Overview

This project aims to classify received MRI images from patients and organize them into appropriate archive folders. In this project, I train a small Convolutional Neural Network (CNN) to classify X-ray images using Kaggle data and deploy it on Streamlit.

Setup

pip install -r requirements.txt

Data Processing

1. Fill in the "kaggle.json" file with your Kaggle API token information.
2. Run the "xray_classifier_data.ipynb" notebook to download and process data

Model Training

1. Run export WANDB_API_KEY=XXXXXXXXX
2. Run the notebook "xray_classifier_model.ipynb" notebook, to train the model.

Inference

Run Streamlit server: streamlit run app.py

Credits

Credits to the Kaggle dataset repos:

• paultimothymooney/chest-xray-pneumonia
• nazmul0087/ct-kidney-dataset-normal-cyst-tumor-and-stone
• abdulkader90/brain-ct-hemorrhage-dataset
• nikhilroxtomar/ct-heart-segmentation
• shashwatwork/knee-osteoarthritis-dataset-with-severity