Tirthajit Baruah

Two-Fold Patch Perturbation for Efficient Self-Supervised Learning in 3D Medical Imaging

Self-supervised pre-training has become a key paradigm for reducing annotation costs in 3D medical imaging, yet many recent approaches rely on complex objectives or incur substantial computational overhead. We propose a simple and efficient self-supervised pre-training framework for 3D medical image