Application value of a deep learning method based on a 3D V-Net convolutional neural network in the recognition and segmentation of the auditory ossicles

Application value of a deep learning method based on a 3D V-Net convolutional neural network in the recognition and segmentation of the auditory ossicles

ObjectiveTo explore the feasibility of a deep learning three-dimensional (3D) V-Net convolutional neural network to construct high-resolution computed tomography (HRCT)-based auditory ossicle structure recognition and segmentation models.MethodsThe temporal bone HRCT images of 158 patients were coll...

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Bibliographic Details
Main Authors: Xing-Rui Wang, Xi Ma, Liu-Xu Jin, Yan-Jun Gao, Yong-Jie Xue, Jing-Long Li, Wei-Xian Bai, Miao-Fei Han, Qing Zhou, Feng Shi, Jing Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Neuroinformatics
Subjects:
auditory ossicles
automatic segmentation
computed tomography
convolutional neural network
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fninf.2022.937891/full

Internet

https://www.frontiersin.org/articles/10.3389/fninf.2022.937891/full

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