Computer Vision News - October 2020

2 Open Source Deep Learning Platform 38 is accomplished within a framework that promotes reproducibility - which is fundamental to open science and of vital importance to medical applications. The openness of MONAI comes from its rapidly expanding community of contributorsandusers, itseaseofuse,and its documentation. MONAI has received over 1,400 stars on github as well as contributions from over 39 developers from around the world. The MONAI team organized a MICCAI endorsed, three-day bootcamp in September of 2020, and that bootcamp received over 560 attendance applications from 40 countries. In version 0.3, the MONAI repositories have been re-organized so that the core repository ismore compact, tutorials are easier to find and follow, and a research repository has been created to host cutting-edge contributions that are companion to recent peer reviewed publications. The recordings from the bootcamp are also being posted on the MONAI website. When we asked MONAI and ITK developers, why do you develop open source deep learning software? The most consistent answer was “ impact ”. The developers wanted their efforts and research to have the biggest possible impact on the medical field, and they saw using and contributing to open source MONAI and ITK as the best way to These open platforms include well established, general purpose systems suchas PyTorchand the Insight Toolkit (ITK), as well as dynamic, cutting- edge, domain specific systems such as the Medical Open Network for AI (MONAI) platform