**Felix Lucka** (CWI)

*Image Reconstruction - A Playground for Applied Mathematicians *
Thursday, 24 February 2022, 14:00-15:00 in HG02.053

### Abstract

Mathematical image reconstruction describes the process of computing images of quantities
of interest from indirect observations through algorithms derived from rigorous mathematics.
As the observation process can often be modeled by partial differential equations, image
reconstruction problems are a classical example of inverse problems and draw from various
fields of applied mathematics, including numerical analysis, Bayesian inference, variational
regularization, compressed sensing, computational optimization, and machine learning.
Mathematical image reconstruction became a key technique in a vast range of scientific,
clinical and industrial applications. In this talk, I want to highlight some of its current
trends and challenges, illustrated by own work on biomedical imaging applications such as X-ray
computed tomography (CT), photoacoustic tomography (PAT), magnetic resonance imaging (MRI) and
ultrasound computed tomography (USCT).