It represents a prerequisite for medical image analysis and supports entire clinical workflows from computer-aided diagnosis to therapy planning, intervention, and follow-up. Segmentation of medical and dental images is a visual task that aims to identify the voxels of organs or lesions from background grey-level scans.

The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. Data are available from the University of Michigan Institutional Review Board (Contact Robert Eber, email for researchers who meet the criteria for access to confidential data.įunding: This work was supported by NIDCR R01 024450, American Association of Orthodontists Foundation Grabber Family Teaching and Research Award and by Research Enhancement Award Activity 141 from the University of the Pacific, Arthur A. The database cannot be shared publicly because the scans contain the patient facial skin that could allow facial recognition. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: We have made all the code available at “ ” that can be used to replicate this study. Received: Accepted: SeptemPublished: October 12, 2022Ĭopyright: © 2022 Gillot et al.

(2022) Automatic multi-anatomical skull structure segmentation of cone-beam computed tomography scans using 3D UNETR. Citation: Gillot M, Baquero B, Le C, Deleat-Besson R, Bianchi J, Ruellas A, et al.

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