Gustav Müller-Franzes

Gustav studied electrical engineering at RWTH Aachen University. He developed deep learning methods for the classification of breast cancer when pursuing his bachelor thesis at the Institute of Imaging and Computer Vision (RWTH Aachen University). Following that, he investigated the effects of inter-rater segmentation variance on radiomics features during his master thesis. He joined the team in 2020 and is now a PhD candidate involved in several projects with the primary goal to establish and validate deep learning methods in clinical practice.