@inproceedings{e8cddd13cd5649f19384d9fb7e50989f,
title = "Automated digital dental articulation",
abstract = "Articulating digital dental models is often inaccurate and very time-consuming. This paper presents an automated approach to efficiently articulate digital dental models to maximum intercuspation (MI). There are two steps in our method. The first step is to position the models to an initial position based on dental curves and a point matching algorithm. The second step is to finally position the models to the MI position based on our novel approach of using iterative surface-based minimum distance mapping with collision constraints. Finally, our method was validated using 12 sets of digital dental models. The results showed that using our method the digital dental models can be accurately and effectively articulated to MI position.",
keywords = "automated, collision avoidance, digital dental articulation, digital dental models",
author = "Xia, {James J.} and Chang, {Yu Bing} and Jaime Gateno and Zixiang Xiong and Xiaobo Zhou",
year = "2010",
doi = "10.1007/978-3-642-15711-0_35",
language = "English (US)",
isbn = "3642157106",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 3",
pages = "278--286",
booktitle = "Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings",
edition = "PART 3",
note = "13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 ; Conference date: 20-09-2010 Through 24-09-2010",
}