Parcellation of Infant Surface Atlas Using Developmental Trajectories of Multidimensional Cortical Attributes

被引:3
作者
Li, Gang [1 ,2 ]
Wang, Li [1 ,2 ]
Gilmore, John H. [3 ]
Lin, Weili [1 ,2 ]
Shen, Dinggang [1 ,2 ]
机构
[1] Univ N Carolina, Dept Radiol, Chapel Hill, NC 27599 USA
[2] Univ N Carolina, BRIC, Chapel Hill, NC 27599 USA
[3] Univ N Carolina, Dept Psychiat, Chapel Hill, NC 27599 USA
来源
MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION, PT III | 2015年 / 9351卷
关键词
Surface area; local gyrification; infant; atlas; parcellation; HUMAN CEREBRAL-CORTEX;
D O I
10.1007/978-3-319-24574-4_65
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cortical surface atlases, equipped with anatomically and functionally defined parcellations, are of fundamental importance in neuroimaging studies. Typically, parcellations of surface atlases are derived based on the sulcal-gyral landmarks, which are extremely variable across individuals and poorly matched with microstructural and functional boundaries. Cortical developmental trajectories in infants reflect underlying changes of microstructures, which essentially determines the molecular organization and functional principles of the cortex, thus allowing better definition of developmentally, microstructurally, and functionally distinct regions, compared to conventional sulcal-gyral landmarks. Accordingly, a parcellation of infant cortical surface atlas was proposed, based on the developmental trajectories of cortical thickness in infants, revealing regional patterning of cortical growth. However, cortical anatomy is jointly characterized by biologically-distinct, multidimensional cortical attributes, i.e., cortical thickness, surface area, and local gyrification, each with its distinct genetic underpinning, cellular mechanism, and developmental trajectories. To date, the parcellations based on the development of surface area and local gyrification is still missing. To bridge this critical gap, for the first time, we parcellate an infant cortical surface atlas into distinct regions based solely on developmental trajectories of surface area and local gyrification, respectively. For each cortical attribute, we first nonlinearly fuse the subject-specific similarity matrices of vertices' developmental trajectories of all subjects into a single matrix, which helps better capture common and complementary information of the population than the conventional method of simple averaging of all subjects' matrices. Then, we perform spectral clustering based on this fused matrix. We have applied our method to parcellate an infant surface atlas using the developmental trajectories of surface area and local gyrification from 35 healthy infants, each with up to 7 time points in the first two postnatal years, revealing biologically more meaningful growth patterning than the conventional method.
引用
收藏
页码:543 / 550
页数:8
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