no code implementations • MIDL 2019 • Nazanin Mohammadi Sepahvand, Raghav Mehta, Douglas Lorne Arnold, Doina Precup, Tal Arbel
In this paper, we develop a modified U-Net architecture to accurately segment new and enlarging lesions in longitudinal MRI, based on multi-modal MRI inputs, as well as subtrac- tion images between timepoints, in the context of large-scale clinical trial data for patients with Multiple Sclerosis (MS).
