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A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T
- Source :
- NeuroImage. 44(2)
- Publication Year :
- 2008
-
Abstract
- This paper describes the construction of a computational anatomical atlas of the human hippocampus. The atlas is derived from high-resolution 9.4 Tesla MRI of postmortem samples. The main subfields of the hippocampus (cornu ammonis fields CA1, CA2/3; the dentate gyrus; and the vestigial hippocampal sulcus) are labeled in the images manually using a combination of distinguishable image features and geometrical features. A synthetic average image is derived from the MRI of the samples using shape and intensity averaging in the diffeomorphic non-linear registration framework, and a consensus labeling of the template is generated. The agreement of the consensus labeling with manual labeling of each sample is measured, and the effect of aiding registration with landmarks and manually generated mask images is evaluated. The atlas is provided as an online resource with the aim of supporting subfield segmentation in emerging hippocampus imaging and image analysis techniques. An example application examining subfield-level hippocampal atrophy in temporal lobe epilepsy demonstrates the application of the atlas to in vivo studies.
- Subjects :
- Models, Anatomic
Cornu Ammonis
Computer science
Cognitive Neuroscience
Hippocampus
Sensitivity and Specificity
Article
Temporal lobe
Imaging, Three-Dimensional
Atlas (anatomy)
Image Interpretation, Computer-Assisted
medicine
Cadaver
Humans
Segmentation
Computer vision
Computer Simulation
medicine.diagnostic_test
business.industry
Dentate gyrus
Reproducibility of Results
Magnetic resonance imaging
Hippocampal sulcus
Image Enhancement
Magnetic Resonance Imaging
Hippocampal atrophy
medicine.anatomical_structure
Neurology
nervous system
Feature (computer vision)
Artificial intelligence
business
Algorithms
Subjects
Details
- ISSN :
- 10959572
- Volume :
- 44
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- NeuroImage
- Accession number :
- edsair.doi.dedup.....fbb6a5040fda1c6fa5543e8f0dd8156a