Scholar
Bene Wiestler
Google Scholar ID: -EEm-_MAAAAJ
AI for Image-Guided Diagnosis and Therapy, TUM
Citations & Impact
Citations
18,401
H-index
55
i10-index
200
Publications
20
Co-authors
0
Contact
No contact links provided.
Resume (English only)
Background
- Aims to bridge the gap between complex multimodal medical data and clinical decision-making by developing AI models that synthesize data into actionable biomarkers for precision diagnostics and personalized therapy
- Research focuses on: efficient (self-)supervised representation learning for medical imaging, predictive (partly bio-physically informed) models for disease assessment and individualized therapy, and algorithms leveraging synergistic multimodal medical data
- Lab holds a joint appointment between TUM Radiation Oncology and TUM Neuroradiology
- Prioritizes research on two neurological diseases: Multiple Sclerosis and Brain Tumors
- Committed to open science with public release of developed tools
- Actively participates in and co-organizes leading challenges (e.g., BraTS, ISLES) and workshops (e.g., MICCAI BrainLesion)
Co-authors