Deep Learning for the Automatic Segmentation of Extracranial Venous Malformations of the Head and Neck from MR Images Using 3D U-Net

Background: It is difficult to characterize extracranial venous malformations (VMs) of the head and neck region from magnetic resonance imaging (MRI) manually and one at a time. We attempted to perform the automatic segmentation of lesions from MRI of extracranial VMs using a convolutional neural ne...

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Detalles Bibliográficos
Autores principales: Ryu, Jeong Yeop, Hong, Hyun Ki, Cho, Hyun Geun, Lee, Joon Seok, Yoo, Byeong Cheol, Choi, Min Hyeok, Chung, Ho Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9573069/
https://www.ncbi.nlm.nih.gov/pubmed/36233460
http://dx.doi.org/10.3390/jcm11195593

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9573069/
https://www.ncbi.nlm.nih.gov/pubmed/36233460
http://dx.doi.org/10.3390/jcm11195593

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