TY - GEN
T1 - Low-dose X-ray computed tomography image reconstruction using edge sparsity regularization
AU - Luo, Shousheng
AU - Kang, Keke
AU - Wang, Yang
AU - Tai, Xue-Cheng
N1 - Funding Information:
Shousheng Luo was supported by the Programs for Science and Technology Development of He'nan Province (1921 02310181). Xue-Cheng Tai was supported by the startup grant at Hong Kong Baptist University, grants RG(R)-RC/17-18/02-MATH and FRG2/17-18/033. Yang Wang was supported in part by the Hong Kong Research Grant Council grants 16306415 and 16308518.
PY - 2019/8/24
Y1 - 2019/8/24
N2 - Total variation (TV) regularization is one of popular techniques for low dose x-ray computed tomography image reconstruction. However, the reconstruction image by TV method often suffers staircase effect. In this paper, we propose an edge sparsity model, which penalizes the difference between L1 norm and L2 norm of gradient, for low dose x-ray computed tomography image reconstruction. Alternating direction method of multipliers (ADMM) is adopted to solve the proposed model. Experiment results on simulation data and real data are presented to verify the effectiveness of the proposed method.
AB - Total variation (TV) regularization is one of popular techniques for low dose x-ray computed tomography image reconstruction. However, the reconstruction image by TV method often suffers staircase effect. In this paper, we propose an edge sparsity model, which penalizes the difference between L1 norm and L2 norm of gradient, for low dose x-ray computed tomography image reconstruction. Alternating direction method of multipliers (ADMM) is adopted to solve the proposed model. Experiment results on simulation data and real data are presented to verify the effectiveness of the proposed method.
KW - ADMM
KW - Edge sparsity regularization
KW - Low dose
KW - XCT image reconstruction
UR - http://www.scopus.com/inward/record.url?scp=85077542711&partnerID=8YFLogxK
U2 - 10.1145/3364836.3364898
DO - 10.1145/3364836.3364898
M3 - Conference proceeding
AN - SCOPUS:85077542711
T3 - ACM International Conference Proceeding Series
SP - 303
EP - 307
BT - ISICDM 2019 - Conference Proceedings
PB - Association for Computing Machinery (ACM)
T2 - 3rd International Symposium on Image Computing and Digital Medicine, ISICDM 2019
Y2 - 24 August 2019 through 26 August 2019
ER -