TY - GEN
T1 - An interactive geometric technique for upper and lower teeth segmentation
AU - Le, Binh Huy
AU - Deng, Zhigang
AU - Xia, James J.
AU - Chang, Yu Bing
AU - Zhou, Xiaobo
PY - 2009/12/1
Y1 - 2009/12/1
N2 - Due to the complexity of the dental models in semantics of both shape and form, a fully automated method for the separation of the lower and upper teeth is unsuitable while manual segmentation requires painstakingly user interventions. In this paper, we present a novel interactive method to segment the upper and lower teeth. The process is performed on 3D triangular mesh of the skull and consists of four main steps: reconstruction of 3D model from teeth CT images, curvature estimation, interactive segmentation path planning using the shortest path finding algorithm, and performing actual geometric cut on 3D models using a graph cut algorithm. The accuracy and efficiency of our method were experimentally validated via comparisons with ground truth (manual segmentation) as well as the state of art interactive mesh segmentation algorithms. We show the presented scheme can dramatically save manual effort for users while retaining an acceptable quality (with an averaged 0.29 mm discrepancy from the ideal segmentation).
AB - Due to the complexity of the dental models in semantics of both shape and form, a fully automated method for the separation of the lower and upper teeth is unsuitable while manual segmentation requires painstakingly user interventions. In this paper, we present a novel interactive method to segment the upper and lower teeth. The process is performed on 3D triangular mesh of the skull and consists of four main steps: reconstruction of 3D model from teeth CT images, curvature estimation, interactive segmentation path planning using the shortest path finding algorithm, and performing actual geometric cut on 3D models using a graph cut algorithm. The accuracy and efficiency of our method were experimentally validated via comparisons with ground truth (manual segmentation) as well as the state of art interactive mesh segmentation algorithms. We show the presented scheme can dramatically save manual effort for users while retaining an acceptable quality (with an averaged 0.29 mm discrepancy from the ideal segmentation).
UR - http://www.scopus.com/inward/record.url?scp=84883841301&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883841301&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04271-3_117
DO - 10.1007/978-3-642-04271-3_117
M3 - Conference contribution
C2 - 20426205
AN - SCOPUS:84883841301
SN - 3642042708
SN - 9783642042706
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 968
EP - 975
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 -