TransUNet combines Vision Transformers with U-Net architecture to perform medical image segmentation. The model uses pre-trained ViT encoders and introduces transformer layers for enhanced feature extraction. It supports both 2D and 3D medical imaging data and has achieved state-of-the-art results on multiple medical imaging benchmarks including BTCV and BraTS challenges.