This project applies segmentation techniques to a set of brain imaging data to identify and analyze different brain regions. The Deep Learning model accurately predicts the midslice of the brain MRI image. The model is implemented using the U-Net architecture. The dataset contains 2D slices of brain MRI images and the corresponding masks for the brain regions.
This project demonstrates my ability to make a model that can accurately predict the midslice of the brain MRI image.
I created three different tensorflow models and i chose the model that had the highest quality predictions.
To get started, clone the repository and install the required dependencies:
In Docker and JupyterLab
git clone https://github.com/lucianoscarpaci/UNet-Brain-Image-Segmentation.gitThis project is licensed under the MIT License.