Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

Aaron Carass (1) , Jennifer Cuzzocreo , Shuo Han , Carlos Hernandez-Castillo , Paul Rasser , Melanie Ganz , Vincent Beliveau , Jose Dolz (2) , Ismail Ben Ayed (3) , Christian Desrosiers (4) , Benjamin Thyreau (5) , José E. Romero (6) , Pierrick Coupé (7, 8) , Jose V. Manjon (6) , Vladimir Fonov (9) , D. Louis Collins (10) , Sarah Ying , Chiadi Onyike , Deana Crocetti , Bennett Landman , Stewart Mostofsky , Paul M. Thompson (11) , Jerry Prince

1 Department of Computer Science [Baltimore]
2 Aquilab
3 GE Healthcare
4 ETS - Ecole de Technologie Supérieure [Montréal]
5 LNAO - Laboratoire de Neuroimagerie Assistée par Ordinateur
6 ITACA
7 LaBRI - Laboratoire Bordelais de Recherche en Informatique
8 PICTURA - Patch-based processing for medical and natural images
9 MNI - McConnell Brain Imaging Centre
10 Montreal Neurological Institute and Hospital
11 LONI - Laboratory of Neuro Imaging [Los Angeles]

Domaines: Imagerie médicale

Aaron Carass, Jennifer Cuzzocreo, Shuo Han, Carlos Hernandez-Castillo, Paul Rasser, et al.. Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images. NeuroImage, 2018, 183, pp.150 - 172. ⟨10.1016/j.neuroimage.2018.08.003⟩. ⟨hal-01918431⟩