CDC_Net: multi-classification convolutional neural network model for detection of COVID-19, pneumothorax, pneumonia, lung Cancer, and tuberculosis using chest X-rays-Reference-Cited by-同舟云学术

CDC_Net: multi-classification convolutional neural network model for detection of COVID-19, pneumothorax, pneumonia, lung Cancer, and tuberculosis using chest X-rays

Published:2022-09-20 Issue:9 Volume:82 Page:13855-13880
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Malik Hassaan^ORCID,Anees Tayyaba,Din Muizzud,Naeem Ahmad

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-022-13843-7.pdf

Reference105 articles.

1. Abbas A, Abdelsamea MM, Gaber MM (2020) Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network. Appl Intell 51:854–864. https://doi.org/10.1007/s10489-020-01829-7

2. Alqudah AM, Qazan S (2020) Augmented COVID-19 X-ray images dataset, 4. https://doi.org/10.17632/2FXZ4PX6D8.4

3. Alqudah AM, Qazan S, Masad IS (2021) Artificial intelligence framework for efficient detection and classification of pneumonia using chest radiography images. J Med Biol Eng 41:599–609

4. Apostolopoulos ID, Mpesiana TA (2020) COVID-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks. Phys Eng Sci Med 43(2):635–640. https://doi.org/10.1007/s13246-020-00865-4

5. Ayan E, Ünver HM (2019) Diagnosis of pneumonia from chest x-ray images using deep learning. In: 2019 scientific meeting on Electrical-Electronics & Biomedical Engineering and computer science (EBBT). IEEE. pp 1-ll

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