@inproceedings{cde6814c5f624680ae76206cea7254c4,
title = "Low-rank matrix estimation-based spatio-temporal image reconstruction for dynamic photoacoustic computed tomography",
abstract = "In order to monitor dynamic physiological events in near-real time, a variety of photoacoustic computed tomography (PACT) systems have been developed that can rapidly acquire data. Previously reported studies of dynamic PACT have employed conventional static methods to reconstruct a temporally ordered sequence of images on a frame-by-frame basis. Frame-by-frame image reconstruction (FBFIR) methods fail to exploit correlations between data frames and are known to be statistically and computationally suboptimal. In this study, a low-rank matrix estimation-based spatio-temporal image reconstruction (LRME-STIR) method is investigated for dynamic PACT applications. The LRME-STIR method is based on the observation that, in many PACT applications, the number of frames is much greater than the rank of the ideal noiseless data matrix. Using computer-simulated photoacoustic data, the performance of the LRME-STIR method is compared with that of conventional FBFIR method. The results demonstrate that LRME-STIR method is not only computationally more efficient but also produces more accurate dynamic PACT images than a conventional FBFIR method.",
keywords = "Dynamic imaging, Low-rank matrix estimation, Optoacoustic tomography, Photoacoustic computed tomography",
author = "Kun Wang and Jun Xia and Changhui Li and Wang, {Lihong V.} and Anastasio, {Mark A.}",
year = "2014",
doi = "10.1117/12.2041850",
language = "English (US)",
isbn = "9780819498564",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
booktitle = "Photons Plus Ultrasound",
note = "Photons Plus Ultrasound: Imaging and Sensing 2014 ; Conference date: 02-02-2014 Through 05-02-2014",
}