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Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI.


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 4-82years 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.

SUBMITTER: Wu D 

PROVIDER: S-EPMC4691373 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI.

Wu Dan D   Ma Ting T   Ceritoglu Can C   Li Yue Y   Chotiyanonta Jill J   Hou Zhipeng Z   Hsu John J   Xu Xin X   Brown Timothy T   Miller Michael I MI   Mori Susumu S  

NeuroImage 20151021


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 4-82years with unique hierarchical structural definitions (286 structures at the finest level). This multi-atlas library resource provides the flexibility to choose approp  ...[more]

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