ETU-Net: efficient Transformer and convolutional U-style connected attention segmentation network applied to endoscopic image of epistaxis

ETU-Net: efficient Transformer and convolutional U-style connected attention segmentation network applied to endoscopic image of epistaxis

Epistaxis is a typical presentation in the otolaryngology and emergency department. When compressive therapy fails, directive nasal cautery is necessary, which strongly recommended operating under the nasal endoscope if it is possible. Limited by the operator's clinical experience, complication...

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Bibliographic Details
Main Authors: Junyang Chen, Qiurui Liu, Zedong Wei, Xi Luo, Mengzhen Lai, Hongkun Chen, Junlin Liu, Yanhong Xu, Jun Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Medicine
Subjects:
epistaxis
nasal endoscope
deep learning
image segmentation
Transformer
attention mechanism
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2023.1198054/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2023.1198054/full

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