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Proceedings Paper

Accurate image reconstruction from sparse data in diffraction tomography using a total variation minimization algorithm
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Paper Abstract

We present a total-variation (TV)-based method for obtaining accurate image reconstruction in diffraction tomography (DT) from sparse data. Using computer-simulated data, we show that the TV-based method is effective in reconstructing accurate images using a total number of data samples comparable to or less than that of other current algorithms, such as filtered backpropagation or inverse scattering. Our algorithm is robust to the effects of measurement noise, and performs very well in limited angle scans. Overall our results indicate that TV minimization can be applied to DT image reconstruction under a variety of scan configurations and data conditions.

Paper Details

Date Published: 6 March 2007
PDF: 6 pages
Proc. SPIE 6513, Medical Imaging 2007: Ultrasonic Imaging and Signal Processing, 651302 (6 March 2007); doi: 10.1117/12.710195
Show Author Affiliations
Samuel J. LaRoque, The Univ. of Chicago (United States)
Emil Y. Sidky, The Univ. of Chicago (United States)
Xiaochuan Pan, The Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 6513:
Medical Imaging 2007: Ultrasonic Imaging and Signal Processing
Stanislav Y. Emelianov; Stephen A. McAleavey, Editor(s)

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