Mathematics of thermoacoustic tomography

By Peter Kuchment, Leonid A. Kunyansky. European journal of applied mathematics, 2007

355 citations recorded by the source corpus.

The article presents a survey of mathematical problems, techniques and challenges arising in thermoacoustic tomography and its sibling photoacoustic tomography.

Subfields: Biomedical Engineering, Mechanics of Materials, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/2b9069ae07821de953bcb89a0b164129d01ff50e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Gunther Uhlmann
2. Guillaume Bal
3. Yi-Hsuan Lin
4. Mikko Salo
5. Katya Krupchyk
6. Tuhin Ghosh
7. Ru-Yu Lai
8. Matti Lassas

In Mechanics of Materials

1. Gunther Uhlmann
2. Guillaume Bal
3. Plamen Stefanov
4. Katya Krupchyk

In Radiology, Nuclear Medicine and Imaging

1. Gunther Uhlmann
2. Guillaume Bal

Citations in the corpus

• Carleman estimates for global uniqueness, stability and numerical methods for coefficient inverse problems (2012, neutral): “[98] L. Kunyansky, Thermoacoustic tomography with detectors on an open curve: an efficient reconstruction algorithm, Inverse Problems, 24, 055021, 2008.”
• Inverse diffusion theory of photoacoustics (2009, background): “Once the amount of deposited energy has been reconstructed, a second step, sometimes called quantitative photoacoustics, consists of inferring the optical properties in the body.”
• Estimates on the generalization error of physics-informed neural networks for approximating a class of inverse problems for PDEs (2020, background): “problem stems from photoacoustic tomography (PAT) [31] and it also arises in control theory, in the form of so-called Luenberger observers [55].”