title: Tensor-based dictionary learning for dynamic tomographic reconstruction.
abstract: In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction.
authors.affiliation: Beijing Key Laboratory of Nuclear Detection & Measurement Technology, Beijing 100084, People's Republic of China. Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, People's Republic of China.
authors.forename: Shengqi
authors.initials: S
authors.lastname: Tan
authors.forename: Yanbo
authors.initials: Y
authors.lastname: Zhang
authors.forename: Ge
authors.initials: G
authors.lastname: Wang
authors.forename: Xuanqin
authors.initials: X
authors.lastname: Mou
authors.forename: Guohua
authors.initials: G
authors.lastname: Cao
authors.forename: Zhifang
authors.initials: Z
authors.lastname: Wu
authors.forename: Hengyong
authors.initials: H
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D000818:Animals; D006321:Heart / Q000000981:diagnostic imaging; D016018:Least-Squares Analysis; D051379:Mice; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012756:Sheep; D012815:Signal Processing, Computer-Assisted; D014057:Tomography, X-Ray Computed / Q000379:methods*