Weighted expectation maximization reconstruction algorithms for thermoacoustic tomography

Abstract—Thermoacoustic tomography (TAT) is an emerging imaging technique with potential for a wide range of biomedical imaging applica-tions. 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 al-gorithms 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 func-tion. Index Terms—Image reconstruction, optoacoustic tomography, photoa-coustic tomography, thermoacoustic tomography. I