Edge-detecting operator-based selection of Huber regularization threshold for low-dose computed tomography imaging
ZHANG Shanli
ZHANG Hua
HU Debin
ZENG Dong
BIAN Zhaoying
LU Lijun
MA Jianhua
HUANG Jing
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.
Keywords：low-dose CTiterative reconstructionHuber regularizationthreshold choice
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 375-379 )