@inproceedings{792486e4b0ed4649b4e0303c96eca165,
title = "Image reconstruction for ultrasound computed tomography by use of the regularized dual averaging method",
abstract = "Waveform inversion methods can produce high-resolution reconstructed sound speed images for ultrasound computed tomography; however, they are very computational expensive. Source encoding methods can reduce this computational cost by formulating the image reconstruction problem as a stochastic optimization problem. Here, we solve this optimization problem by the regularized dual averaging method instead of the more commonly used stochastic gradient descent. This new optimization method allows use of non-smooth regularization functions and treats the stochastic data fidelity term in the objective function separately from the deterministic regularization function. This allows noise to be mitigated more effectively. The method further exhibits lower variance in the estimated sound speed distributions across iterations when line search methods are employed.",
keywords = "image reconstruction, stochastic optimization, ultrasound tomography, waveform inversion",
author = "Matthews, {Thomas P.} and Kun Wang and Cuiping Li and Neb Duric and Anastasio, {Mark A.}",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Medical Imaging 2017: Ultrasonic Imaging and Tomography ; Conference date: 15-02-2017 Through 16-02-2017",
year = "2017",
doi = "10.1117/12.2254170",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Neb Duric and Neb Duric and Brecht Heyde",
booktitle = "Medical Imaging 2017",
address = "United States",
}