of the suspension type tomosynthesis X-ray machine, and the geometric error of the tomosynthesis image sequence can be quickly corrected according to the geometric calibration file.
Further, the auxiliary file further comprises: a weight coefficient file comprising a filter kernel for each tomosynthesis image in the sequence of tomosynthesis images;
the step of processing the corrected tomosynthesis image sequence by using a filtering back projection method to obtain a filtered tomosynthesis image sequence comprises:
in the implementation process, the auxiliary file includes a weight coefficient file, and the weight coefficient file includes a filter kernel function of each tomosynthesis image in the sequence of tomosynthesis images. Based on the embodiment, the fault fusion image sequence can be rapidly filtered.
Further, the weight coefficient file further includes a weight value of each tomosynthesis image in the sequence of tomosynthesis images, the weight value being used to change the pixel intensity of each tomosynthesis image in the sequence of tomosynthesis images;
the step of performing weight assignment on each fault fusion image in the filtered fault fusion image sequence according to the auxiliary file to obtain a weight fault fusion image sequence comprises the following steps:
and performing weight assignment on each fault fusion image in the filtered fault fusion image sequence according to the weight value of each fault fusion image in the fault fusion image sequence to obtain the weighted fault fusion image sequence.
In the implementation process, each tomosynthesis image is obtained by shooting by a suspension type tomosynthesis X-ray machine at different angles, and different weights are given to the tomosynthesis images corresponding to the angles in the process of synthesizing the three-dimensional reconstruction images, so that the definition of the obtained three-dimensional reconstruction images can be improved.
Further, the weight coefficient file further includes a target height of each tomosynthesis image in the sequence of tomosynthesis images;
the step of cutting each tomosynthesis image in the weighted tomosynthesis image sequence according to the auxiliary file to obtain a cut tomosynthesis image sequence comprises the following steps:
and cutting each tomosynthesis image in the weighted tomosynthesis image sequence according to the target height of each tomosynthesis image in the tomosynthesis image sequence to obtain the cut tomosynthesis image sequence.
In the implementation process, each tomosynthesis image is obtained by shooting by the suspension type tomosynthesis X-ray machine at different angles, and the tomosynthesis images shot at different angles are cut, so that the three-dimensional effect of the obtained three-dimensional reconstruction image is more obvious.
Further, the auxiliary file further comprises: a coordinate file comprising final displacement coordinates for each tomosynthesis image in the sequence of tomosynthesis images;
the step of performing translation and difference calculation on the cut tomosynthesis image sequence according to the auxiliary file to obtain the three-dimensional reconstruction image comprises the following steps:
translating each fault fusion image in the cut fault fusion image sequence to the final displacement coordinate of each fault fusion image in the fault fusion image sequence to obtain a translated fault fusion image sequence;
and processing the pixel point of each tomosynthesis image in the translated tomosynthesis image sequence by using an interpolation algorithm to obtain the three-dimensional reconstruction image.
In the implementation process, the coordinate file comprises a final displacement coordinate of each tomosynthesis image in the tomosynthesis image sequence, each tomosynthesis image in the cut tomosynthesis image sequence is translated to the final displacement coordinate of each tomosynthesis image in the tomosynthesis image sequence to obtain the translated tomosynthesis image sequence, and the pixel points of each tomosynthesis image in the translated tomosynthesis image sequence are processed by using an interpolation algorithm, so that the three-dimensional effect of the three-dimensional reconstruction image is more obvious.
Further, after the step of preprocessing the tomosynthesis image sequence, the method further comprises:
judging whether a metal implant image exists in the fault fusion image sequence;
if yes, the step of carrying out fault fusion reconstruction on the fault fusion image sequence according to the auxiliary file to obtain a three-dimensional reconstruction image comprises the following steps:
dividing the tomosynthesis image sequence into a tomosynthesis image sequence with a metal implant and a tomosynthesis image sequence without a metal implant;
according to the auxiliary file, carrying out fault fusion reconstruction on the fault fusion image sequence with the metal implant and the fault fusion image sequence without the metal implant respectively to obtain a three-dimensional reconstruction image with the metal implant and a three-dimensional reconstruction image without the metal implant;
and fusing the three-dimensional reconstruction image with the metal implant and the three-dimensional reconstruction image without the metal implant to obtain the three-dimensional reconstruction image.
In the implementation process, firstly, whether a metal implant image exists in a fault fusion image sequence or not is judged, if yes, the fault fusion image sequence is divided into a fault fusion image sequence with a metal implant and a fault fusion image sequence without the metal implant, and the two sequences are fused after fault fusion reconstruction is respectively carried out on the two sequences, so that the three-dimensional reconstruction image is obtained. Based on the embodiment, a clear three-dimensional reconstruction image can be generated when the metal image is contained in the fault fusion image sequence, the metal artifact caused by the metal implant can be greatly reduced, the image quality is improved, and the diagnosis of the fine tissue structure around the metal implant is very obvious.
In a second aspect, an embodiment of the present application provides a tomosynthesis image reconstruction apparatus, including:
the loading module is used for loading the auxiliary file into the GPU;
the acquisition module is used for acquiring a tomosynthesis image sequence, and the tomosynthesis image sequence is obtained by shooting by a suspended tomosynthesis X-ray machine;
and the reconstruction module is used for carrying out fault fusion reconstruction on the fault fusion image sequence according to the auxiliary file to obtain a three-dimensional reconstruction image, wherein the auxiliary file is used for accelerating the fault fusion process.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic flowchart of a method for reconstructing a tomosynthesis image according to an embodiment of the present application;
fig. 2 is another schematic flowchart of a tomosynthesis image reconstruction method provided in an embodiment of the present application;
fig. 3 is a schematic flowchart of a fault fusion reconstruction provided in an embodiment of the present application;
fig. 4 is another schematic flowchart of a tomosynthesis image reconstruction method provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of a tomosynthesis image reconstruction apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example 1
Referring to fig. 1, the present application provides a tomosynthesis image reconstruction method, including:
s11: loading a predetermined auxiliary file into the GPU;
s12: acquiring a fault fusion image sequence, wherein the fault fusion image sequence is obtained by shooting by a suspension type fault fusion X-ray machine;
s13: and carrying out fault fusion reconstruction on the fault fusion image sequence by using the GPU according to the auxiliary file to obtain a three-dimensional reconstruction image, wherein the predetermined auxiliary file is used for accelerating the process of fault fusion reconstruction.
Specifically, a memory block and a texture display block of the building data are allocated in the host memory and the GPU display memory to store the reconstructed fault fusion data, and then a local file of the pre-computed auxiliary file is loaded into the host memory and then transmitted to the GPU display memory for direct calling of the fault fusion reconstruction.
In the above embodiments, the specific structure of the suspended type tomosynthesis X-ray machine is described in the related patent documents, and is not described herein.
In the above embodiment, the predetermined auxiliary file is loaded in the GPU to obtain the tomosynthesis image sequence, a large amount of calculation processing is required in the process of tomosynthesis, and the time of the process of tomosynthesis is reduced because the auxiliary file is predetermined. Based on the embodiment, the three-dimensional reconstruction image can be synthesized quickly and accurately.
Example 2
Referring to fig. 2, an embodiment of the present application provides another tomosynthesis image reconstruction method, including:
s21: loading a predetermined auxiliary file into the GPU;
s22: acquiring a fault fusion image sequence, wherein the fault fusion image sequence is obtained by shooting by a suspension type fault fusion X-ray machine;
s23: preprocessing a fault fusion image sequence;
the pretreatment comprises the following steps: dark field, gain, dead spot rejection, detector delay, normalization, noise removal, or a combination thereof.
The step improves the quality of the fault fusion image sequence and can improve the definition of the three-dimensional reconstruction image.
The dark field is a background image of the detector acquired under the condition that X rays are not exposed, and is called a dark field image, the detector delay is detector ghost, and partial information can be left in the acquired image of the previous frame.
S24: and carrying out fault fusion reconstruction on the fault fusion image sequence by using the GPU according to the auxiliary file to obtain a three-dimensional reconstruction image, wherein the predetermined auxiliary file is used for accelerating the process of fault fusion reconstruction.
Referring to fig. 3, in one possible implementation, S24 includes the following sub-steps:
s241: according to the auxiliary file, correcting the geometric error of the tomosynthesis image sequence to obtain a corrected tomosynthesis image sequence, wherein the geometric error is caused by the mechanical error of the tomosynthesis X-ray machine;
s242: processing the corrected tomosynthesis image sequence by using a filtering back projection method according to the auxiliary file to obtain a filtered tomosynthesis image sequence;
s243: according to the auxiliary file, carrying out weight assignment on each fault fusion image in the filtered fault fusion image sequence to obtain a weight fault fusion image sequence;
s244: according to the auxiliary file, cutting each tomosynthesis image in the weighted tomosynthesis image sequence to obtain a cut tomosynthesis image sequence;
s245: and according to the auxiliary file, carrying out translation and difference calculation on the cut fault fusion image sequence to obtain a three-dimensional reconstruction image.
In the above embodiment, according to the auxiliary file, the fault fusion image sequence is subjected to mechanical error correction, filtered back projection, weight assignment, clipping, translation, and difference calculation, so as to obtain a high-quality, clear, and high-quality three-dimensional reconstruction image.
In one possible embodiment, the auxiliary file comprises: a geometric calibration file, wherein the geometric calibration file comprises mechanical error correction coefficients of the suspended tomography fusion X-ray machine;
s241 includes: and correcting the geometric error of the tomosynthesis image sequence according to the geometric calibration file to obtain the corrected tomosynthesis image sequence.
Illustratively, the geometric calibration file includes: the system comprises a flat panel detector, a projection angle, a roll angle, deviation of an X-ray source focus and coordinates, a distance from a ray source to the flat panel detector, a distance from an imaging layer of the flat panel detector to a bed panel or a backrest panel, and a distance from the flat panel detector and the ray source to move in a relative translation mode; the use of the geometric calibration data can correct the problem of reduced quality of the reconstructed image caused by mechanical errors and improve the spatial resolution of the tomographic image.
In a possible embodiment, the auxiliary file further comprises: a weight coefficient file comprising a filter kernel for each tomosynthesis image in the sequence of tomosynthesis images;
s242 includes: and respectively replacing the filtering kernel function of the filtering back projection method with the filtering kernel function of each fault fusion image in the corrected fault fusion image sequence in the weight coefficient file, and processing each fault fusion image in the corrected fault fusion image sequence by using the filtering back projection method after replacing the kernel function to obtain the filtered fault fusion image sequence.
The filtered back-projection method is prior art and will not be described herein.
Based on the embodiment, the fault fusion image sequence can be rapidly filtered. In particular, the sharpness of the three-dimensional reconstructed image can be improved by applying different filter functions to different parts of the body.
In one possible embodiment, the weight coefficient file further includes a weight value of each tomosynthesis image in the sequence of tomosynthesis images, the weight value being used to change the pixel intensity of each tomosynthesis image in the sequence of tomosynthesis images; s243 includes: and carrying out weight assignment on each fault fusion image in the filtered fault fusion image sequence according to the weight value of each fault fusion image in the fault fusion image sequence to obtain a weight fault fusion image sequence.
Illustratively, the weight of each tomosynthesis image may be calculated by the following formula:
In one possible embodiment, the weight coefficient file further includes a target height of each tomosynthesis image in the sequence of tomosynthesis images; s244 includes: and cutting each tomosynthesis image in the weighted tomosynthesis image sequence according to the target height of each tomosynthesis image in the tomosynthesis image sequence to obtain the cut tomosynthesis image sequence.
The fault fusion images are obtained by shooting the suspension type fault fusion X-ray machine at different angles, and the fault fusion images shot at different angles are cut, so that the three-dimensional effect of the obtained three-dimensional reconstruction images is more obvious.
Illustratively, the target height of each tomosynthesis image is calculated by the following formula:
zs (z) represents the high values of the layers of the reconstructed tomosynthesis image.
In a possible embodiment, the auxiliary file further comprises: a coordinate file including final displacement coordinates of each tomosynthesis image in the sequence of tomosynthesis images; s245 includes: translating each fault fusion image in the cut fault fusion image sequence to a final displacement coordinate of each fault fusion image in the fault fusion image sequence to obtain a translated fault fusion image sequence;
and processing the pixel point of each tomosynthesis image in the translated tomosynthesis image sequence by using an interpolation algorithm to obtain a three-dimensional reconstruction image.
In one possible implementation, S241, S242, S243, S244, and S245 may be processed by different GPUs, which can increase the processing efficiency.
Example 3
Referring to fig. 4, an embodiment of the present application provides another tomosynthesis image reconstruction method, including:
s31: loading a predetermined auxiliary file into the GPU;
s32: acquiring a fault fusion image sequence, wherein the fault fusion image sequence is obtained by shooting by a suspension type fault fusion X-ray machine;
s33: preprocessing a fault fusion image sequence;
the pretreatment comprises the following steps: dark field, gain, dead spot rejection, detector delay, normalization, noise removal.
S34: judging whether a metal implant image exists in the tomosynthesis image sequence, if so, executing S35, S36 and S37, and if not, executing S38;
s35: dividing the tomosynthesis image sequence into a tomosynthesis image sequence with a metal implant and a tomosynthesis image sequence without a metal implant;
s36: carrying out fault fusion reconstruction on the fault fusion image sequence with the metal implant and the fault fusion image sequence without the metal implant respectively according to the auxiliary file to obtain a three-dimensional reconstruction image with the metal implant and a three-dimensional reconstruction image without the metal implant;
s37: fusing the three-dimensional reconstruction image with the metal implant and the three-dimensional reconstruction image without the metal implant to obtain a three-dimensional reconstruction image;
s38: and carrying out fault fusion reconstruction on the fault fusion image sequence by using the GPU according to the auxiliary file to obtain a three-dimensional reconstruction image, wherein the predetermined auxiliary file is used for accelerating the process of fault fusion reconstruction.
A possible implementation of S38 is already described in example 2 and is not described here.
In the embodiment, a clear three-dimensional reconstruction image can be generated when the metal image is contained in the fault fusion image sequence, so that the metal artifact caused by the metal implant can be greatly reduced, the quality of the image is improved, and the diagnosis of the fine tissue structure around the metal implant is very obvious.
In summary, the embodiment provided by the present application adopts a pre-calculation strategy, and the calculated geometric calibration parameters, weights, and shift coordinates are sent to a texture memory in a computer graphics processor in a manner of loading a local data stream, and are directly used in the shift overlay interpolation process, so that the calculation operation is reduced, and the process of reconstructing the shift overlay image is further accelerated. The fault fusion image is reconstructed in a parallel computing mode of loading local pre-computed parameters, and the reconstruction time can be shortened, the reconstruction speed of the fault fusion image is increased and the clinical observation and diagnosis efficiency is improved no matter in a mode of reconstructing while scanning or in a mode of reconstructing after scanning is finished. The method improves the inspection work flow, quickly and greatly reduces the exposure dose, shortens the inspection time, helps to relieve the mental stress of the patient, facilitates the patient with dyskinesia, helps to expand the inspection range and meet various clinical requirements.
Example 4
Referring to fig. 5, an embodiment of the present application provides a tomosynthesis image reconstruction apparatus, including:
the loading module 1 is used for loading the auxiliary file into the GPU;
the acquisition module 2 is used for acquiring a tomosynthesis image sequence, and the tomosynthesis image sequence is obtained by shooting by a suspension type tomosynthesis X-ray machine;
and the reconstruction module 3 is used for carrying out fault fusion reconstruction on the fault fusion image sequence according to the auxiliary file to obtain a three-dimensional reconstruction image, wherein the auxiliary file is used for accelerating the fault fusion process.
In a possible embodiment, the obtaining module 2 is further configured to pre-process the tomosynthesis image sequence;
the pretreatment comprises the following steps: dark field, gain, dead spot rejection, detector delay, normalization, noise removal.
In a possible embodiment, the reconstruction module 3 is further configured to perform the following steps:
the method comprises the following steps: according to the auxiliary file, correcting the geometric error of the tomosynthesis image sequence to obtain a corrected tomosynthesis image sequence, wherein the geometric error is caused by the mechanical error of the tomosynthesis X-ray machine; step two: processing the corrected tomosynthesis image sequence by using a filtering back projection method according to the auxiliary file to obtain a filtered tomosynthesis image sequence; step three: according to the auxiliary file, carrying out weight assignment on each fault fusion image in the filtered fault fusion image sequence to obtain a weight fault fusion image sequence; step four: according to the auxiliary file, cutting each tomosynthesis image in the weighted tomosynthesis image sequence to obtain a cut tomosynthesis image sequence; step five: and according to the auxiliary file, carrying out translation and difference calculation on the cut fault fusion image sequence to obtain a three-dimensional reconstruction image.
In a possible embodiment, the reconstruction module 3 is further configured to complete the steps two, three, four, and five by using different GPUs.
In one possible embodiment, the auxiliary file comprises: a geometric calibration file, wherein the geometric calibration file comprises mechanical error correction coefficients of the suspended tomography fusion X-ray machine; the reconstruction module 3 is further configured to correct a geometric error of the tomosynthesis image sequence according to the geometric calibration file, so as to obtain a corrected tomosynthesis image sequence.
In a possible embodiment, the auxiliary file further comprises: a weight coefficient file comprising a filter kernel for each tomosynthesis image in the sequence of tomosynthesis images; the reconstruction module 3 is further configured to respectively replace the filtering kernel function of the filtering back-projection method with the filtering kernel function of each tomographic fusion image in the corrected tomographic fusion image sequence in the weight coefficient file, and process each tomographic fusion image in the corrected tomographic fusion image sequence by using the filtering back-projection method after replacing the kernel function, so as to obtain the filtered tomographic fusion image sequence.
In one possible embodiment, the weight coefficient file further includes a weight value of each tomosynthesis image in the sequence of tomosynthesis images, the weight value being used to change the pixel intensity of each tomosynthesis image in the sequence of tomosynthesis images; the reconstruction module 3 is further configured to perform weight assignment on each filtered tomosynthesis image in the tomosynthesis image sequence according to the weight value of each tomosynthesis image in the tomosynthesis image sequence, so as to obtain a weighted tomosynthesis image sequence.
In one possible embodiment, the weight coefficient file further includes a target height of each tomosynthesis image in the sequence of tomosynthesis images; the reconstruction module 3 is further configured to crop each tomosynthesis image in the weighted tomosynthesis image sequence according to the target height of each tomosynthesis image in the tomosynthesis image sequence, so as to obtain a cropped tomosynthesis image sequence.
In a possible embodiment, the auxiliary file further comprises: a coordinate file including final displacement coordinates of each tomosynthesis image in the sequence of tomosynthesis images; the reconstruction module 3 is further configured to process the pixel points of each tomosynthesis image in the translated tomosynthesis image sequence by using an interpolation algorithm to obtain a three-dimensional reconstruction image.
In a possible embodiment, the obtaining module 2 is further configured to determine whether there is a metal implant image in the tomosynthesis image sequence; the reconstruction module 3 is further used for dividing the tomosynthesis image sequence into a tomosynthesis image sequence with a metal implant and a tomosynthesis image sequence without the metal implant when the metal implant image is contained in the tomosynthesis image sequence; carrying out fault fusion reconstruction on the fault fusion image sequence with the metal implant and the fault fusion image sequence without the metal implant respectively according to the auxiliary file to obtain a three-dimensional reconstruction image with the metal implant and a three-dimensional reconstruction image without the metal implant; and fusing the three-dimensional reconstruction image with the metal implant and the three-dimensional reconstruction image without the metal implant to obtain the three-dimensional reconstruction image.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, 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 code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, 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.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are merely examples of the present application and are not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (11)
1. A tomosynthesis image reconstruction method, comprising:
loading a predetermined auxiliary file into the GPU;
acquiring a tomosynthesis image sequence, wherein the tomosynthesis image sequence is obtained by shooting by a suspension type tomosynthesis X-ray machine;
and carrying out fault fusion reconstruction on the fault fusion image sequence according to the auxiliary file by utilizing the GPU to obtain a three-dimensional reconstruction image, wherein the predetermined auxiliary file is used for accelerating the process of fault fusion reconstruction.
2. The tomosynthesis image reconstruction method of claim 1, wherein after the step of acquiring a sequence of tomosynthesis images, the method further comprises:
preprocessing the tomosynthesis image sequence;
the pretreatment comprises the following steps: dark field, gain, dead spot rejection, detector delay, normalization, noise removal.
3. The method of reconstructing tomosynthesis images according to claim 1, wherein the step of performing tomosynthesis reconstruction of the sequence of tomosynthesis images from the auxiliary file comprises:
the method comprises the following steps: according to the auxiliary file, correcting the geometric error of the tomosynthesis image sequence to obtain a corrected tomosynthesis image sequence, wherein the geometric error is caused by the mechanical error of the tomosynthesis X-ray machine;
step two: processing the corrected tomosynthesis image sequence by using a filtering back projection method according to the auxiliary file to obtain a filtered tomosynthesis image sequence;
step three: according to the auxiliary file, carrying out weight assignment on each fault fusion image in the filtered fault fusion image sequence to obtain a weight fault fusion image sequence;
step four: according to the auxiliary file, each tomosynthesis image in the weighted tomosynthesis image sequence is cut to obtain a cut tomosynthesis image sequence;
step five: and according to the auxiliary file, carrying out translation and difference calculation on the cut fault fusion image sequence to obtain the three-dimensional reconstruction image.
4. The tomosynthesis image reconstruction method according to claim 3, wherein the number of GPUs is equal to or greater than four, and the second step, the third step, the fourth step and the fifth step are completed by using different GPUs.
5. The tomosynthesis image reconstruction method according to claim 3, characterized in that the auxiliary file includes: a geometry calibration file comprising mechanical error correction coefficients for the suspended tomosynthesis X-ray machine;
the step of correcting the geometric error of the tomosynthesis image sequence according to the auxiliary file to obtain a corrected tomosynthesis image sequence includes:
and correcting the geometric error of the fault fusion image sequence according to the geometric calibration file to obtain a corrected fault fusion image sequence.
6. The tomosynthesis image reconstruction method of claim 3, wherein the auxiliary file further comprises: a weight coefficient file comprising a filter kernel for each tomosynthesis image in the sequence of tomosynthesis images;
the step of processing the corrected tomosynthesis image sequence by using a filtering back projection method to obtain a filtered tomosynthesis image sequence comprises:
and respectively replacing the filtering kernel function of the filtering back projection method with the filtering kernel function of each fault fusion image in the corrected fault fusion image sequence in the weight coefficient file, and processing each fault fusion image in the corrected fault fusion image sequence by using the filtering back projection method after replacing the kernel function to obtain the filtered fault fusion image sequence.
7. The tomosynthesis image reconstruction method of claim 6, wherein the weight coefficient file further comprises a weight value for each tomosynthesis image in the sequence of tomosynthesis images, the weight value being used to change a pixel intensity of each tomosynthesis image in the sequence of tomosynthesis images;
the step of performing weight assignment on each fault fusion image in the filtered fault fusion image sequence according to the auxiliary file to obtain a weight fault fusion image sequence comprises the following steps:
and performing weight assignment on each fault fusion image in the filtered fault fusion image sequence according to the weight value of each fault fusion image in the fault fusion image sequence to obtain the weighted fault fusion image sequence.
8. The tomosynthesis image reconstruction method of claim 6, wherein the weight coefficient file further comprises a target height of each tomosynthesis image in the sequence of tomosynthesis images;
the step of cutting each tomosynthesis image in the weighted tomosynthesis image sequence according to the auxiliary file to obtain a cut tomosynthesis image sequence comprises the following steps:
and cutting each tomosynthesis image in the weighted tomosynthesis image sequence according to the target height of each tomosynthesis image in the tomosynthesis image sequence to obtain the cut tomosynthesis image sequence.
9. The tomosynthesis image reconstruction method of claim 6, wherein the auxiliary file further comprises: a coordinate file comprising final displacement coordinates for each tomosynthesis image in the sequence of tomosynthesis images;
the step of performing translation and difference calculation on the cut tomosynthesis image sequence according to the auxiliary file to obtain the three-dimensional reconstruction image comprises the following steps:
translating each fault fusion image in the cut fault fusion image sequence to the final displacement coordinate of each fault fusion image in the fault fusion image sequence to obtain a translated fault fusion image sequence;
and processing the pixel point of each tomosynthesis image in the translated tomosynthesis image sequence by using an interpolation algorithm to obtain the three-dimensional reconstruction image.
10. The tomosynthesis image reconstruction method of claim 2, wherein after the step of pre-processing the sequence of tomosynthesis images, the method further comprises:
judging whether a metal implant image exists in the fault fusion image sequence;
if yes, the step of carrying out fault fusion reconstruction on the fault fusion image sequence according to the auxiliary file to obtain a three-dimensional reconstruction image comprises the following steps:
dividing the tomosynthesis image sequence into a tomosynthesis image sequence with a metal implant and a tomosynthesis image sequence without a metal implant;
according to the auxiliary file, carrying out fault fusion reconstruction on the fault fusion image sequence with the metal implant and the fault fusion image sequence without the metal implant respectively to obtain a three-dimensional reconstruction image with the metal implant and a three-dimensional reconstruction image without the metal implant;
and fusing the three-dimensional reconstruction image with the metal implant and the three-dimensional reconstruction image without the metal implant to obtain the three-dimensional reconstruction image.
11. A tomosynthesis image reconstruction apparatus, characterized by comprising:
the loading module is used for loading the auxiliary file into the GPU;
the acquisition module is used for acquiring a tomosynthesis image sequence, and the tomosynthesis image sequence is obtained by shooting by a suspended tomosynthesis X-ray machine;
and the reconstruction module is used for carrying out fault fusion reconstruction on the fault fusion image sequence according to the auxiliary file to obtain a three-dimensional reconstruction image, wherein the auxiliary file is used for accelerating the fault fusion process.
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