Research Papers: Imaging

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

[+] Author Affiliations
Kun Wang

Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, 63130

Jun Xia

Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, 63130

Changhui Li

Peking University, Department of Biomedical Engineering, Beijing 100871, China

Lihong V. Wang

Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, 63130

Mark A. Anastasio

Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, 63130

J. Biomed. Opt. 19(5), 056007 (May 09, 2014). doi:10.1117/1.JBO.19.5.056007
History: Received December 3, 2013; Revised February 20, 2014; Accepted March 21, 2014
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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 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.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Kun Wang ; Jun Xia ; Changhui Li ; Lihong V. Wang and Mark A. Anastasio
"Fast spatiotemporal image reconstruction based on low-rank matrix estimation for dynamic photoacoustic computed tomography", J. Biomed. Opt. 19(5), 056007 (May 09, 2014). ; http://dx.doi.org/10.1117/1.JBO.19.5.056007


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