Implementation of a convolutional neural network for brainstem landmark detection and co-registration

Le résumé fourni par la source

Accurate brainstem co-registration is important when analysing brainstem functional MRI data. We trained a convolutional neural network (CNN) to detect a set of brainstem landmarks and to define a brainstem region-of-interest and used these to co-register the brainstem between functional and anatomical space using previously developed landmark-based and automated brainstem co-registration (LBC and ABC) methods. The use of CNNs to supply these features to LBC and ABC produced results that compared well to conventional methods. Similar CNNs could be applied to other brain regions and such methods may be useful to automate the analysis of large functional datasets.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.