Towards inference of human brain connectivity from MR diffusion tensor data

This paper describes a method to infer the connectivity induced by white ma tter fibers in the living human brain. This method stems from magnetic reso nance tensor imaging (DTI), a technique which gives access to fiber orienta tions. Given typical DTI spatial resolution, connectivity is addressed at t he level of fascicles made up by a bunch of parallel fibers. We propose fir st an algorithm dedicated to fascicle tracking in a direction map inferred from diffusion data. This algorithm takes into account fan-shaped fascicle forks usual in actual white matter organization. Then, we propose a method of inferring a regularized direction map from diffusion data in order to im prove the robustness of the tracking. The regularization stems from an anal ogy between white matter organization and spaghetti plates. Finally, we pro pose a study of the tracking behavior according to the weight given to the regularization and some examples of the tracking results with in vivo human brain data. (C) 2001 Elsevier Science B.V. All rights reserved.