ADLM Medical Image Segmentation
Apr 2024 – Aug 2024 • Chair for AI in Medicine and Healthcare (TUM)
A practical research project conducted with the Chair for AI in Medicine and Healthcare at the Technical University of Munich, focusing on deep learning techniques for medical image segmentation.
Research and Implementation Details
- Resolution Differences Analysis: Investigated how image resolution variations impact segmentation accuracy across 3D medical imaging scans.
- Framework & Models: Utilized PyTorch, Deep Learning architectures (CNNs, U-Net variants), and state-of-the-art nnU-Net self-configuring frameworks.
- Domain Application: Applied computer vision and biomedical image processing pipelines for automatic region-of-interest extraction and organ/lesion segmentation.
Links and Resources
- GitHub Repository: github.com/carloslme/adlm-segmentation