Machine learning methods applied to dMRI tractography for the study of brain connectivity
Schedule
Wednesday, August 19, 2020
13:15 UTC
Pamela Guevara
Engineer
Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, Chile
Host: IIBCE on Brain Science
Recording
Open recording
Event Information
Recording
Available
Host
IIBCE on Brain Science
Duration
70 minutes
Abstract
Tractography datasets, calculated from dMRI, represent the main WM structural connections in the brain. Thanks to advances in image acquisition and processing, the complexity and size of these datasets have constantly increased, also containing a large amount of artifacts. We present some examples of algorithms, most of them based on classical machine learning approaches, to analyze these data and identify common connectivity patterns among subjects.
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