How "Magic" Led to MIT Innovation in AI for Neuroscience

At last week's Conference on Computer Vision and Pattern Recognition, a team of researchers from Massachusetts Institute of Technology (MIT) presented an innovative artificial intelligence (AI) system that can learn to segment anatomical brain structures from a single segmented brain scan image along with unlabeled scans--automating neuroscientific image segmentation. This novel AI system for neuroscience originated from a very distant genre of smartphone and gaming. Amy Zhao, a graduate student in the Department of Electrical Engineering and Computer Science (EECS) and Computer Science and Artificial Intelligence Laboratory (CSAIL), and the first author on the research, initially sought to create an app using convolutional neural network technology that could provide detailed information in real-time about cards from the game "Magic: The Gathering" based on a picture taken on a smartphone. The challenge is that this computer vision task would require a data set of photos that contains not only each of the 20,000 cards, but also many more images of each card with variation in appearance and attributes such as lighting. Creating such a data set manually would be painstakingly tedious and extremely time-consuming.