Search Results for author: Tomomi Nobashi

Found 1 papers, 0 papers with code

CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss

no code implementations27 Nov 2018 Blaine Rister, Darvin Yi, Kaushik Shivakumar, Tomomi Nobashi, Daniel L. Rubin

To achieve the best results from data augmentation, our model uses the intersection-over-union (IOU) loss function, a close relative of the Dice loss.

Data Augmentation Image Segmentation +2

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