Interests
- Medical Imaging
- Machine learning
- Image registration
Education
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PhD in Medical Image Analysis, 2008
UMC Utrecht
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MSc in Mechanical Engineering, 2003
University of Twente
Projects
- Glioma Analysis
- ICAIlab Trustworthy AI for MRI
- AI4AI
- EOSC4Cancer
- EuCanImage
- Eye2Brain
- MERLIN
- Prenatal image analysis
- Towards Fully automated Anomaly Screening in the first Trimester of pregnancy using Artificial Intelligence (FAST-AI)
- AINED AIID
- PATH2XNAT
- The Liver Artificial Intelligence (LAI) consortium
- The Sarcoma Artificial Intelligence (SAI) consortium
Biography
Dr. ir. Stefan Klein is Associate Professor in Applied Medical Image Analysis. He is General Chair of the Biomedical Imaging Group Rotterdam, and holds a PI position at the department of Radiology and Nuclear Medicine of the Erasmus MC - University Medical Center Rotterdam, the Netherlands.
His research focuses on the development and validation of novel medical image analysis methods using advanced computational methods based on numerical mathematics, signal processing, and artificial intelligence (AI) including (deep) machine learning. With his team, he brings state-of-the-art techniques from computer science to the medical imaging domain, further developing, optimising and rigorously validating them. He strongly believes in the power of open science to promote research reproducibility: sharing code, sharing data, and collaborating rather than competing. His interests span a wide range of domains: in the last 5 years he has worked on fundamental technology for accelerated magnetic resonance image (MRI) acquisition and quantification, multi-scale and multi-modal retina imaging, novel spatiotemporal models of the developing and aging brain, and AI-supported diagnosis and prediction methods for various types of cancer, neurodegenerative disorders, osteoarthritis, and major eye diseases.
Besides performing research, Stefan is also active in setting up infrastructures that facilitate research in medical imaging. He has initiated a national Health-RI XNAT research archive for medical imaging data, is Imaging Community manager at Health-RI, and director of the Euro-BioImaging Population Imaging node.
Highlights
- Elastix - widely used open-source software for medical image registration, developed during my PhD study in collaboration with Marius Staring
- nD+t image registration - an elegant framework for nonrigid registration of dynamic medical imaging data, developed in collaboration with Coert Metz
- Groupwise registration for quantitative MRI - novel groupwise image registation method, comprehensively tested in 6 different medical applications (work by Wyke Huizinga)
- CADDementia challenge - an international Grand Challenge on computer-aided diagnosis of dementia, organised by Esther Bron
- KNOAP2020 - an international Grand Challenge on knee osteoarthritis prediction, organised by Jukka Hirvasniemi
- WORC - open-source software for fully automated radiomics analysis, developed by Martijn Starmans
- DEBM - disease progression timeline estimation using discriminative event based modeling, developed by Vikram Venkatraghavan source code
- DeepDicomSort - use deep learning to automatically sort your brain MRI datasets! work by Sebastian van der Voort source code