TY - GEN
T1 - Registering cortical surfaces based on whole-brain structural connectivity and continuous connectivity analysis
AU - Gutman, Boris
AU - Leonardo, Cassandra
AU - Jahanshad, Neda
AU - Hibar, Derrek
AU - Eschenburg, Kristian
AU - Nir, Talia
AU - Villalon, Julio
AU - Thompson, Paul
PY - 2014
Y1 - 2014
N2 - We present a framework for registering cortical surfaces based on tractography-informed structural connectivity. We define connectivity as a continuous kernel on the product space of the cortex, and develop a method for estimating this kernel from tractography fiber models. Next, we formulate the kernel registration problem, and present a means to non-linearly register two brains' continuous connectivity profiles. We apply theoretical results from operator theory to develop an algorithm for decomposing the connectome into its shared and individual components. Lastly, we extend two discrete connectivity measures to the continuous case, and apply our framework to 98 Alzheimer's patients and controls. Our measures show significant differences between the two groups.
AB - We present a framework for registering cortical surfaces based on tractography-informed structural connectivity. We define connectivity as a continuous kernel on the product space of the cortex, and develop a method for estimating this kernel from tractography fiber models. Next, we formulate the kernel registration problem, and present a means to non-linearly register two brains' continuous connectivity profiles. We apply theoretical results from operator theory to develop an algorithm for decomposing the connectome into its shared and individual components. Lastly, we extend two discrete connectivity measures to the continuous case, and apply our framework to 98 Alzheimer's patients and controls. Our measures show significant differences between the two groups.
KW - Connectivity Analysis
KW - Cortical Surface Registration
KW - Data Fusion
KW - Diffusion MRI
UR - http://www.scopus.com/inward/record.url?scp=84906980614&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-10443-0_21
DO - 10.1007/978-3-319-10443-0_21
M3 - Conference contribution
C2 - 25320795
AN - SCOPUS:84906980614
SN - 9783319104423
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 161
EP - 168
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
PB - Springer Verlag
T2 - 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
Y2 - 14 September 2014 through 18 September 2014
ER -