Julius Åkesson will defend his thesis “On Deep Learning in Cardiovascular Magnetic Resonance Imaging” on October 17th, 2025.

Link to thesis in LU Research Portal.

Cardiovascular disease is the leading global cause of death. Cardiovascular magnetic resonance (CMR) imaging is the gold standard method for evaluating cardiac function and structure and is thus an important tool for diagnostics in cardiovascular disease. Recently, deep learning (DL) methods have achieved notable developments in various aspects of CMR. The aim of this thesis was to further assess the benefits of incorporating DL-based methods in CMR, specifically in the process of evaluating cardiac function. This was done in four studies that explored different applications and aspects of DL in CMR. In these, DL was applied alongside other new developments in image acquisition, reconstruction, and analysis. Assessments were conducted on the usefulness of the specific DL applications, and on how randomness in DL can affect the reporting of results.