title: Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging.
abstract: In dynamic Positron Emission Tomography (PET), an estimate of the radio activity concentration is obtained from a series of frames of sinogram data taken at ranging in duration from 10 seconds to minutes under some criteria. So far, all the well-known reconstruction algorithms require known data statistical properties. It limits the speed of data acquisition, besides, it is unable to afford the separated information about the structure and the variation of shape and rate of metabolism which play a major role in improving the visualization of contrast for some requirement of the diagnosing in application. This paper presents a novel low rank-based activity map reconstruction scheme from emission sinograms of dynamic PET, termed as SLCR representing Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging. In this method, the stationary background is formulated as a low rank component while variations between successive frames are abstracted to the sparse. The resulting nuclear norm and l1 norm related minimization problem can also be efficiently solved by many recently developed numerical methods. In this paper, the linearized alternating direction method is applied. The effectiveness of the proposed scheme is illustrated on three data sets.
authors.affiliation: State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Xingjian
authors.initials: X
authors.lastname: Yu
authors.affiliation: State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Shuhang
authors.initials: S
authors.lastname: Chen
authors.affiliation: State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Zhenghui
authors.initials: Z
authors.lastname: Hu
authors.affiliation: Department of Mathematics, University of Florida, Gainesville, Florida, United States of America.
authors.forename: Meng
authors.initials: M
authors.lastname: Liu
authors.affiliation: Department of Mathematics, University of Florida, Gainesville, Florida, United States of America.
authors.forename: Yunmei
authors.initials: Y
authors.lastname: Chen
authors.affiliation: B. Thomas Golisano College of Computing and Information Sciences, Rochester Institute of Technology One Lomb Memorial Drive, Rochester, New York, United States of America.
authors.forename: Pengcheng
authors.initials: P
authors.lastname: Shi
authors.affiliation: State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Huafeng
authors.initials: H
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography / Q000379:methods*