Paulo Reis Rodrigues1, Anna Vilanova1, Thorsten Twellmann2, Bart M. ter Haar Romeny1
1Biomedical Image Analysis, Technical
University of Eindhoven, Eindhoven, Noord Brabant, Netherlands; 2MeVis
Medical Solutions AG, Bremen, Germany
Similarity of diffusion tensors is a crucial point in several applications like segmentation, group statistical analysis, etc. The selection of the most suitable measure, for a given task, is not always clear and often done by trial and error. We present a proof of concept of an initially flexible learning scheme that infers the measure or combination of measures that achieves the best discrimination between a user selected Region of Interest and a representative set of tensors of the whole volume. The results demonstrate the methods potential to infer the ideal parameters for a task specific segmentation algorithm, region growing.