Image reconstruction from few-view CT data by gradient-domain dictionary learning

	Image reconstruction from few-view CT data by gradient-domain dictionary learning
	Hu, Zhanli; Liu, Qiegen; Zhang, Na; Zhang, Yunwan; Peng, Xi; Wu, Peter Z.; Zheng, Hairong; Liang, Dong
刊名	JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY
	2016
英文摘要	BACKGROUND: Decreasing the number of projections is an effective way to reduce the radiation dose exposed to patients in medical computed tomography (CT) imaging. However, incomplete projection data for CT reconstruction will result in artifacts and distortions. OBJECTIVE: In this paper, a novel dictionary learning algorithm operating in the gradient-domain (Grad-DL) is proposed for few-view CT reconstruction. Specifically, the dictionaries are trained from the horizontal and vertical gradient images, respectively and the desired image is reconstructed subsequently from the sparse representations of both gradients by solving the least-square method. METHODS: Since the gradient images are sparser than the image itself, the proposed approach could lead to sparser representations than conventional DL methods in the image-domain, and thus a better reconstruction quality is achieved. RESULTS: To evaluate the proposed Grad-DL algorithm, both qualitative and quantitative studies were employed through computer simulations as well as real data experiments on fan-beam and cone-beam geometry. CONCLUSIONS: The results show that the proposed algorithm can yield better images than the existing algorithms.
收录类别	SCI
原文出处	http://www.ncbi.nlm.nih.gov/pubmed/27232200
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/10471]
专题	深圳先进技术研究院_医工所
作者单位	JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY
推荐引用方式 GB/T 7714	Hu, Zhanli,Liu, Qiegen,Zhang, Na,et al. Image reconstruction from few-view CT data by gradient-domain dictionary learning[J]. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY,2016.
APA	Hu, Zhanli.,Liu, Qiegen.,Zhang, Na.,Zhang, Yunwan.,Peng, Xi.,...&Liang, Dong.(2016).Image reconstruction from few-view CT data by gradient-domain dictionary learning.JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY.
MLA	Hu, Zhanli,et al."Image reconstruction from few-view CT data by gradient-domain dictionary learning".JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY (2016).