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Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI.
- Source :
-
NeuroImage . Jan2016, Vol. 125, p120-130. 11p. - Publication Year :
- 2016
-
Abstract
- Technologies for multi-atlas brain segmentation of T1-weighted MRI images have rapidly progressed in recent years, with highly promising results. This approach, however, relies on a large number of atlases with accurate and consistent structural identifications. Here, we introduce our atlas inventories (n = 90), which cover ages 4–82 years with unique hierarchical structural definitions (286 structures at the finest level). This multi-atlas library resource provides the flexibility to choose appropriate atlases for various studies with different age ranges and structure-definition criteria. In this paper, we describe the details of the atlas resources and demonstrate the improved accuracy achievable with a dynamic age-matching approach, in which atlases that most closely match the subject's age are dynamically selected. The advanced atlas creation strategy, together with atlas pre-selection principles, is expected to support the further development of multi-atlas image segmentation. [ABSTRACT FROM AUTHOR]
- Subjects :
- *BRAIN diseases
*HUMAN anatomy
*CENTRAL nervous system
*BRAIN imaging
*NEUROSCIENCES
Subjects
Details
- Language :
- English
- ISSN :
- 10538119
- Volume :
- 125
- Database :
- Academic Search Index
- Journal :
- NeuroImage
- Publication Type :
- Academic Journal
- Accession number :
- 111640045
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2015.10.042