Wyke Huizinga (Alkmaar, 1989) received a BSc degree in applied physics at the Delft University of Technology. She did a minor in biomedical engineering and in that time she developed an interest for medical imaging. In 2013 Wyke received a MSc degree in applied physics with a specialization in image science and technology. Her graduation project was performed in the Biomedical Imaging Group Rotterdam at the Erasmus MC. The resulting thesis was entitled: “Groupwise Image Registration in Diffusion Weighted MRI using a PCA based Dissimilarity Metric”.
As of August 2013 Wyke works as a PhD student at the Erasmus MC on developing a model of the normal ageing brain using image processing techniques.
Developing new methods to improve medical image analysis.
Role(s) in VPH Dare
In the VPH-DARE@IT project I try to develop a 4D spatio temporal atlas of the ageing brain using data from the Rotterdam Scan Study. The atlas should show how the macro- and microstructure of the brain is changing as a function of age and would provide more insight in how the brain of a healthy population ages.
W. Huizinga, S. Klein and D.H.J. Poot, Fast Multidimensional B-spline Interpolation using Template Metaprogramming, Workshop on Biomedical Image Registration, London, 2014
W. Huizinga, D.H.J. Poot, J.-M. Guyader, H. Smit, M. van Kranenburg, R.J. van Geuns, A. Uitterdijk, H. van Beusekom, B.F. Coolen, A. Leemans, W.J. Niessen and S. Klein, Non-rigid groupwise image registration for motion compensation in quantitative MRI, Workshop on Biomedical Image Registration, London, 2014
W. Huizinga, C.T. Metz, D.H.J. Poot, M. de Groot, A. Leemans, W.J. Niessen and S. Klein, Groupwise registration for correcting subject motion and eddy current distortions in diffusion MRI using a PCA based dissimilarity metric, Workshop on Computational Diffusion MRI and Brain Connectivity, MICCAI, 2013