- Keywords: Regularization, Generalization, Data Augmentation, Mixup, Image Segmentation
- TL;DR: We suggest to apply manifold mixup on medical image segmentation.
- Abstract: The scarcity of labeled data is a challenging problem in medical segmentation. Here, we suggest to apply manifold mixup, a recently proposed simple regularizer that utilizes linear combinations of hidden representations of training examples, on prostate cancer segmentation using MR image. Manifold mixup applied to either the encoder or decoder outperformed training without mixup and mixup applied on the input space.
- Code Of Conduct: I have read and accept the code of conduct.
- Remove If Rejected: Remove submission from public view if paper is rejected.