TY - GEN
T1 - Gyral folding pattern analysis via surface profiling
AU - Li, Kaiming
AU - Guo, Lei
AU - Li, Gang
AU - Nie, Jingxin
AU - Faraco, Carlos
AU - Zhao, Qun
AU - Miller, Stephen
AU - Liu, Tianming
PY - 2009
Y1 - 2009
N2 - Human cortical folding pattern has been studied for decades. This paper proposes a gyrus scale folding pattern analysis technique via cortical surface profiling. Firstly, we sample the cortical surface into 2D profiles and model them using power function. This step provides both the flexibility of representing arbitrary shape by profiling and the compactness of representing shape by parametric modeling. Secondly, based on the estimated model parameters, we extract affine-invariant features on the cortical surface and apply the affinity propagation clustering algorithm to parcellate the cortex into regions with different shape patterns. Finally, a second-round surface profiling is performed on the parcellated cortical regions, and the number of hinges is detected to describe the gyral folding pattern. Experiments demonstrate that our method could successfully classify human gyri into 2-hinge, 3-hinge and 4-hinge gyri. The proposed method has the potential to significantly contribute to automatic segmentation and recognition of cortical gyri.
AB - Human cortical folding pattern has been studied for decades. This paper proposes a gyrus scale folding pattern analysis technique via cortical surface profiling. Firstly, we sample the cortical surface into 2D profiles and model them using power function. This step provides both the flexibility of representing arbitrary shape by profiling and the compactness of representing shape by parametric modeling. Secondly, based on the estimated model parameters, we extract affine-invariant features on the cortical surface and apply the affinity propagation clustering algorithm to parcellate the cortex into regions with different shape patterns. Finally, a second-round surface profiling is performed on the parcellated cortical regions, and the number of hinges is detected to describe the gyral folding pattern. Experiments demonstrate that our method could successfully classify human gyri into 2-hinge, 3-hinge and 4-hinge gyri. The proposed method has the potential to significantly contribute to automatic segmentation and recognition of cortical gyri.
UR - http://www.scopus.com/inward/record.url?scp=84883835040&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04268-3_39
DO - 10.1007/978-3-642-04268-3_39
M3 - 会议稿件
C2 - 20426002
AN - SCOPUS:84883835040
SN - 3642042678
SN - 9783642042676
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 313
EP - 320
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009 - 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 -