Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.
Aaron CarassJennifer L. CuzzocreoShuo HanCarlos R. Hernandez-CastilloPaul E. RasserMelanie GanzVincent BeliveauJose DolzIsmail Ben AyedChristian DesrosiersBenjamin ThyreauJosé E. RomeroPierrick CoupéJosé V. ManjónVladimir S. FonovD. Louis CollinsSarah H. YingChiadi U. OnyikeJerry L. PrincePublished in: NeuroImage (2018)
Keyphrases
- magnetic resonance images
- fully automated
- white matter
- manual segmentation
- fully automatic
- mr images
- medical images
- magnetic resonance imaging
- medical imaging
- brain mri
- diffusion tensor
- mri data
- brain tissue
- medical image analysis
- high resolution
- partial volume
- brain structures
- cortical thickness
- diffusion weighted
- computer vision
- brain tumor segmentation
- high quality
- functional magnetic resonance imaging
- brain tumors
- magnetic resonance
- region of interest
- spatial normalization
- three dimensional