Cris H.B. Claessens

Cris H.B. Claessens is a Doctoral Candidate at the Electrical Engineering Department of Eindhoven University of Technology, specializing in Medical Image Analysis and Self-Supervised Learning. His research focuses on tasks in 3D medical imaging and tumor classification, with recent work involving hierarchical transformer models for ovarian tumor detection.

Research Trends: Claessens' 2024 publications highlight applications of self-supervised learning in medical imaging and transformer-based multiple-instance learning for tumor classification. Keywords include Computer Science, Medical Imaging, and Artificial Intelligence, with sub-fields emphasizing 3D image processing, deep learning, and oncology-related diagnostics.

Collaborations & Projects: He is actively involved in the TASTI - XECS221002 project (2023–2025) alongside collaborators like Viviers, Hamm, and de With. His work spans partnerships with institutions in international collaborations, focusing on medical imaging and cancer detection.