Iterative reconstruction algorithm for optoacoustic imaging

TLDR

Optoacoustic imaging generates thermoelastic stress waves from laser‑heated, optically heterogeneous media, and these waves encode information about structures with preferential optical absorption, but conventional reconstruction requires many detectors and signal filtering to suppress artifacts. This study proposes an iterative reconstruction procedure as an alternative to conventional backprojection methods. The algorithm iteratively minimizes the error between measured and calculated signals using broadband ultrasound detectors, enabling three‑dimensional imaging of multiple optoacoustic sources in experiments and simulations. After roughly ten iterations, the iterative method markedly improves image quality over simple backprojection and, although computationally more intensive, demands fewer detectors and less acquisition time than filtered backprojection.

Abstract

Optoacoustic imaging is based on the generation of thermoelastic stress waves by heating an object in an optically heterogeneous medium with a short laser pulse. The stress waves contain information about the distribution of structures with preferential optical absorption. Detection of the waves with an array of broadband ultrasound detectors at the surface of the medium and applying a backprojection algorithm is used to create a map of absorbed energy inside the medium. With conventional reconstruction methods a large number of detector elements and filtering of the signals are necessary to reduce backprojection artifacts. As an alternative this study proposes an iterative procedure. The algorithm is designed to minimize the error between measured signals and signals calculated from the reconstructed image. In experiments using broadband optical ultrasound detectors and in simulations the algorithm was used to obtain three-dimensional images of multiple optoacoustic sources. With signals from a planar array of 3x3 detector elements a significant improvement was observed after about 10 iterations compared to the simple radial backprojection. Compared to conventional methods using filtered backprojection, the iterative method is computationally more intensive but requires less time and instrumentation for signal acquisition.