Image registration based on thin-plate splines and local estimates of anisotropic landmark localization uncertainties

Abstract

We present an approach to elastic registration of tomographic brain images which is based on thin-plate splines and takes into account landmark errors. The inclusion of error information is important in clinical applications since landmark extraction is always prone to error. In comparison to previous work, our approach can cope with anisotropic errors, which is significantly more realistic than dealing only with isotropic errors. In particular, it is now possible to include different types of landmarks, e. g., quasi-landmarks at the outer contour of the brain. Also, we introduce an approach to estimate landmark localization uncertainties directly from the image data. Experimental results are presented for the registration of 2D and 3D MR images.