Self-paced Multi-view Learning for CT-based severity assessment of COVID-19-Reference-Cited by-同舟云学术

Self-paced Multi-view Learning for CT-based severity assessment of COVID-19

Published:2023-05 Issue: Volume:83 Page:104672
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Liu Yishu,Chen Bingzhi,Zhang Zheng,Yu Hongbing,Ru Shouhang,Chen Xiaosheng,Lu Guangming

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference57 articles.

1. A novel deep learning based method for COVID-19 detection from CT image;JavadiMoghaddam;Biomed. Signal Process. Control,2021

2. COVID-19 CT image denoising algorithm based on adaptive threshold and optimized weighted median filter;Guo;Biomed. Signal Process. Control,2022

3. COVID-19 disease identification from chest CT images using empirical wavelet transformation and transfer learning;Gaur;Biomed. Signal Process. Control,2022

4. Quantification of pulmonary involvement in COVID-19 pneumonia by means of a cascade of two U-nets: training and assessment on multiple datasets using different annotation criteria;Lizzi,2021

5. Abnormal lung quantification in chest CT images of COVID-19 patients with deep learning and its application to severity prediction;Shan;Med. Phys.,2021

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