interpatient; affine + B-spline transformation; mutual information
Screen shot:
In this study, we use nonrigid registration to predict dementia.
For parameter files see the Elastix Model Zoo repository on GitHub.
elastix
version: 4.2
Command line call:
elastix -f image_i.mhd -m image_j.mhd -p par0010affine.txt -p par0010bspline.txt -out outputdir
S. Klein, M. Loog, F. van der Lijn, T. den Heijer, A. Hammers, M. de Bruijne, A. van der Lugt, R.P.W. Duin, M.M.B. Breteler and W.J. Niessen, Early diagnosis of dementia based on intersubject whole-brain dissimilarities, Proceedings of IEEE International Symposium on Biomedical Imaging: from Nano to Macro, 2010.
A control point spacing of 15 mm was used for the B-spline transformation (in the finest resolution).
[1] J.G. Sled, A.P. Zijdenbos, and A.C. Evans. Nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans. Med. Imaging, vol. 17, no. 1, pp. 87–97, 1998
[2] A. Hofman, M.M.B. Breteler, C.M. van Duijn, G.P. Krestin, H.A. Pols, B.H.C. Stricker, H. Tiemeier, A.G. Uitterlinden, J.R. Vingerling, and J.C.M. Witteman. The rotterdam study: objectives and design update. Eur J Epidemiol, vol. 22, no. 11, pp. 819–829, 2007.
© 2020 Viktor van der Valk