On the robustness of model-based algorithms for photoacoustic tomography: comparison between time and frequency domains

TL;DR

This paper compares the robustness of time and frequency domain model-based algorithms in photoacoustic tomography, showing that frequency domain methods are more sensitive to sensor location uncertainties, supported by experiments and theoretical analysis.

Contribution

It provides a comparative analysis of time and frequency domain models' sensitivity to sensor uncertainties in photoacoustic image reconstruction, highlighting the greater sensitivity of frequency domain approaches.

Findings

Frequency domain models are more sensitive to sensor location errors.

Numerical experiments confirm the theoretical sensitivity analysis.

Sensor uncertainties significantly impact image quality in photoacoustic reconstruction.

Abstract

For photoacoustic image reconstruction, certain parameters such as sensor positions and speed of sound have a major impact in the reconstruction process and must be carefully determined before data acquisition. Uncertainties in these parameters can lead to errors produced by a modeling mismatch, hindering the reconstruction process and severely affecting the resulting image quality. Therefore, in this work we study how modeling errors arising from uncertainty in sensor locations affect the images obtained by matrix model-based reconstruction algorithms based on time domain and frequency domain models of the photoacoustic problem. The effects on the reconstruction performance with respect to the uncertainty in the knowledge of the sensors location is compared and analyzed both in a qualitative and quantitative fashion for both time and frequency models. Ultimately, our study shows that the frequency domain approach is more sensitive to this kind of modeling errors. These conclusions are supported by numerical experiments and a theoretical sensitivity analysis of the mathematical operator for the direct problem.