Skip to content

A Capsule Network based approach to detect diagnosing COVID-19 cases using Chest X-ray (CXR) images.

Notifications You must be signed in to change notification settings

Harsh9524/COVID-WideNet

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

87 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

COVID-WideNet—A capsule network for COVID-19 detection

Python 3.8 PWC harshpanwar

This repo is the official Implementation of the paper - COVID-WideNet—A capsule network for COVID-19 detection

🏆 SOTA for COVID-19 Diagnosis on COVIDx (AUC metric) check out papers with code

Abstract

In this paper, we propose a capsule network called COVID-WideNet for diagnosing COVID-19 cases using Chest X-ray (CXR) images. Experimental results have demonstrated that a discriminative trained, multi-layer capsule network achieves state-of-the-art performance on the COVIDx dataset. In particular, COVID-WideNet performs better than any other CNN based approaches for the diagnosis of COVID-19 infected patients. Further, the proposed COVID-WideNet has the number of trainable parameters that is 20 times less than that of other CNN based models. This results in a fast and efficient diagnosing COVID-19 symptoms, and with achieving the 0.95 of Area Under Curve (AUC), 91% of accuracy, sensitivity and specificity, respectively. This may also assist radiologists to detect COVID and its variant like delta.

alt text

Dataset: COVIDx

An open access benchmark dataset comprising of 13,975 CXR images across 13,870 patient cases, with the largest number of publicly available COVID-19 positive cases to the best of the authors' knowledge.

The dataset can be downloaded from the following link: https://paperswithcode.com/dataset/covidx

Citation

@article{gupta2022covid,
  title={COVID-WideNet—A capsule network for COVID-19 detection},
  author={Gupta, PK and Siddiqui, Mohammad Khubeb and Huang, Xiaodi and Morales-Menendez, Ruben and Pawar, Harsh and Terashima-Marin, Hugo and Wajid, Mohammad Saif},
  journal={Applied Soft Computing},
  volume={122},
  pages={108780},
  year={2022},
  publisher={Elsevier}
}

Base Code Inspiration:

capsulelayers.py inspired from https://github.com/XifengGuo/CapsNet-Keras/blob/master/capsulelayers.py
train.py inspired from changspencer/Tumor-CapsNet#3
preprocess.py inspired from https://github.com/ShahinSHH/COVID-CAPS

About

A Capsule Network based approach to detect diagnosing COVID-19 cases using Chest X-ray (CXR) images.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages