Residual Dilated U-net For The Segmentation Of COVID-19 Infection From CT Images-Reference-Cited by-同舟云学术

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Residual Dilated U-net For The Segmentation Of COVID-19 Infection From CT Images

Published:2021-10 Issue: Volume: Page:
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Container-title:2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
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Author:

Amer Alyaa,Ye Xujiong,Janan Faraz

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9607382/9607383/09607760.pdf?arnumber=9607760

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Semi-supervised CT image segmentation via contrastive learning based on entropy constraints;Biomedical Engineering Letters;2024-05-23

2. Recent developments in segmentation of COVID-19 CT images using deep-learning: An overview of models, techniques and challenges;Biomedical Signal Processing and Control;2024-05

3. An efficient Covid-19 detection and severity analysis using optimized mask region-based convolution neural network;Journal of Intelligent & Fuzzy Systems;2023-12-02

4. Pseudo-Label Guided Image Synthesis for Semi-Supervised COVID-19 Pneumonia Infection Segmentation;IEEE Transactions on Medical Imaging;2023-03

5. A Systematic Literature Review of Deep Learning Algorithms for Segmentation of the COVID-19 Infection;Computers, Materials & Continua;2023

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