A shear wave transformation medical CT image denoising method based on a fast non-local mean value and a TV-L1 model

A non-local mean, TV-L1 technology, applied in the field of medical image denoising, can solve problems such as accurate diagnosis and interference, and achieve the effect of good image edge information

Active Publication Date: 2019-04-09
ZHEJIANG UNIV OF TECH
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Problems solved by technology

For clinicians, speckle noise has caused great interference to their accurate diagnosis, especially for doctors who are not very experienced.

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  • A shear wave transformation medical CT image denoising method based on a fast non-local mean value and a TV-L1 model
  • A shear wave transformation medical CT image denoising method based on a fast non-local mean value and a TV-L1 model
  • A shear wave transformation medical CT image denoising method based on a fast non-local mean value and a TV-L1 model

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Embodiment Construction

[0059] The present invention will be further described below in conjunction with the accompanying drawings.

[0060] The shearlet transform medical CT image denoising method based on fast non-local mean value and TV-L1 model of the present invention comprises the following steps:

[0061] Step 1) establishes the model of medical CT image;

[0062] Computed tomography uses X-rays to scan human body parts from multiple different angles and orientations, and then the computer processes different cross-sections to obtain reconstructed images, allowing users to see the scanned objects in a specific area. The low-intensity emission current will produce Gaussian noise enough to affect the observation and judgment, reducing the image quality of the generated image.

[0063] The model of CT image is mainly composed of two parts, namely effective human tissue reflection signal and invalid noise signal, and noise signal includes multiplicative noise and additive noise, among which addit...

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Abstract

A shear wave transformation medical CT image denoising method based on a fast non-local mean value and a TV-L1 model comprises the following steps: 1) establishing a medical CT image model; 2) performing shear wave transformation multi-scale and multi-direction decomposition on the image to obtain a low-frequency sub-band and a plurality of high-frequency sub-bands; Step 3) using TV-L1 model to decompose the image into a cam part and a text part, and takes a low-frequency sub-band and the cam part to obtain a mixed image; 4) performing fast non-local mean denoising on the mixed image by usingan integral image technology to obtain a new low-frequency sub-band; 5) performing threshold shrinkage processing on the shear wave coefficient of the high-frequency sub-band; 6) performing inverse shear wave transformation on the processed coefficients to obtain a decongested medical CT image; experimental analysis is compared with a traditional de-noising field algorithm, the method is effectively applied to the field of medical CT de-noising, and analysis and diagnosis of doctors can be better facilitated.

Description

technical field [0001] The present invention relates to the field of medical image denoising, in particular to medical CT images, in particular to a shearlet transform medical CT image denoising method based on fast non-local mean and TV-L1 model suitable for medical CT images. Background technique [0002] With the development of science and technology, in the field of medical imaging, imaging technologies such as ultrasound imaging, CT, and MRI have been applied in medical clinical diagnosis. Computed Tomography (Computed Tomography, also known as "Computed Tomography", referred to as CT), is a diagnostic imaging examination. This technique was once known as Computed Axial Tomography (Computed AxialTomography). Computed tomography, which uses a computer to process a combination of many x-ray measurements of specific areas of an object, creates cross-sections from different angles, allowing the user to see the inside of the object without cuts. Since the CT imaging techno...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T5/10
CPCG06T5/10G06T2207/10081G06T5/70
Inventor 张聚陈坚吕金城周海林
Owner ZHEJIANG UNIV OF TECH
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