CN115170737A - Image processing method, device and system for breast three-dimensional tomography - Google Patents
Image processing method, device and system for breast three-dimensional tomography Download PDFInfo
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Abstract
The invention provides a method for breast three-dimensional tomosynthesis photography, which comprises the following steps: acquiring original mammographic images at different angles, and performing brightness correction on the original mammographic images to obtain corrected images at different angles; carrying out reconstruction preprocessing on the corrected images at different angles, and carrying out reconstruction processing of converting the preprocessed images into three dimensions from two dimensions; removing the artifact of the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional sectional image; and balancing the brightness of the edge and the center of the reconstructed mammary gland three-dimensional sectional image to obtain a target mammary gland three-dimensional sectional image. The invention is a pure software DBT functional module, so that a client with the mammary machine system and console software capable of shooting X-ray projection images at different angles can obtain the DBT function by integrating the DBT product.
Description
Technical Field
The invention mainly relates to a breast three-dimensional tomography fusion method, in particular to a digital breast three-dimensional tomography method, and belongs to the field of image processing.
Background
Digital Breast Tomography (DBT) is a new technology for breast imaging, an improvement over fully digital mammography (FFDM). The DBT acquires a plurality of projection data from multiple angles, so that the overlapping of mammary tissues is reduced, photographic images of all layers are reconstructed, and some hidden cancers can be detected. Whether the DBT function is provided or not is an important index for distinguishing high and low end models of mammary glands at present. According to the application, a pure software DBT functional module is developed according to market demands, so that a client who can shoot X-ray projection image mammary machine systems and console software at different angles can obtain the DBT function by integrating the DBT product.
Disclosure of Invention
In view of the above, the present application is proposed to provide an image processing method, apparatus and system for breast three-dimensional tomography that overcome or at least partially solve the above problems, including:
an image processing method for breast three-dimensional tomography, comprising the steps of:
acquiring original mammographic images at different angles, and performing brightness correction on the original mammographic images to obtain corrected images at different angles;
carrying out reconstruction preprocessing on the corrected images at different angles, and carrying out reconstruction processing of converting the preprocessed images into three dimensions from two dimensions;
removing the artifact of the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional sectional image;
and balancing the brightness of the edge and the center of the reconstructed mammary gland three-dimensional sectional image to obtain a target mammary gland three-dimensional sectional image.
Further, the acquiring of the original mammographic images at different angles and performing brightness correction on the original mammographic images to obtain corrected images at different angles includes:
acquiring a dark field correction table and a bright field correction table;
and correcting the original breast image according to the dark field correction table and the bright field correction table to obtain a corrected image.
Further, the reconstructing preprocessing is performed on the corrected images at different angles, and the reconstructing preprocessing includes:
carrying out logarithmic transformation on the corrected image;
pre-weighting the corrected image according to the skewness table, and removing the influence of a light source to obtain a pre-weighted image;
and performing three-dimensional reconstruction processing on the pre-weighted image.
Further, the artifact removing operation on the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional tomographic image includes:
segmenting the original mammographic images with different angles according to automatic threshold binarization to obtain segmentation masks;
performing three-dimensional reconstruction on the segmentation mask to obtain a reconstructed mask;
and removing the artifact of the three-dimensional reconstructed image according to the reconstructed mask to obtain a reconstructed breast three-dimensional tomographic image.
Further, the removing the artifact of the reconstructed breast three-dimensional tomographic image according to the reconstructed mask includes:
and comparing the three-dimensional reconstructed image with the reconstructed mask, setting the position of the reconstructed mask number smaller than the reconstructed photographic image number as 0, and leaving the rest positions without processing to obtain a reconstructed mammary three-dimensional tomographic image with removed artifacts.
Further, the step of equalizing the brightness of the edge and the center of the reconstructed breast three-dimensional tomographic image to obtain a target breast three-dimensional tomographic image includes the steps of:
performing mask processing on the finally reconstructed breast three-dimensional tomographic image, and performing median filtering processing on the image in the mask;
carrying out coordinate conversion on the Cartesian coordinates of the reconstructed breast three-dimensional sectional image to obtain the polar coordinates of the image;
carrying out low-pass filtering processing and multi-resolution analysis processing on the reconstructed breast three-dimensional tomographic image to obtain a direct-current component image;
and carrying out regional processing on the direct current component image, replacing the direct current component image with the image processed by the region, and reconstructing to obtain a target breast three-dimensional tomographic image.
Further, before the step of performing mask processing on the final reconstructed breast three-dimensional tomographic image and performing median filtering processing on the image in the mask, the method further includes:
and carrying out slice processing on the reconstructed breast three-dimensional tomographic image according to pixels, and carrying out equalization processing on all slices, wherein the number of the pixels is 1-9.
An apparatus for image processing for breast three-dimensional tomography, which implements the steps of the image processing method for breast three-dimensional tomography of any one of the above items, comprising:
the correction module is used for acquiring original mammographic images at different angles and performing brightness correction on the original mammographic images to obtain corrected images at different angles;
the reconstruction module is used for reconstructing the corrected images at different angles and performing two-dimensional to three-dimensional reconstruction on the images after the pre-processing;
the artifact removing module is used for removing the artifact of the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional tomographic image;
and the post-processing module is used for balancing the brightness of the edge and the center of the reconstructed mammary gland three-dimensional sectional image to obtain a target mammary gland three-dimensional sectional image.
Electronic device, characterized in that it comprises a processor, a memory and a computer program stored on said memory and executable on said processor, said computer program, when being executed by said processor, realizing the steps of the image processing method for three-dimensional tomography of the breast as defined in any of the above.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the image processing method for breast three-dimensional tomography of any of the above.
The application has the following advantages:
the method comprises the steps of obtaining original mammographic images at different angles, and performing brightness correction on the original mammographic images to obtain corrected images at different angles; carrying out reconstruction preprocessing on the corrected images at different angles; carrying out reconstruction processing of converting the pre-processed image into three dimensions;
removing the artifact of the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional sectional image; and balancing the brightness of the edge and the center of the reconstructed mammary gland three-dimensional sectional image to obtain a target mammary gland three-dimensional sectional image. Through the DBT function module of the pure software, a client with a mammary machine system and console software which can shoot X-ray projection images at different angles and do not have the DBT function can acquire the DBT function by integrating the DBT product provided by the application.
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In order to more clearly illustrate the technical solutions of the present application, the drawings needed to be used in the description of the present application will be briefly introduced below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive labor.
Fig. 1 is a flowchart illustrating steps of an image processing method for breast three-dimensional tomography according to an embodiment of the present disclosure;
FIG. 2 is a reconstructed breast three-dimensional tomographic image provided by an embodiment of the present application;
FIG. 3 is a three-dimensional tomographic image of a target breast provided by an embodiment of the present application;
fig. 4 is a schematic block structure diagram of an apparatus of an image processing method for breast three-dimensional tomography according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a computer device for an image processing method for breast three-dimensional tomography according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description. It should be apparent that the embodiments described are some, but not all embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application. In an embodiment of the present invention, an image processing method for breast three-dimensional tomography is provided;
the method as shown in fig. 1 comprises the steps of:
s110, acquiring original mammographic images at different angles, and performing brightness correction on the original mammographic images to obtain corrected images at different angles;
s120, reconstructing the corrected images at different angles, and performing reconstruction processing for converting the images subjected to the reconstruction processing into three dimensions;
s130, performing artifact removing operation on the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional sectional image;
s140, balancing the brightness of the edge and the center of the reconstructed mammary gland three-dimensional sectional image to obtain a target mammary gland three-dimensional sectional image.
In the embodiment of the application, original mammographic images at different angles are obtained, and brightness correction is performed on the original mammographic images to obtain corrected images at different angles; carrying out reconstruction preprocessing on the corrected images at different angles; carrying out reconstruction processing of converting the pre-processed image into three dimensions; removing the artifact of the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional sectional image; and balancing the brightness of the edge and the center of the reconstructed mammary gland three-dimensional sectional image to obtain a target mammary gland three-dimensional sectional image. Through the DBT function module of the pure software, a client with a mammary machine system and console software which can shoot X-ray projection images at different angles and do not have the DBT function can acquire the DBT function by integrating the DBT product provided by the application.
Next, an image processing method for breast three-dimensional tomography in the present exemplary embodiment will be further described.
As described in step S110 above, the specific process of "acquiring raw mammographic images at different angles and performing brightness correction on the raw mammographic images to obtain corrected images at different angles" in step S110 can be further described with reference to the following description.
A dark field correction gauge and a bright field correction gauge are obtained as described in the following steps.
It should be noted that the correction of the original mammographic image is substantially performed by dark field correction and bright field correction, and the correction is performed by applying a correction table to clinical data.
And correcting the original mammary gland image according to the dark field correction table and the bright field correction table to obtain a corrected image.
The correction method includes: subtracting dark field from each image, dividing by bright field with angle corresponding to the dark field, outputting the final correction result, and calculating the correction result according to formula
And rectifying the image, wherein EPS represents floating point relative precision. The EPS is added to the numerator denominator, so that the situation that the denominator is zero can be prevented, the negative number part in the corrected image is set to be 0, and the output result is the final corrected image.
As described in step S120 above, the "performing reconstruction preprocessing on the corrected images at different angles" in step S120 and performing two-dimensional to three-dimensional reconstruction processing on the preprocessed images may be further described with reference to the following description. "is used herein.
The rectified image is logarithmically transformed as described in the following steps.
It should be noted that the property and correlation of the data are not changed after taking the logarithm, but the scale of the variable is compressed. The variance is constant, namely, the fluctuation is relatively stable, and the problem of variance can be eliminated.
By the formula
I＝-log(I)
And carrying out logarithmic transformation processing.
And performing pre-weighting processing on the corrected image according to the inclination table to remove the influence of a light source to obtain a pre-weighted image.
It should be noted that, because the angles of the acquired images are different and the light sources of the images at different angles are different, the images are pre-weighted according to the slope table, so that the problem of the light sources of the different images is solved, and for each image, the corresponding frame angle is acquired to calculate the source position corresponding to the image;
SourcePosition.X＝sx＝0
SourcePosition.Y＝sy＝DSR×sinθ
SourcePosition.Z＝sz＝DDR+DSR×cosθ
for each row iv and each column iu of the image, the coordinate values us and vs are calculated, which values can be pre-calculated geometrically;
for each row iv and column iu of the image, by
And calculating a weight value, multiplying each row iv and each column iu of the image by the weight value of the corresponding position, and finally outputting a result, namely the pre-weighted image.
The pre-weighted image is subjected to a three-dimensional reconstruction process as described in the following steps.
As an example, a filtered back projection method may be used to reconstruct a two-dimensional image into a three-dimensional image, and other methods may be used to convert a two-dimensional image into a three-dimensional image.
In a specific implementation, a filtering back projection method is used to convert a two-dimensional image into a three-dimensional image, and the pre-weighted image is filtered to obtain a filtered image, wherein the digital image is often polluted by various noises during the formation, transmission and recording processes of the digital image. In addition, noise may also be introduced into the resulting image at some point in the image processing when the input image object is not as expected. These noises often appear as an isolated pixel or block of pixels on the image that causes a strong visual effect. In general, the noise signal is not correlated with the object to be studied-it appears in the form of useless information, disturbing the observable information of the image. For digital image signals, the noise table is more or less extreme values, and the extreme values act on the real gray value of an image pixel through addition and subtraction to cause interference of bright and dark points on the image, so that the image quality is greatly reduced, and the subsequent work is influenced. A filtering process is performed. For the selection of the filter, for each pre-weighted image, the filter parameters len, length, and the number of detector columns d =1.5 set to 2 times, b =0.07, the filter order and frequency are calculated for the corresponding gantry angle, the three-stage filter cutoff frequency response is calculated, the other half of the filter is formed according to symmetry, and finally, the combination of the half-hann filter and the half-ram-lak filter is formed. And carrying out back projection on the filtered image to obtain a mammary gland tomogram, and carrying out back projection on the filtered image according to parameters (detector row number, column number and projection number), reconstruction parameters (row number, column number and layer number), a projection matrix and geometric phantom offset of the filtered image.
As described in step S130 above, the "removing artifact from the three-dimensional reconstructed image" in step S130 can be further explained with reference to the following description, so as to obtain a reconstructed breast three-dimensional tomographic image. "is used herein.
And (3) segmenting the original mammographic image with different angles according to automatic threshold binarization to obtain a segmentation mask.
It should be noted that, according to the original mammographic image with different angles and the parameters (the number of detector lines, the number of columns, and the projection type) of the image, an automatic threshold binarization is used to obtain a segmentation mask, the automatic threshold binarization is used to determine whether the image is 0 or 1 by using a set threshold, the number of lines, the number of columns, and the number of projections of the segmentation mask are the same as those of the original mammographic image, the number of breast regions is 1, and the direct exposure region outside the breast is 0.
And performing three-dimensional reconstruction on the segmentation mask to obtain a reconstructed mask as described in the following steps.
As an example, the step processes the segmentation mask in the same way as the above-mentioned back projection processing on the filtered image, and processes the mask by a classical back projection algorithm to obtain the reconstructed mask.
And removing the artifacts of the three-dimensional reconstructed image according to the reconstructed mask to obtain a reconstructed breast three-dimensional tomographic image.
It should be noted that, according to the reconstruction result of the mask and the three-dimensional reconstructed image, traversing each row, each column, and each layer of the reconstructed image, comparing the reconstructed photographic image with the reconstructed mask, setting the position where the number of the reconstructed mask is smaller than that of the reconstructed photographic image to be 0, and leaving the rest positions to be unprocessed, thereby obtaining the three-dimensional tomographic image of the breast with the removed artifacts. The processing results are shown in fig. 2.
As described in step S140 above, the step S140 "of equalizing the brightness of the edge and the center of the reconstructed breast three-dimensional tomographic image to obtain the target breast three-dimensional tomographic image can be further described with reference to the following description. "is used in the specification.
It should be noted that, because the gland compression thickness is not uniform, and there is an edge region, the reconstructed edge and the internal brightness are not uniform at the window width level, and the edge is easily lost at the window width level, so that the edge and the central brightness equalization processing is performed on the reconstructed image, and the situation can be avoided.
And performing mask processing on the final reconstructed breast three-dimensional tomographic image, and performing median filtering processing on an image in a mask.
The mask processing is to set the reconstruction result outside the mask to 0, convert the image inside the mask to a value of 16Bit (0-65535) gray scale range to obtain a preprocessed image, and perform median filtering on the image inside the mask to obtain an I-original.
And performing coordinate conversion on Cartesian coordinates of the reconstructed breast three-dimensional sectional image to obtain polar coordinates of the image.
The cartesian coordinate values (x, y) are converted into polar coordinates (ρ, θ) whose center point is located at the chest muscle wall side center point.
And performing low-pass filtering processing and multi-resolution analysis processing on the reconstructed breast three-dimensional tomographic image to obtain a direct-current component image.
It should be noted that the area outside the mask is defined as Out, the area with large gradient change is defined as Margin, the rest area is defined as Central, the boundary between Margin and Central is innerEdge, the boundary between Margin and the outside is OuterEdge, and the straight Line from the center point of polar coordinates to each point of OuterEdge is defined as Line _ outEdge (i).
The low-pass filtering process is to keep the place with lower frequency in the image, and the low-pass filtering process can smooth the image, weaken the edge and eliminate the noise. And obtaining a direct current component (DC) image through resolution analysis processing. Converting Line _ outEdge (i) to DC _ Line _ outEdge (i), and recording the position of DC _ innerEdge on each Line.
And performing region processing on the direct current component image, replacing the direct current component image with the region processed image, and reconstructing to obtain a target breast three-dimensional tomographic image.
It should be noted that, for each straight Line of DC _ Line _ outEdge (i), the mean value from the starting point (polar center point) to DC _ innerEdge on the straight Line, target _ DC _ Line (i), is calculated. DC _ Line _ outEdge (i) the grayscale value for each point after Target _ DC _ Line DC _ outEdge (i) _ outEdge = DC _ Line _ outEdge (i) _ outEdge a + Target _ DC _ Li ne _ outEdge (i) _ b. Where a and b are constants, a is 0.3 and b is 0.7. After the processing, the processed image is replaced by the digital image decomposed by the pyramid, and the target breast three-dimensional tomographic image is obtained after reconstruction. The processing results are shown in fig. 3.
And as described in the following steps, carrying out slice processing on the reconstructed breast three-dimensional tomographic image according to 1-9 pixels, and carrying out equalization processing on all slices.
Before image post-processing, firstly, slicing the image according to 1-9 pixel intervals, and after the slicing processing, performing post-processing operation on all slices, wherein the slices are specifically according to the size of an actual image, the slice intervals are large, the processing time is short, and the image fineness is low; the slice interval is small, the processing time is long, and the picture fineness is high.
In one implementation, the images are sliced according to 3 pixel intervals, and the final reconstructed image is shown in fig. 3.
Referring to fig. 4, an embodiment of the present invention provides an apparatus for image processing for breast three-dimensional tomography, including:
s410, a correction module for acquiring original mammographic images at different angles and performing brightness correction on the original mammographic images to obtain corrected images at different angles;
s420, a reconstruction module for reconstructing the corrected images at different angles and performing two-dimensional to three-dimensional reconstruction on the images after the reconstruction;
s430, an artifact removing module, configured to perform artifact removing operation on the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional tomographic image;
and S440, a post-processing module, which is used for balancing the brightness of the edge and the center of the reconstructed breast three-dimensional tomographic image to obtain a target breast three-dimensional tomographic image.
In one embodiment, the corrective module S410 includes:
the correction table acquisition module is used for acquiring a dark field correction table and a bright field correction table;
and the brightness correction module is used for correcting the original mammary gland image according to the dark field correction table and the bright field correction table to obtain a corrected image.
In an embodiment, the reconstruction front-end module S420 includes:
the logarithm change module is used for carrying out logarithm transformation on the corrected image;
the pre-weighting module is used for pre-weighting the corrected image according to the inclination table, removing the influence of a light source and obtaining a pre-weighted image;
and the three-dimensional reconstruction module is used for performing three-dimensional reconstruction processing on the pre-weighted image.
In an embodiment, the artifact removing module S430 includes:
the segmentation mask module is used for segmenting the original mammographic images at different angles according to automatic threshold binarization to obtain segmentation masks;
the mask reconstruction module is used for performing three-dimensional reconstruction on the segmented mask to obtain a reconstructed mask;
and the mask artifact removing module is used for removing the artifact of the three-dimensional reconstructed image according to the reconstructed mask to obtain a reconstructed breast three-dimensional tomographic image.
In one embodiment, the mask deghost module includes:
and comparing the reconstructed breast three-dimensional tomographic image with the reconstructed mask, setting the position where the number of the reconstructed mask is smaller than that of the reconstructed photographic image to be 0, and not processing the rest positions to obtain the breast three-dimensional tomographic image with the removed artifacts.
In an embodiment, the post-processing module S440 includes:
the mask processing module is used for performing mask processing on the finally reconstructed breast three-dimensional tomographic image and performing median filtering processing on an image in a mask;
the coordinate conversion module is used for carrying out coordinate conversion on Cartesian coordinates of the reconstructed breast three-dimensional sectional image to obtain polar coordinates of the image;
the filtering processing module is used for carrying out low-pass filtering processing and multi-resolution analysis processing on the reconstructed breast three-dimensional tomographic image to obtain a direct-current component image;
and the region processing module is used for carrying out region processing on the direct current component image, replacing the direct current component image with the region processed image, and reconstructing to obtain a target breast three-dimensional tomographic image.
In an embodiment, the post-processing module S440 further includes:
and the slice processing module is used for carrying out slice processing on the reconstructed breast three-dimensional tomographic image according to 1-9 pixel intervals and carrying out equalization processing on all slices.
Referring to fig. 5, a computer device of an image processing method for breast three-dimensional tomography according to the present invention is shown, which may specifically include the following:
the computer device 12 described above is in the form of a general purpose computing device, and the components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (commonly referred to as "hard drives"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. The memory may include at least one program product having a set (e.g., at least one) of program modules 42, with the program modules 42 configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules 42, and program data, each of which examples or some combination thereof may include an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The processing unit 16 executes programs stored in the system memory 28 to perform various functional applications and data processing, such as implementing the method for enhancing artifact suppression for punctured images provided by embodiments of the present invention.
That is, the processing unit 16 implements, when executing the program,: an image processing method for breast three-dimensional tomography.
In an embodiment of the present invention, the present invention further provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements a method for enhancing artifacts in punctured image suppression as provided in all embodiments of the present application:
that is, the program when executed by the processor implements: an image processing method for breast three-dimensional tomography.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer-readable storage medium or a computer-readable signal medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPOM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the healthcare worker computer, partly on the healthcare worker computer, as a stand-alone software package, partly on the healthcare worker 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 healthcare worker's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). The embodiments in the present specification are all described in a progressive manner, and each embodiment focuses on differences from other embodiments, and portions that are the same and similar between the embodiments may be referred to each other.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.
Finally, it should also be 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 terminal 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 terminal. Without further limitation, an element defined by the phrases "comprising one of \ 8230; \8230;" does not exclude the presence of additional like elements in a process, method, article, or terminal device that comprises the element.
The image processing method, device and system for breast three-dimensional tomography provided by the present application are introduced in detail above, and specific examples are applied herein to illustrate the principle and implementation of the present application, and the description of the above embodiments is only used to help understand the method and core ideas of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. An image processing method for breast three-dimensional tomography, characterized by comprising the steps of:
acquiring original mammographic images at different angles, and performing brightness correction on the original mammographic images to obtain corrected images at different angles;
carrying out reconstruction preprocessing on the corrected images at different angles, and carrying out reconstruction processing of converting the preprocessed images into three dimensions from two dimensions;
removing the artifact of the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional sectional image;
and balancing the brightness of the edge and the center of the reconstructed mammary gland three-dimensional sectional image to obtain a target mammary gland three-dimensional sectional image.
2. The method according to claim 1, wherein said obtaining raw mammographic images at different angles and intensity correcting said raw mammographic images to obtain corrected images at different angles comprises the steps of:
acquiring a dark field correction table and a bright field correction table;
and correcting the original mammary gland image according to the dark field correction gauge and the bright field correction gauge to obtain a corrected image.
3. The method according to claim 1, wherein the reconstructing the corrected images at different angles is performed by a pre-processing, and the reconstructing of the pre-processed images is performed by a two-dimensional to three-dimensional reconstructing process, and the reconstructing process comprises:
carrying out logarithmic transformation on the corrected image;
pre-weighting the corrected image according to a slope table, and removing the influence of a light source to obtain a pre-weighted image;
and performing three-dimensional reconstruction processing on the pre-weighted image.
4. The method of claim 1, wherein said removing artifacts from said three-dimensional reconstructed image resulting in a reconstructed breast three-dimensional tomographic image comprises:
segmenting the original mammographic images with different angles according to automatic threshold binarization to obtain segmentation masks;
performing three-dimensional reconstruction on the segmentation mask to obtain a reconstructed mask;
and removing the artifact of the three-dimensional reconstructed image according to the reconstructed mask to obtain a reconstructed breast three-dimensional tomographic image.
5. The method of claim 4, wherein said removing artifacts from said reconstructed breast three-dimensional tomographic image according to said reconstructed mask comprises:
and comparing the three-dimensional reconstructed image with the reconstructed mask, setting the position of the reconstructed mask number smaller than the reconstructed photographic image number as 0, and leaving the rest positions unprocessed to obtain the reconstructed mammary gland three-dimensional tomographic image with the removed artifacts.
6. The method according to claim 1, wherein the step of equalizing the brightness of the edge and the center of the reconstructed breast three-dimensional tomographic image to obtain a target breast three-dimensional tomographic image comprises the steps of:
performing mask processing on the finally reconstructed breast three-dimensional tomographic image, and performing median filtering processing on the image in the mask;
carrying out coordinate conversion on the Cartesian coordinates of the reconstructed breast three-dimensional sectional image to obtain the polar coordinates of the image;
performing low-pass filtering processing and multi-resolution analysis processing on the reconstructed breast three-dimensional tomographic image to obtain a direct-current component image;
and carrying out regional processing on the direct current component image, replacing the direct current component image with the image processed by the region, and reconstructing to obtain a target breast three-dimensional tomographic image.
7. The method according to claim 6, wherein the step of masking the final reconstructed breast three-dimensional tomographic image and performing median filtering on the image within the mask is preceded by the step of:
and carrying out slice processing on the reconstructed breast three-dimensional tomographic image according to 1-9 pixel intervals, and carrying out equalization processing on all slices.
8. An apparatus for image processing for breast three-dimensional tomography, characterized in that the apparatus for breast three-dimensional tomosynthesis implements the steps of the image processing method for breast three-dimensional tomography of any of claims 1 to 7, comprising:
the correction module is used for acquiring original mammographic images at different angles and performing brightness correction on the original mammographic images to obtain corrected images at different angles;
the reconstruction module is used for reconstructing the corrected images at different angles and performing two-dimensional to three-dimensional reconstruction on the images after the pre-processing;
the artifact removing module is used for removing the artifact of the three-dimensional reconstructed image to obtain a reconstructed breast three-dimensional tomographic image;
and the post-processing module is used for balancing the brightness of the edge and the center of the reconstructed breast three-dimensional sectional image to obtain a target breast three-dimensional sectional image.
9. Electronic device, characterized in that it comprises a processor, a memory and a computer program stored on said memory and executable on said processor, said computer program, when being executed by said processor, implementing the steps of the image processing method for breast three-dimensional tomography according to any of claims 1 to 7.
10. Computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the image processing method for breast three-dimensional tomography as claimed in any one of claims 1 to 7.
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