@article {48166,
	title = {Automatic detection and classification of teeth in CT data.},
	journal = {Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
	volume = {15},
	year = {2012},
	month = {2012},
	pages = {609-16},
	abstract = {<p>We propose a fully automatic method for tooth detection and classification in CT or cone-beam CT image data. First we compute an accurate segmentation of the maxilla bone. Based on this segmentation, our method computes a complete and optimal separation of the row of teeth into 16 subregions and classifies the resulting regions as existing or missing teeth. This serves as a prerequisite for further individual tooth segmentation. We show the robustness of our approach by providing extensive validation on 43 clinical head CT scans.</p>
},
	keywords = {Algorithms, Artifacts, Bone and Bones, Humans, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Maxilla, Models, Statistical, Pattern Recognition, Automated, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Tomography, X-Ray Computed, Tooth},
	author = {Duy, Nguyen The and Lamecker, Hans and Kainmueller, Dagmar and Zachow, Stefan}
}
