Low-rank matrix estimation-based spatio-temporal image reconstruction 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 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.
Additional Information© 2014 Society of Photo-Optical Instrumentation Engineers. This work was supported in part by NIH awards EB016963, EB010049, and CA167446. K. W. would also like to thank Dr. Robert W. Schoonover for useful discussions.
Published - 89432I.pdf