Prediction of Cranio-Maxilofacial Surgical Planning using an Inverse Soft Tissue Modelling Approach

Shahim, Kamal; Jürgens, Philipp; Cattin, Philippe C.; Nolte, Lutz-P.; Reyes, Mauricio (October 2013). Prediction of Cranio-Maxilofacial Surgical Planning using an Inverse Soft Tissue Modelling Approach. In: The 16th Conference on Medical Image Computing and Computer Assisted Intervention — MICCAI 2013. Lecture Notes in Computer Science: Vol. 7908 (pp. 18-25). Springer 10.1007/978-3-642-40811-3_3

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In cranio-maxillofacial surgery, the determination of a proper surgical plan is an important step to attain a desired aesthetic facial profile and a complete denture closure. In the present paper, we propose an efficient modeling approach to predict the surgical planning on the basis of the desired facial appearance and optimal occlusion. To evaluate the proposed planning approach, the predicted osteotomy plan of six clinical cases that underwent CMF surgery were compared to the real clinical plan. Thereafter, simulated soft-tissue outcomes were compared using the predicted and real clinical plan. This preliminary retrospective comparison of both osteotomy planning and facial outlook shows a good agreement and thereby demonstrates the potential application of the proposed approach in cranio-maxillofacial surgical planning prediction.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB [discontinued]

UniBE Contributor:

Shahim, Kamal, Nolte, Lutz-Peter, Reyes, Mauricio

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health
000 Computer science, knowledge & systems

ISBN:

978-3-642-40811-3

Series:

Lecture Notes in Computer Science

Publisher:

Springer

Language:

English

Submitter:

Mauricio Antonio Reyes Aguirre

Date Deposited:

15 Apr 2014 10:30

Last Modified:

02 Mar 2023 23:24

Publisher DOI:

10.1007/978-3-642-40811-3_3

BORIS DOI:

10.7892/boris.46457

URI:

https://boris.unibe.ch/id/eprint/46457

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