Publisher’s Note: This paper, originally published on 15 February 2021, was replaced with a corrected/revised version on 13 May 2021. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.
Mandibular meshes segmented from computerized tomography (CT) images contain rich information of the dentition conditions, which impairs the performance of shape completion algorithms relying on such data, but can benefit virtual planning for oral reconstructive surgeries. To locate the alveolar process and remove the dentition area, we propose a tooth segmentation method including a preprocessing step using non-rigid registration, an active contour model, and constructive solid geometry (CSG) operations. An easy-to-use interactive tool is developed, allowing users to adjust the tooth crown contour position. A validation study and a comparison study were conducted for method evaluation. In the validation study, we removed teeth for 28 models acquired from Vancouver General Hospital (VGH) and ran a shape completion test. Regarding 95th percentile Hausdorff distance (HD95), using edentulous models produced significantly better predictions of the premorbid shapes of diseased mandibles than using models with inconsistent dentition conditions(Z = -2.484, p = 0.01). The volumetric Dice score (DSC) shows no significant difference. In the second study, we compared the proposed method to manual removal in terms of manual processing time, symmetric HD95, and symmetric root mean square deviation (RMSD). The result indicates that our method reduced the manual processing time by 40% on average and approached the accuracy of manual tooth segmentation. It is promising to warrant further efforts towards clinical usage. This work forms the basis of a useful tool for coupling jaw reconstruction and restorative dentition for patient treatment planning.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.