3 citations · 3 across the 1 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…
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…
Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation
Zhuo Zhao, Lin Yang, Hao Zheng +3
Instance segmentation in 3D images is a fundamental task in biomedical image analysis. While deep learning models often work well for 2D instance segmentation, 3D instance segmenta…
BoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation
Lin Yang, Yizhe Zhang, Zhuo Zhao +5
In recent years, deep learning (DL) methods have become powerful tools for biomedical image segmentation. However, high annotation efforts and costs are commonly needed to acquire…