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CT image denoising method based on wavelet transformation

A technology of CT image and wavelet transformation, which is applied in the field of medical image processing and image signal processing, can solve problems such as CT image interference, and achieve the effect of no fixed deviation, obvious shrinkage effect, and good adaptability

Active Publication Date: 2021-08-06
BEIJING INSTITUTE OF TECHNOLOGYGY +2
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

CT images are interfered by Gaussian noise during transmission and acquisition

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  • CT image denoising method based on wavelet transformation
  • CT image denoising method based on wavelet transformation
  • CT image denoising method based on wavelet transformation

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Embodiment Construction

[0051] The present invention will be described in detail below according to the accompanying drawings and examples, but the specific implementation of the present invention is not limited thereto.

[0052] This example illustrates the denoising process of the present invention applied to Gaussian noise in chest CT images of COVID-19. Embodiments of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0053] figure 1 For the overall flowchart of the algorithm of the present invention, a kind of CT image denoising method of wavelet transform comprises the following steps:

[0054] Step A, select the db5 wavelet basis function to perform wavelet decomposition on the CT image containing Gaussian noise.

[0055] Step B, performing multi-scale wavelet transform on the wavelet decomposition coefficients of the noisy image. After wavelet decomposition, different subband coefficients are obtained respectively: wavelet coefficien...

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Abstract

The invention discloses a CT image denoising method based on wavelet transformation, belongs to the technical field of medical image processing, and is particularly suitable for CT image denoising of new crown pneumonia. The CT image is susceptible to the interference of Gaussian noise in the transmission and acquisition process, and the wavelet transform can effectively remove the interference of the Gaussian noise. In order to solve the problems that early-stage lesions of a new crown CT image are not obvious in change, the number of the lesions is small, the range of the lesions is small, the density is low, and missed diagnosis of early-stage new crown patients is easily caused, the contrast ratio of the new crown lesions is improved, namely, an arc tangent improved self-adaptive wavelet threshold function of index adjustment and an improved threshold based on contraction factors are provided; the arc tangent function changes quickly near the zero point and changes slowly away from the zero point, the exponential function is adjusted to adapt to different layer threshold functions, more high-frequency detail information in the lung CT image is obtained, the detail edge is reserved, and fuzziness is reduced. The selection of wavelet threshold function parameters is a key factor for determining distortion and errors after image denoising, and the optimal adjustment parameters are searched through the improved particle swarm optimization of sine and cosine fusion normal distribution, so that the threshold optimization effect is greatly improved.

Description

technical field [0001] The invention relates to the technical field of image signal processing, in particular to a wavelet transform CT image denoising method based on an improved threshold function, which is suitable for filtering and processing of pneumonia CT images, especially suitable for the denoising of CT images of new coronary pneumonia, and belongs to medical image processing technology field. Background technique [0002] The lesions of COVID-19 are characterized by various forms of ground-glass opacity, or accompanied by consolidation. CT images are disturbed by Gaussian noise during transmission and acquisition. Digital image wavelet transform is a new method of processing images using mathematical methods. It is a problem of numerical approximation. The parent function is expanded and translated to a new function space, and the best approximation method is found according to the criteria, so as to realize the original image information and The distinction of ...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T5/10G06N3/00
CPCG06T5/10G06N3/006G06T2207/10081G06T2207/20064G06T2207/20081G06T2207/30061G06T5/70
Inventor 郭树理王国威韩丽娜宋晓伟杨文涛
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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