12 citations · 17 across the 4 of their papers we have counts for
4 papers
Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
Hao Zheng, Jun Han, Hongxiao Wang +4
A large labeled dataset is a key to the success of supervised deep learning, but for medical image segmentation, it is highly challenging to obtain sufficient annotated images for…
Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation
Hongxiao Wang, Hao Zheng, Jianxu Chen +3
Automatic histopathology image segmentation is crucial to disease analysis. Limited available labeled data hinders the generalizability of trained models under the fully supervised…
SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation
Yizhe Zhang, Lin Yang, Hao Zheng +5
Supervised training a deep neural network aims to "teach" the network to mimic human visual perception that is represented by image-and-label pairs in the training data. Superpixel…
A New Ensemble Learning Framework for 3D Biomedical Image Segmentation
Hao Zheng, Yizhe Zhang, Lin Yang +4
3D image segmentation plays an important role in biomedical image analysis. Many 2D and 3D deep learning models have achieved state-of-the-art segmentation performance on 3D biomed…