dr. H.J. (Hugo) Kuijf Assistant Professor
- Image Sciences Institute
Hugo Kuijf graduated in Computer Science at Utrecht University in 2009, with academic minors in Software Engineering and Game- and Media Technology. In 2013, he received his PhD in Medical Imaging after defending his thesis entitled "Image processing techniques for quantification and assessment of brain MRI".
His research focuses on innovative image processing and (deep) machine learning techniques for the quantification and assessment of brain MR images. These techniques are applied in the context of brain anatomy and pathology, in particular small vessel disease. Semi-automated techniques for the detection of microbleeds, microinfarcts, small arteries and veins, perivascular spaces, and white matter hyperintensities are developed; inclusing lesion-symptom mapping solutions. Development and utilization of modern machine learning and deep learning techniques (also known as "artifical intelligence") are a central pillar in the development of new medical image analysis techniques.
He organized the MICCAI grand challenges on WMH segmentation and brain tissue segmentation (MRBrainS13 and MRBrainS18). He developed freely available software for the detection of the midsagittal plane and suface and lesion-symptom mapping.
Hugo Kuijf is an assistant professor at the Image Sciences Institute, UMC Utrecht; programme coordinator of the MSc programme Medical Imaging; member of the Board of Examiners of the Graduate School of Life Sciences; chair of the Education Committee of the PhD programme Medical Imaging; and university lecturer at Eindhoven University of Technology.
University Lecturer at Eindhoven University of Technology
Chair of the Education Committee of the PhD programme Medical Imaging
Programme coordinator of the MSc programme Medical Imaging
Fellowship and Awards
I've received a number of smaller and larger grants, fellowships, and awards for my research.
- ZonMW Off Road - "The odd one out: generic detection of anomalies in brain MR images"
- Applied Data Analytics in Medicine - Imagr
- Hartstichting PPS 2018 - "ANEURYSM@RISK: automatic intracranial aneurysm quantification, 4D flow MRI and feature learning modelling to optimize intracranial aneurysm rupture prediction"
- BRAIN@RISK Talent Programme
- Research grant from Applied Data Science - Special Interest Group Imaging
- Study grant from Circulatory Health - visit to Massachusetts General Hospital and Harvard Medical School, Boston, USA
- NVIDIA GPU Grant Programme
- Travel grant from Alzheimer Nederland
- ISMRM Educational Stiped (twice)