📊 Data-Driven Image Processing

This repository contains my uni work and experiments in data-driven image processing using deep learning in the medical space. It includes projects focused on medical image registration, segmentation, and restoration.

📁 Project Structure

• Registration/ – Image registration using models like VoxelMorph
• Segmentation/ – Deep learning-based medical image segmentation (e.g. U-Net)
• Restoration/ – Image restoration and enhancement tasks

🚀 Goals

• Learn and apply data-driven approaches to medical imaging
• Implement and evaluate models such as U-Net and VoxelMorph
• Explore segmentation masks, image alignment, and reconstruction

⚠️ Large dataset files (.npy, .pth) are excluded from the repository due to GitHub size limits.

✍️ Notes

This repository reflects my learning process in applying machine learning to biomedical images. Some components are prototypical or academic in nature.

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Feel free to explore and reach out with suggestions or questions!