Tomographic Inverse Problems: Mathematical Challenges and Novel Applications
Simon R. Arridge
University College London, UKMartin Burger
Universität Erlangen-Nürnberg, GermanyBernadette Hahn
Universität Stuttgart, GermanyEric Todd Quinto
Tufts University, Medford, USA
![Tomographic Inverse Problems: Mathematical Challenges and Novel Applications cover](/_next/image?url=https%3A%2F%2Fcontent.ems.press%2Fassets%2Fpublic%2Fimages%2Fserial-issues%2Fcover-owr-volume-20-issue-2.png&w=3840&q=90)
Abstract
This workshop brought together researchers working on mathematical problems related to tomography, with a particular emphasis on novel applications and associated mathematical challenges. Examples of respective issues represented in the workshop were tomographic imaging with Compton cameras or coupled-physics imaging, resolution and aliasing, vector and tensor field tomography, diffraction tomography, magnetic particle tomography, and limited data, all of which are motivated by the many modern applications. These topics were complemented by novel algorithmic strategies in the solution of tomographic inverse problems, such as stochastic methods and machine learning techniques. Bringing together mathematical and scientific researchers working on these different mathematical problems created a fruitful interchange with novel ideas and strong impact for the future of the field.
Cite this article
Simon R. Arridge, Martin Burger, Bernadette Hahn, Eric Todd Quinto, Tomographic Inverse Problems: Mathematical Challenges and Novel Applications. Oberwolfach Rep. 20 (2023), no. 2, pp. 1105–1194
DOI 10.4171/OWR/2023/21