Robust deconvolution for low-dose CT myocardial perfusion imaging(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2017年第11期
- Page:
- 1131-1136
- Research Field:
- 医学影像物理
- Publishing date:
Info
- Title:
- Robust deconvolution for low-dose CT myocardial perfusion imaging
- Author(s):
- CHEN Weiguo; HE Jiexin; MO Tianlan; BIAN Zhaoying
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
- Keywords:
- Keywords: low-dose CT; myocardial perfusion imaging; deconvolution; low-rank and sparsity
- PACS:
- R318
- DOI:
- DOI:10.3969/j.issn.1005-202X.2017.11.010
- Abstract:
- Abstract: A robust deconvolution algorithm was proposed for improving the low-dose CT myocardial perfusion imaging. Considering the correlation and redundancy of blood flow signals in the CT myocardial perfusion images, we introduced a low-rank and sparsity regularization in the proposed algorithm to enhance the robustness of the deconvolution model. The experimental results of the low-dose CT simulated XCAT myocardial perfusion show that compared with those existing methods, the proposed algorithm not only effectively suppresses the noise and artifacts in the myocardial perfusion image, but also preserves the diagnostic information of myocardial ischemia, providing better quantitative images for the diagnosis of myocardial ischemia.
Last Update: 2017-11-23