title: Identification of cortical landmarks based on structural connectivity to subcortical regions.
abstract: Quantitative assessment of structural connectivities between cortical and subcortical regions has been of increasing interest in recent years. This paper proposes an algorithmic pipeline for identification of reliable cortical landmarks based on the consistent structural connectivity patterns between cortical and subcortical regions. Our experimental results of eight healthy subjects show that reliable and meaningful cortical landmarks can be extracted by using our approaches. Furthermore, subcortical regions can serve as reliable reference points for the identification of consistent corresponding cortical regions across individuals.
authors.affiliation: Northwestern Polytechnical University, Xi'an, China.
authors.forename: Degang
authors.initials: D
authors.lastname: Zhang
authors.forename: Lei
authors.initials: L
authors.lastname: Guo
authors.forename: Xintao
authors.initials: X
authors.lastname: Hu
authors.forename: Kaiming
authors.initials: K
authors.lastname: Li
authors.forename: Dajiang
authors.initials: D
authors.lastname: Zhu
authors.forename: Xi
authors.initials: X
authors.lastname: Jiang
authors.forename: Hanbo
authors.initials: H
authors.lastname: Chen
authors.forename: Fan
authors.initials: F
authors.lastname: Deng
authors.forename: Qun
authors.initials: Q
authors.lastname: Zhao
authors.forename: Tianming
authors.initials: T
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology*; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000033:anatomy & histology / Q000502:physiology*; D006801:Humans; D008279:Magnetic Resonance Imaging; D015203:Reproducibility of Results