TY - GEN
T1 - Anatomy-guided discovery of large-scale consistent connectivity-based cortical landmarks
AU - Jiang, Xi
AU - Zhang, Tuo
AU - Zhu, Dajiang
AU - Li, Kaiming
AU - Lv, Jinglei
AU - Guo, Lei
AU - Liu, Tianming
PY - 2013
Y1 - 2013
N2 - Establishment of structural and functional correspondences across different brains is one of the most fundamental issues in the human brain mapping field. Recently, several multimodal DTI/fMRI studies have demonstrated that consistent white matter fiber connection patterns can predict brain function and represent common brain architectures across individuals and populations, and along this direction, several approaches have been proposed to discover large-scale cortical landmarks with common structural connection profiles. However, an important limitation of previous approaches is that the rich anatomical information such as gyral/sulcal folding patterns has not been incorporated into the landmark discovery procedure yet. In this paper, we present a novel anatomy-guided discovery framework that defines and optimizes a dense map of cortical landmarks that possess group-wise consistent anatomical and fiber connectional profiles. This framework effectively integrates reliable and rich anatomical, morphological, and fiber connectional information for landmark initialization, optimization and prediction, which are formulated and solved as an energy minimization problem. Validation results based on fMRI data demonstrate that the identified 555 cortical landmarks are producible, predictable and exhibit accurate structural and functional correspondences across individuals and populations, offering a universal and individualized brain reference system for neuroimaging research.
AB - Establishment of structural and functional correspondences across different brains is one of the most fundamental issues in the human brain mapping field. Recently, several multimodal DTI/fMRI studies have demonstrated that consistent white matter fiber connection patterns can predict brain function and represent common brain architectures across individuals and populations, and along this direction, several approaches have been proposed to discover large-scale cortical landmarks with common structural connection profiles. However, an important limitation of previous approaches is that the rich anatomical information such as gyral/sulcal folding patterns has not been incorporated into the landmark discovery procedure yet. In this paper, we present a novel anatomy-guided discovery framework that defines and optimizes a dense map of cortical landmarks that possess group-wise consistent anatomical and fiber connectional profiles. This framework effectively integrates reliable and rich anatomical, morphological, and fiber connectional information for landmark initialization, optimization and prediction, which are formulated and solved as an energy minimization problem. Validation results based on fMRI data demonstrate that the identified 555 cortical landmarks are producible, predictable and exhibit accurate structural and functional correspondences across individuals and populations, offering a universal and individualized brain reference system for neuroimaging research.
KW - anatomical
KW - connectivity
KW - cortical landmarks
KW - DTI
KW - fMRI
UR - http://www.scopus.com/inward/record.url?scp=84894610113&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40760-4_77
DO - 10.1007/978-3-642-40760-4_77
M3 - 会议稿件
C2 - 24505813
AN - SCOPUS:84894610113
SN - 9783642407598
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 617
EP - 625
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings
T2 - 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013
Y2 - 22 September 2013 through 26 September 2013
ER -