Deep learning-driven ultrasound-assisted diagnosis: optimizing GallScopeNet for precise identification of biliary atresia

Deep learning-driven ultrasound-assisted diagnosis: optimizing GallScopeNet for precise identification of biliary atresia

BackgroundBiliary atresia (BA) is a severe congenital biliary developmental abnormality threatening neonatal health. Traditional diagnostic methods rely heavily on experienced radiologists, making the process time-consuming and prone to variability. The application of deep learning for the automated...

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Bibliographic Details
Main Authors: Yupeng Niu, Jingze Li, Xiyuan Xu, Pu Luo, Pingchuan Liu, Jian Wang, Jiong Mu
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-10-01
Series:Frontiers in Medicine
Subjects:
biliary atresia (BA)
deep learning
ultrasound diagnosis
feature extraction
clinical application
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2024.1445069/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2024.1445069/full

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