Remco Duits is an Associate Professor at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). He is also affiliated to the TU/e biomedical engineering department medical image analysis (IMAG/e) where he applies his theory to medical imaging applications. Areas of expertise incluce mathematics, medical image analysis, differential geometry, Lie group analysis and numerical analysis. His research interests encompass group theory, functional analysis, differential geometry, PDE’s, harmonic analysis, geometric control and their applications to biomedical imaging and vision. Current research projects include a new retinal vessel tracking method based on orientation scores, Lie Group Analysis for Medical Image Processing and analysis of cardiac motion and strain patterns from Magnetic Resonance Imaging and Ultrasound Imaging to identify disease and its location.
Remco Duits received his MSc degree (with honors) in Mathematics in 2001 at the TU/e, where he also received his PhD (with honors) at the Department of Biomedical Engineering. Now he is associate professor at the Department of Applied Mathematics & Computer Science and affiliated part-time group at the Biomedical Engineering Department. Remco has organized and chaired three international workshops held at Eurandom TU/e intended for both mathematicians (probability theory, harmonic analysis and statistics) and mathematically inclined engineers (statistics and imaging). He has organized various other workshops and is a member of the EMaCs (Eindhoven Mathematics Colloquiums) organizing committee.as well as several other program committees, such as the international conferences on scale space and variational methods. He has also acted as associate editor on the JMIV editorial board and scientific reviewer for research proposals in the European Union, conference proceedings and related books, and journals such as JMIV, IJCV, PAMI, Journal of Physiology, SIAM Journal on Imaging Science, and IEEE-journal TMI.
Retrieving challenging vessel connections in retinal images by line co-occurrence statisticsBiological Cybernetics (2017)
Template matching via densities on the roto-translation groupIEEE Transactions on Pattern Analysis and Machine Intelligence (2018)
On Sub-Riemannian Geodesics in SE(3) whose spatial projections do not have cuspsJournal of Dynamical and Control Systems (2016)
Brain-inspired algorithms for retinal image analysisMachine Vision and Applications (2016)
Robust retinal vessel segmentation via locally adaptive derivative frames in orientation scoresIEEE Transactions on Medical Imaging (2016)
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