Fiber feature map based landmark initialization for highly deformable DTI registration.

[krabbe disease]

This paper presents a novel pipeline for the registration of diffusion tensor images (DTI ) with large pathological variations to normal controls based on the use of a novel feature map derived from white matter (WM ) fiber tracts . The research presented aims towards an atlas based DTI analysis of subjects with considerable brain pathologies such as tumors or hydrocephalus . In this paper , we propose a novel feature map that is robust against variations in WM fiber tract integrity and use these feature maps to determine a landmark correspondence using a 3 D point correspondence algorithm . This correspondence drives a deformation field computed using Gaussian radial basis functions (RBF ). This field is employed as an initialization to a standard deformable registration method like demons . We present early preliminary results on the registration of a normal control dataset to a dataset with abnormally enlarged lateral ventricles affected by fatal demyelinating Krabbe disease . The results are analyzed based on a regional tensor matching criterion and a visual assessment of overlap of major WM fiber tracts . While further evaluation and improvements are necessary , the results presented in this paper highlight the potential of our method in handling registration of subjects with severe WM pathology .