A general region-of-interest image reconstruction approach with truncated Hilbert transform

Article type: Research Article

Authors: Li, Liang | Kang, Kejun | Chen, Zhiqiang | Zhang, Li | Xing, Yuxiang

Affiliations: Department of Engineering Physics, Tsinghua University, Beijing, 100084, China. and Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, China

Note: [] Corresponding author. E-mail: liliang02@mails.tsinghua.edu.cn

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.

Keywords: Computed tomography (CT), image reconstruction, Region-of-interest (ROI), truncated Hilbert transform

DOI: 10.3233/XST-2009-0218

Journal: Journal of X-Ray Science and Technology, vol. 17, no. 2, pp. 135-152, 2009