2024/10/31 | People | Artificial Intelligence

PhD Defense: Lukas Zbinden Advances Non-Invasive Liver MRI Analysis with Cutting-Edge AI Techniques

On 31 October 2024, Lukas Zbinden successfully defended his PhD thesis in Biomedical Engineering. His groundbreaking work, titled "Advances in Automated Non-Invasive Liver MRI Phenotyping and Stochastic Segmentation", addresses key challenges in liver MRI analysis, presenting innovative solutions to improve the accuracy and efficiency of this critical diagnostic tool. Congratulations to Dr. Lukas Zbinden on this significant achievement!

@ Lukas Zbinden

Publications:

L. Zbinden, D. Catucci, Y. Suter, A. Berzigotti, L. Ebner, A. Christe, V. C. Obmann, R. Sznitman, A. T. Huber. Convolutional Neural Network for Automated Segmentation of the Liver and its Vessels on Non-Contrast T1 vibe Dixon Acquisitions. Scientific Reports, vol. 12, no. 1, p. 22059, Dec. 2022, doi:10.1038/s41598-022-26328-2                                             

L. Zbinden, D. Catucci, Y. Suter, L. Hulbert, A. Berzigotti, M. Brönnimann, L. Ebner, A. Christe, V. C. Obmann, R. Sznitman, A. T. Huber. Automated liver segmental volume ratio quantification on non-contrast T1–Vibe Dixon liver MRI using deep learning. European Journal of Radiology (2023) 167:111047. doi: 10.1016/j.ejrad.2023.111047                                                                

L. Zbinden*, L. Doorenbos*, T. Pissas, A. Huber, R. Sznitman, P. Márquez-Neila. Stochastic Segmentation with Conditional Categorical Diffusion Models. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pages 1119–1129, 2023.