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

OBJECTIVE: To 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. METHODS: The temporal bone HRCT images of 158 patients were...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Xing-Rui, Ma, Xi, Jin, Liu-Xu, Gao, Yan-Jun, Xue, Yong-Jie, Li, Jing-Long, Bai, Wei-Xian, Han, Miao-Fei, Zhou, Qing, Shi, Feng, Wang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9470864/
https://www.ncbi.nlm.nih.gov/pubmed/36120083
http://dx.doi.org/10.3389/fninf.2022.937891

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9470864/
https://www.ncbi.nlm.nih.gov/pubmed/36120083
http://dx.doi.org/10.3389/fninf.2022.937891

Ejemplares similares