Cutting-edge multi-task model: unveiling COVID-19 through fusion of image processing algorithms-Reference-Cited by-同舟云学术

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Cutting-edge multi-task model: unveiling COVID-19 through fusion of image processing algorithms

Published:2023-12-05 Issue: Volume: Page:1-10
ISSN:2168-1163
Container-title:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization

Author:

Kordnoori Shirin¹,Sabeti Maliheh¹,Mostafaei Hamidreza²,Seyed Agha Banihashemi Saeed³

Affiliation:

1. Department of Computer Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran

2. Department of Statistics, North Tehran Branch, Islamic Azad University, Tehran, Iran

3. Department of Mathematics, North Tehran Branch, Islamic Azad University, Tehran, Iran

Publisher

Informa UK Limited

Subject

Computer Science Applications,Radiology, Nuclear Medicine and imaging,Biomedical Engineering,Computational Mechanics

Link

https://www.tandfonline.com/doi/pdf/10.1080/21681163.2023.2287521

Reference37 articles.

1. Automatic clustering method to segment COVID-19 CT images

2. COVIR: A virtual rendering of a novel NN architecture O-Net for COVID-19 Ct-scan automatic lung lesions segmentation

3. Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation

4. CXGNet: A tri-phase chest X-ray image classification for COVID-19 diagnosis using deep CNN with enhanced grey-wolf optimizer

5. Aria M Ghaderzadeh M Asadi F Jafari R. 2021. COVID-19 Lung CT Scans. https://www.kaggle.com/dsv/1875670 10.34740/KAGGLE/DSV/1875670

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