TY - JOUR
T1 - Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI
AU - Wu, Dan
AU - Ma, Ting
AU - Ceritoglu, Can
AU - Li, Yue
AU - Chotiyanonta, Jill
AU - Hou, Zhipeng
AU - Hsu, John
AU - Xu, Xin
AU - Brown, Timothy
AU - Miller, Michael I.
AU - Mori, Susumu
N1 - Publisher Copyright:
© 2015 Elsevier Inc.
PY - 2016/1/15
Y1 - 2016/1/15
N2 - 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.
AB - 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.
KW - Atlas creation strategy
KW - Dynamic age-matching
KW - Hierarchical ontology
KW - Multi-atlas
KW - Segmentation accuracy
KW - T1-weighted
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U2 - 10.1016/j.neuroimage.2015.10.042
DO - 10.1016/j.neuroimage.2015.10.042
M3 - Article
C2 - 26499813
AN - SCOPUS:84945895434
SN - 1053-8119
VL - 125
SP - 120
EP - 130
JO - NeuroImage
JF - NeuroImage
ER -