no code implementations • 15 Apr 2020 • Gaurav Fotedar, Nima Tajbakhsh, Shilpa Ananth, Xiaowei Ding
In this paper, we introduce \emph{extreme consistency}, which overcomes the above limitations, by maximally leveraging unlabeled data from the same or a different domain in a teacher-student semi-supervised paradigm.
no code implementations • 10 Oct 2019 • Nima Tajbakhsh, Brian Lai, Shilpa Ananth, Xiaowei Ding
In this paper, we propose a segmentation framework called ErrorNet, which learns to correct these segmentation mistakes through the repeated process of injecting systematic segmentation errors to the segmentation result based on a learned shape prior, followed by attempting to predict the injected error.