4 citations · 13 across the 9 of their papers we have counts for
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eess.IV2021★ 1 cited
Style Curriculum Learning for Robust Medical Image Segmentation
Zhendong Liu, Van Manh, Xin Yang +6
The performance of deep segmentation models often degrades due to distribution shifts in image intensities between the training and test data sets. This is particularly pronounced…
eess.IV2021
Generalize Ultrasound Image Segmentation via Instant and Plug & Play Style Transfer
Zhendong Liu, Xiaoqiong Huang, Xin Yang +8
Deep segmentation models that generalize to images with unknown appearance are important for real-world medical image analysis. Retraining models leads to high latency and complex…
eess.IV2020★ 2 cited
Style-invariant Cardiac Image Segmentation with Test-time Augmentation
Xiaoqiong Huang, Zejian Chen, Xin Yang +5
Deep models often suffer from severe performance drop due to the appearance shift in the real clinical setting. Most of the existing learning-based methods rely on images from mult…