Interior Tomography With Continuous Singular Value Decomposition

Authors

    Authors

    X. Jin; A. Katsevich; H. Y. Yu; G. Wang; L. Li;Z. Q. Chen

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    IEEE Trans. Med. Imaging

    Keywords

    Hilbert transform; interior tomography; singular value decomposition; (SVD); X-ray computed tomography (CT); TRUNCATED HILBERT TRANSFORM; IMAGE-RECONSTRUCTION; LOCAL TOMOGRAPHY; Computer Science, Interdisciplinary Applications; Engineering, ; Biomedical; Engineering, Electrical & Electronic; Imaging Science &; Photographic Technology; Radiology, Nuclear Medicine & Medical Imaging

    Abstract

    The long-standing interior problem has important mathematical and practical implications. The recently developed interior tomography methods have produced encouraging results. A particular scenario for theoretically exact interior reconstruction from truncated projections is that there is a known subregion in the region of interest (ROI). In this paper, we improve a novel continuous singular value decomposition (SVD) method for interior reconstruction assuming a known subregion. First, two sets of orthogonal eigen-functions are calculated for the Hilbert and image spaces respectively. Then, after the interior Hilbert data are calculated from projection data through the ROI, they are projected onto the eigen-functions in the Hilbert space, and an interior image is recovered by a linear combination of the eigen-functions with the resulting coefficients. Finally, the interior image is compensated for the ambiguity due to the null space utilizing the prior subregion knowledge. Experiments with simulated and real data demonstrate the advantages of our approach relative to the projection onto convex set type interior reconstructions.

    Journal Title

    Ieee Transactions on Medical Imaging

    Volume

    31

    Issue/Number

    11

    Publication Date

    1-1-2012

    Document Type

    Article

    Language

    English

    First Page

    2108

    Last Page

    2119

    WOS Identifier

    WOS:000313689400010

    ISSN

    0278-0062

    Share

    COinS