Mathematics and AI for Imaging Seminars I
Organizer:
Chenglong Bao
Speaker:
Per Christian Hansen, Technical University of Denmark
Time:
Wednesday, 15:00-16:00
Oct. 23, 2024
Venue:
A04, the 8th Floor
Shuangqing Complex Building
双清综合楼8楼A04
Title:
CUQI – Computational Uncertainty Quantification for Inverse Problems
Abstract:
Since 2019 we have worked on developing a practical framework for applying uncertainty quantification to inverse problems.
Our work contributes to the basis for UQ studies of a range of linear and nonlinear inverse problems with different priors and noise models. Specifically, building on the Bayesian framework we develop a modeling and computational platform, including an abstraction layer aimed at non-experts, which is implemented in the python software package CUQIpy.
In this talk I highlight some of our results and methods, with examples from X-ray computed tomography (CT). I describe how we handle uncertain projection angles, how we include structural priors tailored to the geometry of the scanned object, and how we use a goal-oriented approach to compute inclusion boundaries and their roughness. I also briefly describe our software package.
This is joint work with all the members of the CUQI project:
https://sites.dtu.dk/cuqi
The work is supported by a grant from the Villum Foundation.