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Journal of Visualization

Erschienen in:

21.09.2020 | Regular Paper

An automatic tooth reconstruction method based on multimodal data

verfasst von: Jiahong Qian, Shijuan Lu, Yuan Gao, Yubo Tao, Jun Lin, Hai Lin

Erschienen in: Journal of Visualization | Ausgabe 1/2021

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Abstract

A complete digital tooth model with both the dental crown and root is of great importance for computer-aided orthodontic treatment. This paper first proposes an automatic segmentation method for complete tooth models with both the crown and reconstructed root based on multimodal data. With the laser-scanned crown mesh and cone-beam computed tomography (CBCT) data of a patient, we propose an improved iterative closest point algorithm and convex hull selection method to obtain the initial contour and slice for segmentation. Based on the initialization, we propose an improved level set method with the shape prior, named LSS, to segment the root of the tooth slice by slice. After segmentation, we reconstruct the root model and replace the crown part with the scanned crown model to solve the occlusal problem. The experiments demonstrate that our method can obtain tooth models from CBCT automatically and accurately.

Graphical abstract

Vorheriger Artikel Colormap optimization with data equality

Nächster Artikel Correction to: An automatic tooth reconstruction method based on multimodal data

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Titel: An automatic tooth reconstruction method based on multimodal data
verfasst von: Jiahong Qian
Shijuan Lu
Yuan Gao
Yubo Tao
Jun Lin
Hai Lin
Publikationsdatum: 21.09.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Visualization / Ausgabe 1/2021
Print ISSN: 1343-8875
Elektronische ISSN: 1875-8975
DOI: https://doi.org/10.1007/s12650-020-00697-0

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