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Chest X-Ray Classification

This repository proposes a workflow for training and evaluating deep learning models designed to classify chest X-ray images using PyTorch.

Objective

The purpose of this project is to develop a system capable of accurately classifying chest X-ray images into different categories, such as pleural effusion, pneumonia, cardiomegaly, or other abnormalities.

Information about the Dataset

The models used for classification have been trained using PadChest Datataset

Bustos, A., Pertusa, A., Salinas, J. M., & De La Iglesia-Vaya, M. (2020). Padchest: A large chest x-ray image dataset with multi-label annotated reports. Medical image analysis, 66, 101797.

Prerequisites

  • Anaconda
  • PyTorch
    • version 2.0.1 or above
  • Scikit-learn
    • version 1.3.0 or above
  • Matplotlib
  • Pandas

Installation

Clone this repository:

git clone https://github.com/mt4sd/ChestXRayClassification.git

or click Download ZIP in right panel of repository and extract it.