Edge-detecting operator-based selection of Huber regularization threshold for low-dose computed tomography imaging
10.3969/j.issn.1673-4254.2015.03.12
- VernacularTitle:基于边缘检测算子的Huber正则化阈值选择方法在低剂量CT重建中的应用
- Author:
Shanli ZHANG
1
;
Hua ZHANG
;
Debin HU
;
Dong ZENG
;
Zhaoying BIAN
;
Lijun LU
;
Jianhua MA
;
Jing HUANG
Author Information
1. 南方医科大学生物医学工程学院
- Keywords:
low-dose CT;
iterative reconstruction;
Huber regularization;
threshold choice
- From:
Journal of Southern Medical University
2015;(3):375-379
- CountryChina
- Language:Chinese
-
Abstract:
Objective To compare two methods for threshold selection in Huber regularization for low-dose computed tomography imaging. Methods Huber regularization-based iterative reconstruction (IR) approach was adopted for low-dose CT image reconstruction and the threshold of Huber regularization was selected based on global versus local edge-detecting operators. Results The experimental results on the simulation data demonstrated that both of the two threshold selection methods in Huber regularization could yield remarkable gains in terms of noise suppression and artifact removal. Conclusion Both of the two methods for threshold selection in Huber regularization can yield high-quality images in low-dose CT image iterative reconstruction.
