Quantitative Photo-acoustic Tomography with Partial Data

TL;DR

This paper advances quantitative photo-acoustic tomography by demonstrating unique and stable reconstruction of parameters from partial internal data using specialized boundary conditions and CGO solutions.

Contribution

It extends previous results to partial data scenarios, providing conditions for unique and stable parameter reconstruction in photo-acoustic tomography.

Findings

Unique reconstruction with 4 internal data sets under boundary conditions.

Stability achieved under convexity or geometric conditions.

Characterization of boundary measurements via CGO solutions.

Abstract

Photo-acoustic tomography is a newly developed hybrid imaging modality that combines a high-resolution modality with a high-contrast modality. We analyze the reconstruction of diffusion and absorption parameters in an elliptic equation and improve an earlier result of Bal and Uhlmann to the partial date case. We show that the reconstruction can be uniquely determined by the knowledge of 4 internal data based on well-chosen partial boundary conditions. Stability of this reconstruction is ensured if a convexity condition is satisfied. Similar stability result is obtained without this geometric constraint if 4n well-chosen partial boundary conditions are available, where $n$ is the spatial dimension. The set of well-chosen boundary measurements is characterized by some complex geometric optics (CGO) solutions vanishing on a part of the boundary.