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The main objective of this project is to develop an intelligent system to detect pneumonia in chest X-ray images. In addition to developing detection algorithms, data exploration, analysis, and preprocessing are also performed.

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DimitrisReppas/Detect-pneumonia-in-chest-X-ray-images

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Detect pneumonia in chest X-ray images

The main objective of the project is to develop an intelligent system to detect pneumonia in chest X-ray images. We consider the following steps:

  • Explore the data and define appropriate classes
  • Visualize data and employ appropriate preprocessing to X-ray images
  • Develop the detection algorithms
    • Using features and classical machine learning techniques
    • Using neural network architectures
  • Presentation of results

The code, to achieve the goals of this project, and the results can be found Project_code.ipynb.

Dataset

The dataset we use for the project can be found https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia. From its structure, we can distinguish 3 folders (test, valid and train)

Download the 3 folders and put them into: /path/to/Detect-pneumonia-in-chest-X-ray-images/

Run locally

To clone the repo:

  git clone https://github.com/DimitrisReppas/Detect-pneumonia-in-chest-X-ray-images.git

Requirements

To install the requirements:

  pip install -r /path/to/Detect-pneumonia-in-chest-X-ray-images/requirements.txt

About

The main objective of this project is to develop an intelligent system to detect pneumonia in chest X-ray images. In addition to developing detection algorithms, data exploration, analysis, and preprocessing are also performed.

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