TY - GEN
T1 - Teichmüller shape space theory and its application to brain morphometry
AU - Wang, Yalin
AU - Dai, Wei
AU - Gu, Xianfeng
AU - Chan, Tony F.
AU - Yau, Shing Tung
AU - Toga, Arthur W.
AU - Thompson, Paul M.
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2009
Y1 - 2009
N2 - Here we propose a novel method to compute Teichmüller shape space based shape index to study brain morphometry. Such a shape index is intrinsic, and invariant under conformal transformations, rigid motions and scaling. We conformally map a genus-zero open boundary surface to the Poincaré disk with the Yamabe flow method. The shape indices that we compute are the lengths of a special set of geodesics under hyperbolic metric. Tests on longitudinal brain imaging data were used to demonstrate the stability of the derived feature vectors. In leave-one-out validation tests, we achieved 100% accurate classification (versus only 68% accuracy for volume measures) in distinguishing 11 HIV/AIDS individuals from 8 healthy control subjects, based on Teichmüller coordinates for lateral ventricular surfaces extracted from their 3D MRI scans.
AB - Here we propose a novel method to compute Teichmüller shape space based shape index to study brain morphometry. Such a shape index is intrinsic, and invariant under conformal transformations, rigid motions and scaling. We conformally map a genus-zero open boundary surface to the Poincaré disk with the Yamabe flow method. The shape indices that we compute are the lengths of a special set of geodesics under hyperbolic metric. Tests on longitudinal brain imaging data were used to demonstrate the stability of the derived feature vectors. In leave-one-out validation tests, we achieved 100% accurate classification (versus only 68% accuracy for volume measures) in distinguishing 11 HIV/AIDS individuals from 8 healthy control subjects, based on Teichmüller coordinates for lateral ventricular surfaces extracted from their 3D MRI scans.
UR - http://www.scopus.com/inward/record.url?scp=84863022209&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863022209&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04271-3_17
DO - 10.1007/978-3-642-04271-3_17
M3 - Conference contribution
C2 - 20426105
AN - SCOPUS:84863022209
SN - 3642042708
SN - 9783642042706
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 133
EP - 140
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings
T2 - 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
Y2 - 20 September 2009 through 24 September 2009
ER -