BrainTrain

Deep learning pipeline for brain MRI classification with explainability.

Overview

Train and evaluate deep learning models on brain MRI data with explainability methods to visualize model predictions.

Features

• Training - Train deep learning models on brain MRI scans
• Testing - Evaluate model performance on test sets
• Explainability - Generate GradCAM and saliency maps for predictions

Project Structure

.
├── architectures/          # Neural network models
├── dataloaders/           # Dataset loaders
├── src/          # Neural network models
├── dataloaders/           # Dataset loaders
├── train.py               # Model training script
├── test.py                # Model evaluation script
├── heatmap.py             # GradCAM and saliency visualization
└── config.py              # Configuration and paths

Quick Start

1. Train Model

python train.py

Trains the model on your brain MRI dataset and saves checkpoints.

2. Test Model

python test.py

Evaluates the trained model on the test set and reports performance metrics.

3. Generate Explainability Maps

python heatmap.py

Configuration

Edit config.py to customize:

• Data paths
• Model architecture
• Training hyperparameters
• Explainability settings