Brain-MRI-segmentation

Business Objective:

To create segmentation masks for tumors in the human brain using MRI scans.

📖 Table of Contents

Table of Contents

1. ➤ Dataset
2. ➤ Sample example
3. ➤ How to use the trained model
4. ➤ Sample runtime output of application

💾 Dataset

Source of dataset is kaggle.

The dataset is publicly available. Please refer to the Brain MRI segmentation

🗒️ Sample example

🎯 How to use the trained model

1. Install following required libraries

1. cv2
2. streamlit
3. PIL
4. tensorflow

For more details use requirements.txt file.

`pip install -r /path/to/requirements.txt`

2. Link to trained final model : EfficientNet

3. Download this repo and the trained model folder.

4. change your directory to the file containing application.py and then run the command in terminal.

    `streamlit run application.py`
   

5. Sample images for trying out model Inference Images

🗒️ Sample runtime output of application