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Low-dose CT projection domain denoising method based on composite regularization

A low-dose, projection technology, applied in image enhancement, image analysis, instruments, etc., can solve problems such as excessive smoothing, no consideration of image texture structure, loss of boundary texture details, etc., to achieve good texture details, significant denoising effect, The smoothness of the section line is good

Pending Publication Date: 2021-10-01
JILIN NORMAL UNIV
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Problems solved by technology

However, because this method does not consider the image texture structure, the edge information of the rec

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  • Low-dose CT projection domain denoising method based on composite regularization
  • Low-dose CT projection domain denoising method based on composite regularization
  • Low-dose CT projection domain denoising method based on composite regularization

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specific Embodiment 2

[0191] Use the numerical XCAT phantom to verify the proposed method. For the existing noise-free projection data, refer to the simulation method of Zeng and La Riviere to generate low-dose projection data, which is equivalent to the projection with a scanning voltage of 80kVp and a tube current of 20mA. Data dependent noise level. The simulated CT imaging parameters are the same as those of the clinical Siemens SOMATOM Sensation16CT scanner, as shown in Table 1. Generated numerical XCAT phantom images such as figure 1 shown. The main hardware devices used in the experiment include Intel Xeon E5-1620 central processing unit, NVIDIA GTX 1080Ti graphics processor and 64GB internal memory, and the software operating environment is Matlab 2016 under Windows 10.

[0192] Table 1 Simulation CT imaging parameters

[0193]

[0194] The images reconstructed after denoising by different methods are as follows: figure 2 shown. figure 2 (a) is the original image, figure 2 (b) i...

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Abstract

The invention discloses a low-dose CT projection domain denoising method based on composite regularization, and the method comprises the steps: employing a non-convex penalty function to enhance the sparsity of wavelet transformation based on a second-order fully generalized variational regularization method, and establishing a wavelet-TGV denoising model based on the non-convex penalty function for a projection domain; establishing a logarithmic penalty function, and performing wavelet-TGV denoising; adopting a split augmented Lagrange shrinkage algorithm, and finding an optimal solution of wavelet-TGV denoising; and inputting projection data, and reconstructing a CT image by using a filtered back projection algorithm. Most noise and strip artifacts are removed from the reconstructed image on the premise of keeping edge and texture detail information. The method has obvious noise reduction and artifact removal effects on low-dose CT images.

Description

technical field [0001] The invention relates to the technical field of low-dose CT image denoising, in particular to a low-dose CT projection domain denoising method based on compound regularization. Background technique [0002] As one of the most commonly used medical imaging equipment, CT can provide high-resolution medical images and provide a strong basis for clinical diagnosis and treatment. Since high doses of X-ray ionizing radiation can cause damage to the body tissues of patients and radiologists, and increase the probability of cancer in human cells, how to reduce the dose of ionizing radiation and reduce the noise of CT reconstruction images at lower radiation doses to Obtaining high-quality images for clinical diagnosis is an important research area. From the perspective of the three main factors affecting the radiation dose of CT, namely tube current, slice scanning time and peak voltage, reducing the tube current is the most simple and direct method, but the ...

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/10081
Inventor 张伟于萍周伟张佳铮纪晓晗季佳奇
Owner JILIN NORMAL UNIV
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