Hugo Kuijf



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 microbleedsmicroinfarcts, 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 Imagingmember 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.


Image Sciences Institute
University Medical Center Utrecht
Heidelberglaan 100
Room Q.02.4.45
3584 CX Utrecht
The Netherlands
email: h.kuijf@umcutrecht.nl
office: Q.02.4.45
phone: +31 88 75 58562
secretary: +31 88 75 57772


Publications