Towards accurate, automatic segmentation of the hippocampus and amygdala from MRI by augmenting ANIMAL with a template library and label fusion
- 1 October 2010
- journal article
- Published by Elsevier BV in NeuroImage
- Vol. 52 (4), 1355-1366
- https://doi.org/10.1016/j.neuroimage.2010.04.193
Abstract
No abstract availableKeywords
This publication has 48 references indexed in Scilit:
- Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracyNeuroImage, 2009
- A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumesNeuroImage, 2009
- Validation of a fully automated 3D hippocampal segmentation method using subjects with Alzheimer's disease mild cognitive impairment, and elderly controlsNeuroImage, 2008
- FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric MappingNeuroImage, 2008
- A comparison of methods for the automated calculation of volumes and atrophy rates in the hippocampusNeuroImage, 2008
- Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interestNeuroImage, 2008
- Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: A proof-of-principle studyNeuroImage, 2007
- Anatomically constrained region deformation for the automated segmentation of the hippocampus and the amygdala: Method and validation on controls and patients with Alzheimer’s diseaseNeuroImage, 2007
- Hippocampal Volume and Shape Analysis in an Older Adult PopulationThe Clinical Neuropsychologist, 2007
- Active Shape Models-Their Training and ApplicationComputer Vision and Image Understanding, 1995