2 citations · 4 across the 2 of their papers we have counts for
5 papers
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…
Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation
Peixian Liang, Jianxu Chen, Hao Zheng +3
The Encoder-Decoder architecture is a main stream deep learning model for biomedical image segmentation. The encoder fully compresses the input and generates encoded features, and…
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…