Weighted expectation maximization reconstruction algorithms for thermoacoustic tomography

Jin Zhang, Mark A. Anastasio, Xiaochuan Pan, Lihong V. Wang

Research output: Contribution to journalArticlepeer-review


Thermoacoustic tomography (TAT) is an emerging imaging technique with potential for a wide range of biomedical imaging applications. In this correspondence, we propose an infinite family of weighted expectation maximization (EM) algorithms for reconstruction of images from temporally truncated TAT measurement data. The weighted EM algorithms are equivalent mathematically to the conventional EM algorithm, but are shown to propagate data inconsistencies in different ways. Using simulated and experimental TAT measurement data, we demonstrate that suitable choices of weighted EM algorithms can effectively mitigate image artifacts that are attributable to temporal truncation of the TAT data function.

Original languageEnglish (US)
Pages (from-to)817-820
Number of pages4
JournalIEEE Transactions on Medical Imaging
Issue number6
StatePublished - Jun 2005
Externally publishedYes


  • Image reconstruction
  • Optoacoustic tomography
  • Photoacoustic tomography
  • Thermoacoustic tomography

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computational Theory and Mathematics


Dive into the research topics of 'Weighted expectation maximization reconstruction algorithms for thermoacoustic tomography'. Together they form a unique fingerprint.

Cite this