Video-SwinUNet: Spatio-temporal Deep Learning Framework for VFSS Instance Segmentation
Author:
Affiliation:
1. University of Bristol,Department of Mechanical Engineering,UK
2. University of Bristol,Department of Computer Science,UK
3. Queen Elizabeth Hospital,Woolwich,UK
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10221937/10221892/10222212.pdf?arnumber=10222212
Reference30 articles.
1. Online Learning for the Hyoid Bone Tracking During Swallowing With Neck Movement Adjustment Using Semantic Segmentation
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3. Deep learning-based auto-segmentation of swallowing and chewing structures in ct;iyer;BioRxiv,2019
4. Automatic Hyoid Bone Tracking in Real-Time Ultrasound Swallowing Videos Using Deep Learning Based and Correlation Filter Based Trackers
5. Simultaneous Truth and Performance Level Estimation (STAPLE): An Algorithm for the Validation of Image Segmentation
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1. Deep learning models for bolus segmentation in videofluoroscopic swallow studies;Journal of Real-Time Image Processing;2024-01-05
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