MIScnn provides an intuitive API for setting up medical image segmentation pipelines with state-of-the-art convolutional neural networks. It handles data I/O, preprocessing, and data augmentation for biomedical images, and supports patch-wise and full image analysis. The library includes built-in deep learning models and metrics, multiple evaluation techniques like cross-validation, and is built on Keras with TensorFlow as the backend.