Reconstruction-classification method for quantitative photoacoustic tomography

TL;DR

This paper introduces a combined reconstruction-classification method for quantitative photoacoustic tomography that improves the accuracy of recovering optical parameters by leveraging class-based parameter estimation, resulting in superior image quality.

Contribution

The novel method integrates classification into the reconstruction process, enabling more accurate and robust recovery of absorption and scattering in turbid media.

Findings

Accurately recovers absorption and scattering in 2D and 3D.

Outperforms traditional reconstruction-only approaches.

Enhances image quality in photoacoustic tomography.

Abstract

We propose a combined reconstruction-classification method for simultaneously recovering absorption and scattering in turbid media from images of absorbed optical energy. This method exploits knowledge that optical parameters are determined by a limited number of classes to iteratively improve their estimate. Numerical experiments show that the proposed approach allows for accurate recovery of absorption and scattering in 2 and 3 dimensions, and delivers superior image quality with respect to traditional reconstruction-only approaches.