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

Kun Wang, Jun Xia, Changhui Li, Lihong V. Wang, Mark A. Anastasio

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number056007
JournalJournal of biomedical optics
Volume19
Issue number5
DOIs
StatePublished - May 2014
Externally publishedYes

Keywords

  • dynamic imaging
  • low-rank matrix estimation
  • optoacoustic tomography
  • photoacoustic computed tomography

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Biomedical Engineering

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