Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6024063 | NeuroImage | 2016 | 11 Pages |
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.
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Authors
Dan Wu, Ting Ma, Can Ceritoglu, Yue Li, Jill Chotiyanonta, Zhipeng Hou, John Hsu, Xin Xu, Timothy Brown, Michael I. Miller, Susumu Mori,