Enabling the autofocus approach for parameter optimization in planar measurement geometry clinical optoacoustic imaging

TL;DR

This paper introduces a fast, computationally simple autofocus algorithm for planar optoacoustic imaging systems, significantly reducing parameter estimation time and facilitating clinical application.

Contribution

A novel fast autofocus algorithm tailored for planar optoacoustic imaging that drastically decreases reconstruction time compared to traditional methods.

Findings

FAF algorithm estimates speed of sound in about 5 seconds

Validated with simulated and experimental data

Potential to enable clinical optoacoustic imaging

Abstract

In optoacoustic (photoacoustic) tomography, several parameters related to tissue and detector features are needed for image formation, but they may not be known a priori. An autofocus (AF) algorithm is generally used to estimate these parameters. However, the algorithm works iteratively, therefore, it is impractical for clinical imaging with systems featuring planar geometry due to long reconstruction times. We have developed a fast autofocus (FAF) algorithm for optoacoustic systems with planar geometry that is much simpler computationally than the conventional AF algorithm. We show that the FAF algorithm required about 5 sec. to provide accurate estimates of the speed of sound in simulated data and experimental data obtained using an imaging system that is poised to enter the clinic. The applicability of FAF for estimating other image formation parameters is discussed. We expect the FAF algorithm to contribute decisively to the clinical use of optoacoustic tomography systems with planar geometry.