Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares

	Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares
	Zhang, C.; T. Zhang; M. Li; C. T. Peng; Z. B. Liu and J. Zheng
	2016
发表期刊	Biomedical Engineering Online
卷号	15
摘要	We propose a novel three-dimensional (3D) ghost imaging method using unfocused ultrasonic transducer, where the transducer is used as the bucket detector to collect the total photoacoustic signal intensity from spherical surfaces with different radius circling the transducer. This collected signal is a time sequence corresponding to the optic absorption information on the spherical surfaces, and the values at the same moments in all the sequences are used as the bucket signals to restore the corresponding spherical images, which are assembled as the object 3D reconstruction. Numerical experiments show this method can effectively accomplish the 3D reconstruction and by adding up each sequence on time domain as a bucket signal it can also realize two dimensional (2D) ghost imaging. The influence of the measurement times on the 3D and 2D reconstruction is analyzed with Peak Signal to Noise Ratio (PSNR) as the yardstick, and the transducer as a bucket detector is also discussed. (C) 2016 Elsevier B.V. All rights reserved.
文章类型	期刊
收录类别	SCI ; EI
语种	英语
WOS记录号	BMC:10.1186/s12938-016-0193-y
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/57401
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Zhang, C.,T. Zhang,M. Li,et al. Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares[J]. Biomedical Engineering Online,2016,15.
APA	Zhang, C.,T. Zhang,M. Li,C. T. Peng,&Z. B. Liu and J. Zheng.(2016).Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares.Biomedical Engineering Online,15.
MLA	Zhang, C.,et al."Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares".Biomedical Engineering Online 15(2016).

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