The increased need for automatic medical image segmentation has been created due to the enormous usage of modern medical imaging in technology. Despite this large need, the current medical image segmentation platforms do not provide required functionalities for the plain setup of medical image segmentation pipelines. Therefore this paper introduces the open-source Python library MIScnn. MIScnn is an opensource framework with intuitive APIs allowing the fast setup of medical image segmentation pipelines with Convolutional Neural Network and DeepLearning models in just a few lines of code. The objective of MIScnn according to paper is to provide a framework API that can be allowing the fast building of medical image segmentation pipelines including data I/O, preprocessing, data augmentation, patch-wise analysis, metrics, a library with state-of-the-art deep learning models and model utilization like training, prediction, as well as fully automatic evaluation (e.g.