Style Curriculum Learning for Robust Medical Image Segmentation

no code implementations • 1 Aug 2021 • Zhendong Liu, Van Manh, Xin Yang, Xiaoqiong Huang, Karim Lekadir, Víctor Campello, Nishant Ravikumar, Alejandro F Frangi, Dong Ni

A style transfer model with style fusion is employed to generate the curriculum samples.

Medical Image Segmentation Semantic Segmentation +1

Generalize Ultrasound Image Segmentation via Instant and Plug & Play Style Transfer

no code implementations • 11 Jan 2021 • Zhendong Liu, Xiaoqiong Huang, Xin Yang, Rui Gao, Rui Li, Yuanji Zhang, Yankai Huang, Guangquan Zhou, Yi Xiong, Alejandro F Frangi, Dong Ni

Deep segmentation models that generalize to images with unknown appearance are important for real-world medical image analysis.

Semantic Segmentation Style Transfer

Style-invariant Cardiac Image Segmentation with Test-time Augmentation

no code implementations • 24 Sep 2020 • Xiaoqiong Huang, Zejian Chen, Xin Yang, Zhendong Liu, Yuxin Zou, Mingyuan Luo, Wufeng Xue, Dong Ni

Based on the zero-shot style transfer to remove appearance shift and test-time augmentation to explore diverse underlying anatomy, our proposed method is effective in combating the appearance shift.

Cardiac Segmentation Semantic Segmentation +1

Remove Appearance Shift for Ultrasound Image Segmentation via Fast and Universal Style Transfer

no code implementations • 14 Feb 2020 • Zhendong Liu, Xin Yang, Rui Gao, Shengfeng Liu, Haoran Dou, Shuangchi He, Yuhao Huang, Yankai Huang, Huanjia Luo, Yuanji Zhang, Yi Xiong, Dong Ni

In this paper, we propose a novel and intuitive framework to remove the appearance shift, and hence improve the generalization ability of DNNs.

Semantic Segmentation Style Transfer