A general region-of-interest image reconstruction approach with truncated Hilbert transform.
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.
Li
Liang
L
Department of Engineering Physics, Tsinghua University, Beijing, China. liliang02@mails.tsinghua.edu.cn
Kang
Kejun
K
Chen
Zhiqiang
Z
Zhang
Li
L
Xing
Yuxiang
Y
D000465:Algorithms; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted; D019047:Phantoms, Imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*