Automated 3D segmentation of the hyoid bone in CBCT using nnU-Net v2: a retrospective study on model performance and potential clinical utility

Automated 3D segmentation of the hyoid bone in CBCT using nnU-Net v2: a retrospective study on model performance and potential clinical utility

Abstract Objective This study aimed to identify the hyoid bone (HB) using the nnU-Net based artificial intelligence (AI) model in cone beam computed tomography (CBCT) images and assess the model’s success in automatic segmentation. Methods CBCT images of 190 patients were randomly selected. The raw...

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Bibliographic Details
Main Authors: Ismail Gümüssoy, Emre Haylaz, Suayip Burak Duman, Fahrettin Kalabalik, Seyda Say, Ozer Celik, Ibrahim Sevki Bayrakdar
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Medical Imaging
Subjects:
Hyoid bone
Cone-beam computed tomography
Artificial intelligence
Convolutional neural network
Online Access:https://doi.org/10.1186/s12880-025-01797-9
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https://doi.org/10.1186/s12880-025-01797-9

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