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Shearlet Transform Method for Medical CT Image Denoising Based on Fast Nonlocal Mean and 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 clear steps, perfect theoretical support, and simple structure

Active Publication Date: 2021-11-23
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.

Method used

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  • Shearlet Transform Method for Medical CT Image Denoising Based on Fast Nonlocal Mean and TV-L1 Model
  • Shearlet Transform Method for Medical CT Image Denoising Based on Fast Nonlocal Mean and TV-L1 Model
  • Shearlet Transform Method for Medical CT Image Denoising Based on Fast Nonlocal Mean and 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

The shearlet transform medical CT image denoising method based on the fast non-local mean value and TV-L1 model comprises the following steps: step 1) establishing a medical CT image model; step 2) performing shearlet transform multi-scale and multi-direction on the image Decompose to obtain a low-frequency subband and multiple high-frequency subbands; step 3) use the TV‑L1 model to decompose the image into cartoon and texture parts, and take the mixed image of the low-frequency subband and cartoon; step 4) apply the integral to the mixed image The fast non-local mean value denoising obtained by image technology acceleration obtains a new low-frequency subband; step 5) performs threshold shrinkage processing on the shear wave coefficients of the high frequency subband; step 6) performs shear wave inverse on the processed coefficients Transform to obtain the denoised medical CT image. The present invention is compared with the traditional denoising field algorithm through experimental analysis, and is effectively applied in the field of medical CT denoising, which can better facilitate the analysis and diagnosis of physicians.

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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Patent Type & Authority Patents(China)
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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