Self-Adaptive Iterative Step Approach to Noise Reduction in Low-Dose CT Images

被引：0

作者：

Zhang, Wei ^{[1
,2
]}

Mao, Baolin ^{[2
]}

Chen, Xiaozhao ^{[2
]}

Wang, Luyang ^{[2
]}

Fan, Shengyu ^{[2
]}

Kang, Yan ^{[2
]}

机构：

[1] Jilin Normal Univ, Comp Sch, Siping 136000, Peoples R China

[2] Northeastern Univ, Sinodutch Biomed & Informat Engn Sch, Shenyang 110169, Peoples R China

来源：

JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS | 2017年 / 7卷 / 01期

关键词：

Image Deno sing; CT Image; Projection Data; Total Variation; Adaptive Iteration; RAY COMPUTED-TOMOGRAPHY; SINOGRAM DATA; RECONSTRUCTION;

D O I：

10.1166/jmihi.2017.2005

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This study presents a projection field noise reduction approach to for low -dose CT images based on a self adaptive iterative step algorithm. The self -adaptive gradient descending step is determined based on the noise variance of the projection data. In addition, iterative noise reduction is achieved with an isotropic total variation gradient descending approach. The results indicate that the proposed approach achieved significant noise reduction in the reconstructed image while maintaining the boundary information. Therefore, the proposed approach could be used to effectively reduce noise in low -dose CT images.

引用

页码：194 / 196

页数：3

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