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COVID Lung X-Rays Classification with Deep Learning

This project is a fork of MAR24_BDS_Radios_Pulmonaire which was developped during the Data Scientist course of Datascientest from March to June 2024.

The primary goal of this fork is to introduce new features and improvements to enhance functionality, the user interface and performance.

Improvements

  • Added references for dataset, models and images.
  • Provided context of the project on the homepage.
  • Redesigned the footer.
  • Light code refactoring.
  • Added some lung x-rays images for demo.
  • Introduced a lung segmentation model.
  • Deep code refactoring?

View the updated streamlit app on Hugging Face 🤗

How to deploy the streamlit app on Hugging Face:

  • Create a new space on Hugging Face and clone the repository
  • Push the content of the src/streamlit directory
  • Add the model's weights file to the models folder
  • Store the model weights in Git LFS by adding the following line to the .gitattributes file:
    *.h5 filter=lfs diff=lfs merge=lfs -text
  • Push to Huggingface
  • Do not modify or delete the REAMDE.md file created by Hugging Face during the initialization on the space.

Dataset

The COVID-QU-Ex dataset is available on Kaggle: https://www.kaggle.com/datasets/anasmohammedtahir/covidqu

[1] A. M. Tahir, M. E. H. Chowdhury, A. Khandakar, Y. Qiblawey, U. Khurshid, S. Kiranyaz, N. Ibtehaz, M. S. Rahman, S. Al-Madeed, S. Mahmud, M. Ezeddin, K. Hameed, and T. Hamid, “COVID-19 Infection Localization and Severity Grading from Chest X-ray Images”, Computers in Biology and Medicine, vol. 139, p. 105002, 2021, https://doi.org/10.1016/j.compbiomed.2021.105002.

[2] Anas M. Tahir, Muhammad E. H. Chowdhury, Yazan Qiblawey, Amith Khandakar, Tawsifur Rahman, Serkan Kiranyaz, Uzair Khurshid, Nabil Ibtehaz, Sakib Mahmud, and Maymouna Ezeddin, “COVID-QU-Ex .” Kaggle, 2021, https://doi.org/10.34740/kaggle/dsv/3122958.

[3] T. Rahman, A. Khandakar, Y. Qiblawey A. Tahir S. Kiranyaz, S. Abul Kashem, M. Islam, S. Al Maadeed, S. Zughaier, M. Khan, M. Chowdhury, "Exploring the Effect of Image Enhancement Techniques on COVID-19 Detection using Chest X-rays Images," Computers in Biology and Medicine, p. 104319, 2021, https://doi.org/10.1016/j.compbiomed.2021.104319.

[4] A. Degerli, M. Ahishali, M. Yamac, S. Kiranyaz, M. E. H. Chowdhury, K. Hameed, T. Hamid, R. Mazhar, and M. Gabbouj, "Covid-19 infection map generation and detection from chest X-ray images," Health Inf Sci Syst 9, 15 (2021), https://doi.org/10.1007/s13755-021-00146-8.

[5] M. E. H. Chowdhury, T. Rahman, A. Khandakar, R. Mazhar, M. A. Kadir, Z. B. Mahbub, K. R. Islam, M. S. Khan, A. Iqbal, N. A. Emadi, M. B. I. Reaz, M. T. Islam, "Can AI Help in Screening Viral and COVID-19 Pneumonia?," IEEE Access, vol. 8, pp. 132665-132676, 2020, https://doi.org/10.1109/ACCESS.2020.3010287.

Original Project:

supervised by: Gaël Penessot

View the original streamlit app on Hugging Face 🤗

Project based on the cookiecutter data science project template. #cookiecutterdatascience