An automated approach to connectivity-based partitioning of brain structures.
We present an automated approach to the problem of connectivity-based partitioning of brain structures using diffusion imaging. White-matter fibres connect different areas of the brain, allowing them to interact with each other. Diffusion-tensor MRI measures the orientation of white-matter fibres in vivo, allowing us to perform connectivity-based partitioning non-invasively. Our new approach leverages atlas-based segmentation to automate anatomical labeling of the cortex. White-matter connectivities are inferred using a probabilistic tractography algorithm that models crossing pathways explicitly. The method is demonstrated with the partitioning of the corpus callosum of eight healthy subjects.
Cook
P A
PA
Centre for Medical Image Computing, Department of Computer Science, University College London, UK.
Zhang
H
H
Avants
B B
BB
Yushkevich
P
P
Alexander
D C
DC
Gee
J C
JC
Ciccarelli
O
O
Thompson
A J
AJ