Eleftherios Garyfallidis1,2, Matthew Brett3, Vassilis Tsiaras4, George Vogiatzis5, Ian Nimmo-Smith1
1MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom; 2University of Cambridge, Cambridge, United Kingdom; 3University of California, Berkeley, United States; 4Department of Computer Science, University of Crete, Greece; 5Computer Vision Group, Toshiba Research Europe, Cambridge, United Kingdom
Identifying manually corresponding tracks in different brain tractogaphies is a very complicated task, typically requiring lots of expertise, and lots of time. Moreover different local diffusion models and different tractography algorithms generate tractographies with wide differences in numbers of tracks and in shape characteristics. We address these problems by introducing an automatic method for detecting corresponding tracks in different dMRI (diffusion weighted MRI) datasets.