24 citations · 104 across the 24 of their papers we have counts for
5 papers · 1 filter
ACT-Net: Asymmetric Co-Teacher Network for Semi-supervised Memory-efficient Medical Image Segmentation
Ziyuan Zhao, Andong Zhu, Zeng Zeng +2
While deep models have shown promising performance in medical image segmentation, they heavily rely on a large amount of well-annotated data, which is difficult to access, especial…
MMGL: Multi-Scale Multi-View Global-Local Contrastive learning for Semi-supervised Cardiac Image Segmentation
Ziyuan Zhao, Jinxuan Hu, Zeng Zeng +4
With large-scale well-labeled datasets, deep learning has shown significant success in medical image segmentation. However, it is challenging to acquire abundant annotations in cli…
Self-supervised Assisted Active Learning for Skin Lesion Segmentation
Ziyuan Zhao, Wenjing Lu, Zeng Zeng +3
Label scarcity has been a long-standing issue for biomedical image segmentation, due to high annotation costs and professional requirements. Recently, active learning (AL) strategi…
Object-Aware Self-supervised Multi-Label Learning
Xu Kaixin, Liu Liyang, Zhao Ziyuan +2
Multi-label Learning on Image data has been widely exploited with deep learning models. However, supervised training on deep CNN models often cannot discover sufficient discriminat…
A predictive analytics approach for stroke prediction using machine learning and neural networks
Soumyabrata Dev, Hewei Wang, Chidozie Shamrock Nwosu +3
The negative impact of stroke in society has led to concerted efforts to improve the management and diagnosis of stroke. With an increased synergy between technology and medical di…