X-Ray_Classification-CDAC

X-Ray classification deals with identifying the disease i.e. pneumonia in a person.The objective of this project is to make the work of medical professionals easier and quicker than earlier to detect pneumonia in a person's body. To fulfill the objective of this project, we need the datasets so as to train the model about the differences between normal person and a person having pneumonia.

Dataset for project:

Link- https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia/download

Before running training dataset program download the dataset from the link and place the chest_xray folder, containing train, test and val folders, inside X-Ray_Classification-CDAC folder.

Install process:

git clone https://github.com/prateeksarangi/X-Ray_Classification-CDAC/
cd X-Ray_Classification-CDAC

Create and activate virtual environment:

pip install virtualenv
virtualenv <env_name>
source <env_name>/bin/activate

Installing required packages:

pip install -r requirements.txt

Training dataset on local system:

python TunedNN.py

Runnning the prediction model:

python ServerSide.py

Running the webapp:

python exec.py

After executing exec.py, open localhost:5000 in web browser.

Springer Paper Link

SCI-2020 - https://link.springer.com/chapter/10.1007/978-981-16-1502-3_59

Reference

@incollection{sarangi2021early,
  title={Early Detection of Pneumonia from Chest X-Ray Images Using Deep Learning Approach},
  author={Sarangi, Prateek and Priyadarshan, Pradosh and Mishra, Swagatika and Rath, Adyasha and Panda, Ganapati},
  booktitle={Smart Computing Techniques and Applications},
  pages={595--604},
  year={2021},
  publisher={Springer}
}