# Iterative Methods for Photoacoustic Tomography in Attenuating Acoustic   Media

**Authors:** Markus Haltmeier, Richard Kowar, and Linh V. Nguyen

arXiv: 1704.07422 · 2017-11-22

## TL;DR

This paper develops and analyzes iterative reconstruction methods for photoacoustic tomography in media with frequency-dependent attenuation, providing stable solutions and demonstrating high accuracy through numerical experiments.

## Contribution

It introduces a new iterative regularization framework for photoacoustic tomography in attenuating media with explicit convergence analysis and efficient adjoint computations.

## Key findings

- Stable solutions for attenuating media demonstrated
- High reconstruction accuracy shown in numerical tests
- Effective in limited view scenarios

## Abstract

The development of efficient and accurate reconstruction methods is an important aspect of tomographic imaging. In this article, we address this issue for photoacoustic tomography. To this aim, we use models for acoustic wave propagation accounting for frequency dependent attenuation according to a wide class of attenuation laws that may include memory. We formulate the inverse problem of photoacoustic tomography in attenuating medium as an ill-posed operator equation in a Hilbert space framework that is tackled by iterative regularization methods. Our approach comes with a clear convergence analysis. For that purpose we derive explicit expressions for the adjoint problem that can efficiently be implemented. In contrast to time reversal, the employed adjoint wave equation is again damping and, thus has a stable solution. This stability property can be clearly seen in our numerical results. Moreover, the presented numerical results clearly demonstrate the Efficiency and accuracy of the derived iterative reconstruction algorithms in various situations including the limited view case.

## Full text

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## Figures

25 figures with captions in the complete paper: https://tomesphere.com/paper/1704.07422/full.md

## References

79 references — full list in the complete paper: https://tomesphere.com/paper/1704.07422/full.md

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Source: https://tomesphere.com/paper/1704.07422