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.

Shearlet-based regularized ROI reconstruction in fan beam computed tomography / Bubba T., A.; Labate, D.; Zanghirati, G.; Bonettini, Silvia; Goossens, B.. - 9597:(2015), pp. 1-11. (Intervento presentato al convegno Wavelets and Sparsity XVI tenutosi a San Diego nel 10-12 agosto 2015) [10.1117/12.2187387].

Shearlet-based regularized ROI reconstruction in fan beam computed tomography

BONETTINI, Silvia;
2015

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.
2015
Wavelets and Sparsity XVI
San Diego
10-12 agosto 2015
9597
1
11
Bubba T., A.; Labate, D.; Zanghirati, G.; Bonettini, Silvia; Goossens, B.
Shearlet-based regularized ROI reconstruction in fan beam computed tomography / Bubba T., A.; Labate, D.; Zanghirati, G.; Bonettini, Silvia; Goossens, B.. - 9597:(2015), pp. 1-11. (Intervento presentato al convegno Wavelets and Sparsity XVI tenutosi a San Diego nel 10-12 agosto 2015) [10.1117/12.2187387].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1146898
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