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

Samuel J. LaRoque; Emil Y. Sidky; Xiaochuan Pan

doi:10.1117/12.710195

6 March 2007 Accurate image reconstruction from sparse data in diffraction tomography using a total variation minimization algorithm

Samuel J. LaRoque, Emil Y. Sidky, Xiaochuan Pan

Author Affiliations +

Proceedings Volume 6513, Medical Imaging 2007: Ultrasonic Imaging and Signal Processing; 651302 (2007) https://doi.org/10.1117/12.710195
Event: Medical Imaging, 2007, San Diego, CA, United States

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.

Citation Download Citation

Samuel J. LaRoque, Emil Y. Sidky, and Xiaochuan Pan "Accurate image reconstruction from sparse data in diffraction tomography using a total variation minimization algorithm", Proc. SPIE 6513, Medical Imaging 2007: Ultrasonic Imaging and Signal Processing, 651302 (6 March 2007); https://doi.org/10.1117/12.710195

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