TY - GEN
T1 - Iterative image reconstruction for ultra-low-dose CT with a combined low-mAs and sparse-view protocol
AU - Zhang, Yunwan
AU - Huang, Jing
AU - Ma, Jianhua
AU - Zhang, Hua
AU - Bian, Zhaoying
AU - Zeng, Dong
AU - Gao, Yang
AU - Chen, Wufan
PY - 2013
Y1 - 2013
N2 - Ultra-low-dose x-ray computed tomography (CT) imaging is needed in CT fields. Through a scan protocol by lowering the milliampere-seconds (mAs) and reducing the number of projections per rotation around the body, we can realize low-dose CT imaging. However, the resulting noisy and insufficient measurements will unavoidably cause the degradation of desired-image. To solve this problem, iterative image reconstruction is a promising choice for achieving high-quality image with a low-dose scan. In this study, we are focusing on ultra-low-dose CT image reconstruction by using penalized weighted least-square (PWLS) criteria with a combined low-mAs and sparse-view protocol. Specifically, the sinogram data acquired with a combined low-mAs and sparse-view protocol is first restored by using a PWLS based sinogram restoration method. Then, the restored sinogram data is hereafter used to reconstruct image by using a PWLS based total variation (PWLS-TV) method. Qualitative and quantitative evaluations by simulations were carried out to validate the present method.
AB - Ultra-low-dose x-ray computed tomography (CT) imaging is needed in CT fields. Through a scan protocol by lowering the milliampere-seconds (mAs) and reducing the number of projections per rotation around the body, we can realize low-dose CT imaging. However, the resulting noisy and insufficient measurements will unavoidably cause the degradation of desired-image. To solve this problem, iterative image reconstruction is a promising choice for achieving high-quality image with a low-dose scan. In this study, we are focusing on ultra-low-dose CT image reconstruction by using penalized weighted least-square (PWLS) criteria with a combined low-mAs and sparse-view protocol. Specifically, the sinogram data acquired with a combined low-mAs and sparse-view protocol is first restored by using a PWLS based sinogram restoration method. Then, the restored sinogram data is hereafter used to reconstruct image by using a PWLS based total variation (PWLS-TV) method. Qualitative and quantitative evaluations by simulations were carried out to validate the present method.
UR - https://www.scopus.com/pages/publications/84886579928
U2 - 10.1109/EMBC.2013.6610697
DO - 10.1109/EMBC.2013.6610697
M3 - 会议稿件
C2 - 24110884
AN - SCOPUS:84886579928
SN - 9781457702167
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 5107
EP - 5110
BT - 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
T2 - 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Y2 - 3 July 2013 through 7 July 2013
ER -