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Proceedings Paper

Shearlet-based regularized ROI reconstruction in fan beam computed tomography
Author(s): T. A. Bubba; D. Labate; G. Zanghirati; S. Bonettini; B. Goossens
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Paper Abstract

Region-of-interest (ROI) reconstruction in computed tomography (CT) is a problem receiving increasing attention in the medical imaging community, due to its potential to lower exposure to X-ray radiation and to reduce the scanning time. Since the ROI reconstruction problem requires to deal with truncated projection images, classical CT reconstruction algorithms tend to become very unstable and the solution of this problem requires either ad hoc analytic formulas or more sophisticated numerical schemes. In this paper, we introduce a novel approach for ROI CT reconstruction, formulated as a convex optimization problem with a regularized functional based on shearlets or wavelets. Our numerical implementation consists of an iterative algorithm based on the scaled gradient projection method. As illustrated by numerical tests in the context of fan beam CT, our algorithm is insensitive to the location of the ROI and remains very stable also when the ROI size is rather small.

Paper Details

Date Published: 24 August 2015
PDF: 11 pages
Proc. SPIE 9597, Wavelets and Sparsity XVI, 95970K (24 August 2015); doi: 10.1117/12.2187387
Show Author Affiliations
T. A. Bubba, Univ. of Ferrara (Italy)
INdAM-GNCS (Italy)
D. Labate, Univ. of Houston (United States)
G. Zanghirati, Univ. of Ferrara (Italy)
INdAM-GNCS (Italy)
S. Bonettini, Univ. of Ferrara (Italy)
INdAM-GNCS (Italy)
B. Goossens, Ghent Univ. (Belgium)


Published in SPIE Proceedings Vol. 9597:
Wavelets and Sparsity XVI
Manos Papadakis; Vivek K. Goyal; Dimitri Van De Ville, Editor(s)

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