WO2018126434A1

WO2018126434A1 - Ct image shadow correction method and apparatus, and electronic device

Info

Publication number: WO2018126434A1
Application number: PCT/CN2017/070410
Authority: WO
Inventors: 梁晓坤; 张志诚; 谢耀钦
Original assignee: 深圳先进技术研究院
Priority date: 2017-01-06
Filing date: 2017-01-06
Publication date: 2018-07-12
Also published as: CN106780397A; CN106780397B

Abstract

A CT image shadow correction method and apparatus, and an electronic device (600). The CT image shadow correction method comprises: performing an image texture removal operation on an original CT reconstruction image to obtain a smoothed image (S101); performing, according to human tissue, segmentation processing on structural components of the original CT reconstruction image, and constructing a template image (S102); and performing shadow correction according to the smoothed image and the template image (S103). The method can reduce the loss of image space resolution and quickly correct the original CT reconstruction image.

Description

CT image shading correction method, device and electronic device

Technical field

The present invention relates to the field of image shading correction technology, and in particular, to a CT image shading correction method, apparatus and electronic device.

Background technique

In cone-beam CT (CBCT) scanning, due to the influence of scattering signal and beam hardening effect, low-frequency CT image shadows appear in reconstructed images. CT image shadows seriously affect the accuracy of CT values. And the spatial uniformity of the image. In the CBCT system without shadow correction, the CT image shading can cause the CT value error of the reconstructed image to exceed 350 HU, which brings errors to the positioning accuracy of the image-guided treatment and the diagnosis of the image, thus limiting the wide application of CBCT in the clinic. At present, CBCT is mainly used for preliminary positioning and radiotherapy placement, and further application in intervention and radiotherapy is limited. Therefore, CT image shading correction is one of the most important issues to improve CBCT image quality.

The currently known methods of shadow correction for CT images can be mainly divided into two categories: pre-processing and post-processing methods. The pre-processing method corrects the shadow of the CT image mainly by attaching hardware devices to prevent the scattered photons from reaching the detector, so that there is no scattered signal. The following are two typical methods for preprocessing shadow correction. The first is to increase the air gap between the object and the detector, and the second is to use an anti-scatter grid. As the air gap widens, the detected rate of diffused scattered photons decreases, while the source signal is unaffected. However, the first method is limited by the physical space of the CBCT device itself. The spatial distance cannot be increased wirelessly, and the geometric blurring of the image is increased while increasing the X-ray dose to compensate for the increase in distance. Not practical. The anti-scatter grid uses a grid of lead grids that are focused on the source to block scattered light at unfocused angles of incidence. The second method also has a defect that the attenuation efficiency of the scattered light is not high. At present, the commercial grid can only provide about 3 times the SPR reduction rate, and cannot guarantee the CBCT image quality in a high scattering environment. In addition, it also needs to increase the patient's exposure dose to compensate for the attenuation of the source ray intensity, and the clinical application value is not high.

Although the pretreatment method can directly prevent the scattered photons from reaching the detector, its limitations are more prominent, and the post-processing method is more practical. Post-processing refers to the estimation of the scattering distribution after the X-ray projection is acquired according to the original method, and the estimated scattering distribution is subtracted from the source projection, and the shading correction can be performed. Post-processing methods include: analytical modeling, Monte Carlo simulation, source modulation, measurement, based on prior data correction, polar coordinate based correction and adaptive iterative shadow correction. The analytical modeling method considers that the scattered signal is the sound of the source signal after passing through the scattering core. Should be, the calculation speed is very fast, but the corresponding scattering estimation accuracy is limited and cumbersome adjustment parameters are required for complex objects. Monte Carlo simulation is the "gold standard" for scatter estimation, but it is computationally intensive and time consuming. The source modulation method is to add a high frequency modulator between the x-ray source and the object, and separate them in the frequency domain according to different response characteristics of the scattering and source signals, but the method requires high precision in manufacturing the modulation board, The clinical application effect is limited by the actual physical factors; the measurement method is to insert a source ray blocker (usually a lead strip) between the x-ray source and the object, so that a shadow area containing only the scatter signal is formed on the detector, but The method is to change the hardware settings of the system, which is difficult to operate. Although the corrected image can be obtained better based on the prior data correction method, the method requires additional prior patient information in the radiotherapy, and thus cannot be used as a general solution for shading correction of the large-volume CT imaging system. The polar coordinate-based correction method estimates the shadow distribution of the CT image by the distribution characteristics of the shadow of the CT image in polar coordinates, but this method requires polar transformation and interpolation of the image, which takes a long time. The adaptive iterative shading correction method does not require a priori image information, but the method requires repeated pre-projection operations on the reconstructed image, and the calculation efficiency is low.

Summary of the invention

Embodiments of the present invention provide a CT image shading correction method, apparatus, and electronic device to reduce loss of image spatial resolution and quickly correct an original CT reconstructed image.

An embodiment of the present invention provides a CT image shadow correction method, including:

Performing an image texture removal operation on the original CT reconstructed image to obtain a smoothed image;

Performing segmentation processing on the structural components of the original CT reconstructed image according to human tissue, and constructing a template image;

Shadow correction is performed based on the smoothed image and the template image.

In an embodiment, the image texture removal operation is performed on the original CT reconstructed image to obtain a smooth image, including:

The original CT reconstructed image is edge-protected and the image texture is removed by using an L0 norm smoothing algorithm to obtain the smoothed image.

In an embodiment, the structural components of the original CT reconstructed image are segmented according to human tissue, and the template image is constructed, including:

Using the image segmentation method, the original CT reconstructed image is segmented into a plurality of human tissue regions;

The CT values of the corresponding tissue corresponding to the X-ray tube voltage are respectively filled in different human tissue regions to obtain the template image.

In an embodiment, the shading correction is performed according to the smoothed image and the template image, including:

Performing a difference between the smoothed image and the template image to obtain a residual image, where the residual image includes image shading and structural error;

Performing a low-pass filtering process on the structural error of the residual image to obtain a shadow distribution of the CT image;

The original CT reconstructed image is subjected to compensation processing using the CT image shadow distribution to obtain a corrected CT image.

In an embodiment, the low-pass filtering process is performed on the structural error of the residual image, including:

The tissue error of the residual image is low-pass filtered by a Savitzky-Golay local low-pass filter.

In an embodiment, performing image texture removal on the original CT reconstructed image by using an L0 norm smoothing algorithm, including:

The textureless smooth image is calculated by the objective function, which is as follows:

among them,

S _p is the p-th pixel index of the texture-free smooth image S, I _p is the p-th pixel index of the original CT reconstructed image I, and C(S) is

The number of pixel indices p, λ is the smoothing factor,

and

The partial derivative of the pixel index in both the x and y directions.

An embodiment of the present invention further provides a CT image shading correction apparatus, including:

a smooth image generating unit, configured to perform an image texture removing operation on the original CT reconstructed image to obtain a smooth image;

a template image construction unit, configured to perform segmentation processing on a structural component of the original CT reconstructed image according to human body tissue, and construct a template image;

And a correction unit configured to perform shading correction according to the smoothed image and the template image.

In an embodiment, the smooth image generating unit is specifically configured to:

In an embodiment, the template image construction unit includes:

a segmentation module, configured to segment the original CT reconstructed image into a plurality of human tissue regions by using an image segmentation method;

The stencil building module is configured to respectively fill the CT values of the corresponding tissue corresponding X-ray tube voltages in different human tissue regions to obtain the stencil image.

In an embodiment, the correction unit comprises:

a residual image construction module, configured to perform a difference image with the template image to obtain a residual image, where the residual image includes image shadows and organizational structure errors;

a low-pass filtering module, configured to perform low-pass filtering processing on the structural error of the residual image to obtain a shadow distribution of the CT image;

The compensation processing module is configured to perform compensation processing on the original CT reconstructed image by using the CT image shadow distribution to obtain a corrected CT image.

In an embodiment, the low pass filter module is specifically configured to:

An embodiment of the present invention further provides an electronic device, where the electronic device includes:

Processor; and

A memory comprising computer readable instructions that, when executed, cause the processor to:

In one embodiment, the instruction causes the processor to perform edge protection and image texture removal on the original CT reconstructed image by using an L0 norm smoothing algorithm to obtain the smoothed image.

In an embodiment, the instructions cause the processor to perform the following operations:

In one embodiment, the instructions cause the processor to perform a low pass filtering process on the tissue structure error of the residual image using a Savitzky-Golay local low pass filter.

The invention utilizes the edge-protected L0 norm smoothing algorithm to decompose the image into a structural image and a texture image, eliminates the texture information and performs subsequent processing without loss of image resolution. Segmentation of human tissue using image segmentation algorithms, An accurate reference image can be generated. Through the L0 norm smoothing algorithm, the detailed information of the image can be protected to the utmost, and the image spatial resolution loss is small. In addition, the present invention eliminates the need for a priori CT information, eliminates the need for front projection operations and polar coordinate conversion, and therefore has a faster calculation speed; it is fully compatible with the image-guided CBCT system of modern radiotherapy accelerators without changing other hardware and scanning protocols.

DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below. Obviously, the drawings in the following description are only It is a certain embodiment of the present invention, and other drawings can be obtained from those skilled in the art without any creative work.

1 is a flowchart of a CT image shading correction method according to an embodiment of the present invention;

2 is a schematic view showing the operation of an image shading correction method according to an embodiment of the present invention;

3 is a schematic diagram of smoothing and correcting images under different smoothing intensity factors λ according to an embodiment of the present invention;

4 is a schematic structural diagram of a CT image shading correction apparatus according to an embodiment of the present invention;

FIG. 5 is another schematic structural diagram of a CT image shading correction apparatus according to an embodiment of the present invention; FIG.

FIG. 6 is a schematic block diagram of a system configuration of an electronic device 600 according to an embodiment of the present invention.

detailed description

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

Example 1

The embodiment of the present invention provides a CT image shading correction method, and FIG. 1 is a flowchart of a CT image shading correction method according to an embodiment of the present invention. As shown in FIG. 1, the CT image shading correction method includes:

S101: Perform image texture removal operation on the original CT reconstructed image to obtain a smooth image.

S102: Perform segmentation processing on the structural components of the original CT reconstructed image according to human tissue, and construct a template image;

S103: Perform shading correction according to the smoothed image and the template image.

The execution body of the CT image shading correction method shown in FIG. 1 may be an electronic device, and the electronic device may be a desktop computer, a tablet computer, or the like, but the present invention is not limited thereto.

It can be seen from the flow shown in FIG. 1 that the present invention first performs an image texture removal operation on the original CT reconstructed image, and then performs a segmentation process on the original CT reconstructed image, and finally performs a shadow according to the smoothed image obtained by the de-texturing operation and the segmented template image. Correction can reduce the loss of image spatial resolution and quickly correct the original CT reconstructed image.

The texture of the image is a high frequency signal relative to the CT image shadow signal. In the image shading correction, in order to protect the image details without degrading the image spatial resolution, the original CT reconstructed image may be decomposed into textures and structures. For example, the original CT reconstructed image may be edge-protected by using the L0 norm smoothing algorithm. The image texture is removed to obtain the smoothed image.

The L0 norm smoothing algorithm with edge protection is as follows:

Let I be the original CT reconstructed image of the input, and S be the smooth image with no texture output.

Is the gradient of the image, where p is the pixel index of the image, and x and y are the coordinates of the horizontal and vertical directions of the image, respectively.

For a pixel index p, calculate the sum of the gradient differences in both the x and y directions as its gradient value, as shown in Equation 1:

Upper formula The number of pixel indices p.

According to the above definition, the untextured smooth image S can be obtained by the following objective function, see Equation 2:

In Equation 1 and Equation 2, ∑(SI) ² is the image structure similarity constraint, S _p is the p-th pixel index of the texture-free smooth image S, and I _p is the p-th pixel index of the original CT reconstructed image I, λ is the smoothing factor,

and

The partial derivative of the x and y in the two coordinate directions of the image is indexed for the pixel.

Because of the incomprehensibility of the L0 norm, the present invention divides the algorithm into two sub-problems to solve separately, and adopts a special alternating optimization strategy of semi-quadratic splitting to obtain an approximate optimal solution.

According to anatomical knowledge, the CT values of the same type of human tissue in CBCT images without artifacts should be basically the same, and therefore, the method of image segmentation can be utilized. The structural components in CT images can be divided into air, bone, soft tissue (such as muscle and fat), etc. Image segmentation method can be used to segment the original CT reconstructed image into multiple human tissue regions, that is, to segment different tissues of the human body. , fill the corresponding tissue with the corresponding tissue area in the corresponding X-ray The standard CT value at the line tube voltage produces a stencil image that can be used as a reference image for the shading correction process.

In one embodiment, the present invention may employ a multi-threshold image segmentation algorithm that separates the bone and soft tissue of the patient's head and assigns standard CT values.

The present invention needs to perform shading correction using a smooth image and a stencil image. Therefore, it is necessary to make the smooth image and the stencil image to be inferior to obtain a residual image, and the residual image includes image shading and a small amount of tissue structure error. Since the image shadow is mainly a low frequency signal, and the tissue structure is mainly a high frequency signal, a low pass filter can be used to eliminate the structural error and obtain a shadow distribution of the CT image.

Ordinary low-pass filtering eliminates errors in tissue structure, but the boundary contours of the anatomy are also filtered out, resulting in a severe loss of image contrast. In a preferred embodiment, the present invention uses a Savitzky-Golay local low pass filter to filter the residual image on the image domain. The low pass filter preserves the contour features and avoids the contrast resolution of the corrected loss image. .

After obtaining the shadow distribution of the CT image, the CT reconstructed image is compensated by the shadow distribution of the CT image, and the corrected CT image can be obtained.

FIG. 2 is a schematic diagram of the operation of the image shading correction method according to the embodiment of the present invention. The specific operation flow is described below with reference to FIG. 2 . As shown in FIG. 2, the L0 norm smoothing process and the image segmentation are respectively performed on the pre-correction image (original CT reconstructed image), and the L0 norm smoothing process is performed to obtain a textureless image (smooth image), and the image is segmented to obtain a template image. . The residual image can be obtained by smoothing the image and the template image, and the residual image can be low-pass filtered to obtain a shadow distribution image. Finally, the obtained shadow distribution image is superimposed with the pre-correction image (compensation processing) to obtain a corrected image, and image correction is completed.

Texture removal and edge protection are a pair of contradictions. The parameter selection of L0 norm smoothing algorithm affects the degree of image texture removal and the edge protection of tissue structure. Full image texture removal helps to preserve the detail retention of the corrected image without compromising the image resolution. Good edge protection helps to estimate the accuracy of image shadows and improve the contrast between the corrected image tissue. Therefore, in the L0 norm smoothing process, the selection of the smoothing intensity factor λ should be balanced between the two. Different λ selection affects the image. As shown in Fig. 3, the first line image of Fig. 3 is respectively an L0 norm smooth image under three different sizes λ, and the second line image of Fig. 3 is a corrected image under the corresponding λ. When λ is taken too small, as shown in the first column image of FIG. 3, insufficient texture removal results in the image information being included in the estimated shadow signal, and the shadow signal compensates for the corrected image loss image detail obtained from the original image. When λ is too large, as shown in the third column image of Fig. 3, the edge of the tissue structure is blurred due to the excessive smoothness, and the estimated shadow information contains structural information, so the corrected image tissue knot The contrast between the structures is reduced. When λ is taken as 0.01, a balance is obtained between texture removal and edge protection, while protecting the details of the image without reducing the contrast between the tissues.

The invention combines L0 norm smoothing with image segmentation to perform CT image shading correction, effectively eliminating image shading. Different from the existing methods, the method utilizes the edge-protected L0 norm smoothing algorithm to decompose the image into a structural image and a texture image, and eliminates the texture information and then performs subsequent processing without loss of image resolution. The invention successfully segmentes the human tissue using an accurate image segmentation algorithm and generates an accurate reference image. The CT image shading correction technology based on L0 norm smoothing and image segmentation has the following advantages in addition to the image shading correction effect:

1. The L0 norm smoothing maximizes the protection of the image details, and the image spatial resolution loss is small;

2. Compared with the existing correction algorithm, the invention does not need a priori CT information, does not require a front projection operation, does not require polar coordinate conversion, and has a faster calculation speed;

3. Fully compatible with the image-guided CBCT system of modern radiotherapy accelerators without changing other hardware and scanning protocols.

Example 2

Embodiment 2 of the present invention provides a CT image shading correction apparatus. The apparatus can be applied to the electronic apparatus in Embodiment 1. Since the principle of solving the problem is similar to the method of Embodiment 1, the specific implementation may refer to the implementation of the method of Embodiment 1, and the repeated description is not repeated.

4 is a schematic structural diagram of a CT image shading correction apparatus according to an embodiment of the present invention. As shown in FIG. 4, the CT image shading correction apparatus includes a smooth image generation unit 401, a template image construction unit 402, and a correction unit 403.

The smooth image generating unit 401 is configured to perform an image texture removing operation on the original CT reconstructed image to obtain a smoothed image;

The template image construction unit 402 is configured to perform segmentation processing on the structural components of the original CT reconstructed image according to human body tissue to construct a template image;

The correcting unit 403 is configured to perform shading correction according to the smoothed image and the template image.

In this embodiment, the smooth image generating unit 401 may be configured to perform edge protection and image texture removal on the original CT reconstructed image by using an L0 norm smoothing algorithm to obtain the smoothed image.

FIG. 5 is another schematic structural diagram of a CT image shading correction apparatus according to an embodiment of the present invention. The template image construction unit 402 includes a segmentation module 501 and a template construction module 502. The correcting unit 403 includes a residual image constructing module 503, a low pass filtering module 504, and a compensation processing module 505.

The segmentation module 501 is configured to segment the original CT reconstructed image into a plurality of human tissue regions by using an image segmentation method;

The stencil building module 502 is configured to respectively fill the CT values of the corresponding tissue corresponding X-ray tube voltages in different human tissue regions to obtain the stencil image.

The residual image construction module 503 is configured to perform the difference between the smoothed image and the template image to obtain a residual image, where the residual image includes image shadows and organizational structure errors;

The low-pass filtering module 503 is configured to perform low-pass filtering processing on the structural error of the residual image to obtain a CT image shadow distribution; the low-pass filtering module 503 may use the Savitzky-Golay local low-pass filter to perform the residual The organization error of the image is subjected to low-pass filtering.

The compensation processing module 504 is configured to perform compensation processing on the original CT reconstructed image by using the CT image shadow distribution to obtain a corrected CT image.

The apparatus of the embodiment uses the edge-protected L0 norm smoothing algorithm to decompose the image into a structural image and a texture image, and eliminates the texture information and performs subsequent processing without loss of image resolution. The image segmentation algorithm is used to segment the human tissue to generate an accurate reference image. Through the L0 norm smoothing algorithm, the detailed information of the image can be protected to the utmost, and the image spatial resolution loss is small. In addition, the present invention eliminates the need for a priori CT information, eliminates the need for front projection operations and polar coordinate conversion, and therefore has a faster calculation speed; it is fully compatible with the image-guided CBCT system of modern radiotherapy accelerators without changing other hardware and scanning protocols.

Example 3

The embodiment 3 provides an electronic device, which may be a desktop computer, a tablet computer, a mobile terminal, etc., and the embodiment is not limited thereto. In this embodiment, the electronic device may refer to the implementation of the method of Embodiment 1 and the apparatus described in Embodiment 2, and the content thereof is incorporated herein, and the details are not described again.

FIG. 6 is a schematic block diagram of a system configuration of an electronic device 600 according to an embodiment of the present invention. As shown in FIG. 6, the electronic device 600 can include a central processing unit 100 and a memory 140; the memory 140 is coupled to the central processing unit 100. It should be noted that the figure is exemplary; other types of structures may be used in addition to or in place of the structure to implement telecommunications functions or other functions.

In an embodiment, the CT image shading correction function can be integrated into the central processing unit 100. The central processing unit 100 may be configured to perform the following operations: performing an image texture removal operation on the original CT reconstructed image to obtain a smooth image; and performing segmentation processing on the structural components of the original CT reconstructed image according to human body tissue to construct a template image; Shadow correction is performed based on the smoothed image and the template image.

The image texture removal operation is performed on the original CT reconstructed image to obtain a smooth image, including: performing edge protection and image texture removal on the original CT reconstructed image by using a L0 norm smoothing algorithm to obtain the smoothed image.

The method for segmenting the structural components of the original CT reconstructed image according to the human body tissue, and constructing the template image comprises: dividing the original CT reconstructed image into a plurality of human tissue regions by using an image segmentation method; respectively, in different human bodies The tissue area is filled with the CT value of the corresponding tissue corresponding to the X-ray tube voltage to obtain the template image.

Performing shading correction according to the smoothed image and the template image includes: performing difference between the smoothed image and the template image to obtain a residual image, where the residual image includes image shading and organizational structure error; The structural error of the difference image is subjected to low-pass filtering processing to obtain a shadow distribution of the CT image; the original CT reconstructed image is compensated by the shadow distribution of the CT image to obtain a corrected CT image.

The low-pass filtering process is performed on the structural error of the residual image, including: performing a low-pass filtering process on the structural error of the residual image by using a Savitzky-Golay local low-pass filter.

The image texture removal is performed on the original CT reconstructed image by using an L0 norm smoothing algorithm, including:

among them,

S _p is the p-th pixel index of the texture-free smooth image S, and I _p is the p-th pixel index of the original CT reconstructed image I,

The number of pixel indices p, λ is the smoothing factor,

and

The partial derivative of the pixel index in both the x and y directions.

In another embodiment, the CT image shading correction device may be configured separately from the central processing unit 100. For example, the CT image shading correction device may be configured as a chip connected to the central processing unit 100, and the CT image is implemented by the control of the central processing unit. Shadow correction function.

As shown in FIG. 6, the electronic device 600 may further include: a communication module 110, an input unit 120, an audio processing unit 130, a display 160, and a power source 170. It should be noted that the electronic device 600 does not have to include all the components shown in FIG. 6; in addition, the electronic device 600 may further include components not shown in FIG. 6, and reference may be made to the prior art.

As shown in FIG. 6, central processor 100, also sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device that receives input and controls various components of electronic device 600. The operation of the part.

The memory 140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory, or other suitable device. The above-mentioned information related to the failure can be stored, and a program for executing the related information can be stored. And the central processing unit 100 can execute the program stored by the memory 140 to implement information storage or processing and the like.

Input unit 120 provides input to central processor 100. The input unit 120 is, for example, a button or a touch input device. The power source 170 is used to provide power to the electronic device 600. The display 160 is used to display a display object such as an image or a character. The display may be, for example, an LCD display, but is not limited thereto.

The memory 140 can be a solid state memory such as a read only memory (ROM), a random access memory (RAM), a SIM card, or the like. It is also possible to store a memory that can be selectively erased and provided with more data even when the power is turned off, and an example of the memory is sometimes referred to as an EPROM or the like. Memory 140 can also be some other type of device. Memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application/function storage section 142 for storing an application and a function program or a flow for executing an operation of the electronic device 600 by the central processing unit 100.

The memory 140 may also include a data storage portion 143 for storing data such as contacts, digital data, pictures, sounds, and/or any other data used by the electronic device. The driver storage portion 144 of the memory 140 may include various drivers for the communication function of the electronic device and/or for performing other functions of the electronic device such as a messaging application, an address book application, and the like.

The communication module 110 is a transmitter/receiver 110 that transmits and receives signals via the antenna 111. A communication module (transmitter/receiver) 110 is coupled to the central processing unit 100 to provide an input signal and receive an output signal, which may be the same as in the case of a conventional mobile communication terminal.

Based on different communication technologies, a plurality of communication modules 110, such as a cellular network module, a Bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 110 is also coupled to the speaker 131 and microphone 132 via the audio processor 130 to provide an audio output via the speaker 131 and to receive audio input from the microphone 132 to achieve the usual telecommunications functions. Audio processor 130 may include any suitable buffer, decoder, amplifier, or the like. In addition, the audio processor 130 is also coupled to the central processing unit 100 such that recording can be performed on the local unit through the microphone 132, and the sound stored on the local unit can be played through the speaker 131.

An embodiment of the present invention further provides a computer readable program, wherein when the program is executed in an electronic device, the program causes a computer to perform a CT image shading correction method as described in Embodiment 1 above in the electronic device .

The embodiment of the present invention further provides a storage medium storing a computer readable program, wherein the computer readable program causes the computer to perform the CT image shading correction described in Embodiment 1 above in the electronic device.

The preferred embodiments of the present invention have been described above with reference to the accompanying drawings. The many features and advantages of the embodiments are apparent from the detailed description and the appended claims. In addition, many modifications and changes may be made to the embodiments of the present invention, and the invention is not limited to the precise structure and operation illustrated and described. Things.

Those skilled in the art will appreciate that embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.

The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.

The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.

These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

The principles and embodiments of the present invention have been described in connection with the specific embodiments of the present invention. The description of the above embodiments is only for the understanding of the method of the present invention and the core idea thereof. At the same time, for those skilled in the art, according to the present invention The present invention is not limited by the scope of the present invention.

Claims

A CT image shading correction method, comprising:

Performing an image texture removal operation on the original CT reconstructed image to obtain a smoothed image;

Performing segmentation processing on the structural components of the original CT reconstructed image according to human tissue, and constructing a template image;

Shadow correction is performed based on the smoothed image and the template image.
The CT image shading correction method according to claim 1, wherein the image texture removal operation is performed on the original CT reconstructed image to obtain a smooth image, comprising:

The original CT reconstructed image is edge-protected and the image texture is removed by using an L0 norm smoothing algorithm to obtain the smoothed image.
The CT image shading correction method according to claim 1, wherein the structural component of the original CT reconstructed image is segmented according to human tissue, and the template image is constructed, including:

Using the image segmentation method, the original CT reconstructed image is segmented into a plurality of human tissue regions;

The CT values of the corresponding tissue corresponding to the X-ray tube voltage are respectively filled in different human tissue regions to obtain the template image.
The CT image shading correction method according to claim 1, wherein performing shading correction according to the smoothed image and the template image comprises:

Performing a difference between the smoothed image and the template image to obtain a residual image, where the residual image includes image shading and structural error;

Performing a low-pass filtering process on the structural error of the residual image to obtain a shadow distribution of the CT image;

The original CT reconstructed image is subjected to compensation processing using the CT image shadow distribution to obtain a corrected CT image.
The CT image shading correction method according to claim 4, wherein the low-pass filtering processing is performed on the structural error of the residual image, including:

The tissue error of the residual image is low-pass filtered by a Savitzky-Golay local low-pass filter.
The CT image shading correction method according to claim 2, wherein the image texture removal is performed on the original CT reconstructed image by using a L0 norm smoothing algorithm, including:

The textureless smooth image is calculated by the objective function, which is as follows:

among them,

S p is the p-th pixel index of the texture-free smooth image S, I p is the p-th pixel index of the original CT reconstructed image I, and C(S) is
The number of pixel indices p, λ is the smoothing factor,
and
The partial derivative of the pixel index in both the x and y directions.
A CT image shading correction device, comprising:

a smooth image generating unit, configured to perform an image texture removing operation on the original CT reconstructed image to obtain a smooth image;

a template image construction unit, configured to perform segmentation processing on a structural component of the original CT reconstructed image according to human body tissue, and construct a template image;

And a correction unit configured to perform shading correction according to the smoothed image and the template image.
The CT image shading correction apparatus according to claim 7, wherein the smooth image generating unit is specifically configured to:

The original CT reconstructed image is edge-protected and the image texture is removed by using an L0 norm smoothing algorithm to obtain the smoothed image.
The CT image shading correction apparatus according to claim 7, wherein the template image construction unit comprises:

a segmentation module, configured to segment the original CT reconstructed image into a plurality of human tissue regions by using an image segmentation method;

The stencil building module is configured to respectively fill the CT values of the corresponding tissue corresponding X-ray tube voltages in different human tissue regions to obtain the stencil image.
The CT image shading correction apparatus according to claim 7, wherein the correction unit comprises:

a residual image construction module, configured to perform a difference image with the template image to obtain a residual image, where the residual image includes image shadows and organizational structure errors;

a low-pass filtering module, configured to perform low-pass filtering processing on the structural error of the residual image to obtain a shadow distribution of the CT image;

The compensation processing module is configured to perform compensation processing on the original CT reconstructed image by using the CT image shadow distribution to obtain a corrected CT image.
The CT image shading correction apparatus according to claim 10, wherein the low pass filter module is specifically configured to:

The tissue error of the residual image is low-pass filtered by a Savitzky-Golay local low-pass filter.
An electronic device comprising:

Processor; and

A memory comprising computer readable instructions that, when executed, cause the processor to:

Performing an image texture removal operation on the original CT reconstructed image to obtain a smoothed image;

Performing segmentation processing on the structural components of the original CT reconstructed image according to human tissue, and constructing a template image;

Shadow correction is performed based on the smoothed image and the template image.
The electronic device according to claim 12, wherein the instruction causes the processor to perform edge protection and image texture removal on the original CT reconstructed image by using an L0 norm smoothing algorithm to obtain the smoothed image.
The electronic device of claim 12 wherein said instructions cause said processor to:

Using the image segmentation method, the original CT reconstructed image is segmented into a plurality of human tissue regions;

The CT values of the corresponding tissue corresponding to the X-ray tube voltage are respectively filled in different human tissue regions to obtain the template image.
The electronic device of claim 12 wherein said instructions cause said processor to:

Performing a difference between the smoothed image and the template image to obtain a residual image, where the residual image includes image shading and structural error;

Performing a low-pass filtering process on the structural error of the residual image to obtain a shadow distribution of the CT image;

The original CT reconstructed image is subjected to compensation processing using the CT image shadow distribution to obtain a corrected CT image.
The electronic device of claim 15, wherein the instructions cause the processor to perform a low pass filtering process on the tissue structure error of the residual image using a Savitzky-Golay local low pass filter.