This repository implements Med3D, a transfer learning approach for 3D medical image analysis. It aggregates diverse medical imaging datasets across multiple modalities and pathologies to train 3D-ResNet models that can be fine-tuned for downstream tasks. The project includes pre-trained model weights (ResNet-10/18/34/50) trained on 23 datasets, along with training code for tasks such as segmentation and classification on medical images.