Versatile U-Net implementation for volumetric semantic segmentation written in PyTorch
PyTorch implementation of 3D U-Net and its variants (ResidualUNet3D, ResidualUNetSE3D). The code allows for training the U-Net for both: semantic segmentation (binary and multi-class) and regression problems (e.g. de-noising, learning deconvolutions).
