title: A general region-of-interest image reconstruction approach with truncated Hilbert transform.
abstract: This paper presents a novel data sufficiency condition that unique and stable ROI reconstruction can be achieved from a more flexible family of data sets. To the interior problem, it allows the ROI (Region-of-interest) can be reconstructed from the line integrals passing through this ROI and a small region B located anywhere as long as the image is known on B. Especially, ROI reconstruction can be achieved without any other a priori knowledge when region B is placed outside the object support. We also develop a general reconstruction algorithm with the DBP-POCS (Differentiated backprojection-projection onto convex sets) method. Finally, both numerical and real experiments were done to illustrate the new data sufficiency condition and the good stability of the ROI reconstruction algorithm.
authors.affiliation: Department of Engineering Physics, Tsinghua University, Beijing, China. liliang02@mails.tsinghua.edu.cn
authors.forename: Liang
authors.initials: L
authors.lastname: Li
authors.forename: Kejun
authors.initials: K
authors.lastname: Kang
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Chen
authors.forename: Li
authors.initials: L
authors.lastname: Zhang
authors.forename: Yuxiang
authors.initials: Y
authors.lastname: Xing
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted; D019047:Phantoms, Imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*