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Published May 9, 2014 | Published
Journal Article Open

Fast spatiotemporal image reconstruction based on low-rank matrix estimation for dynamic photoacoustic computed tomography


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 spatiotemporal 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 both computer-simulated and experimentally measured photoacoustic data, the performance of the LRME-STIR method is compared with that of conventional FBFIR method followed by image-domain filtering. The results demonstrate that the LRME-STIR method is not only computationally more efficient but also produces more accurate dynamic PACT images than a conventional FBFIR method followed by image-domain filtering.

Additional Information

© 2014 SPIE. Paper 130851R received Dec. 3, 2013; revised manuscript received Feb. 20, 2014; accepted for publication Mar. 21, 2014; published online May 9, 2014. This work was supported in part by NIH awards EB016963, EB010049, and CA1744601. K.W. would also like to thank Dr. Robert W. Schoonover for useful discussions.

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