44 citations · 79 across the 7 of their papers we have counts for
7 papers
BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation
Mo Zhang, Fei Yu, Jie Zhao +2
Blood vessel segmentation is crucial for many diagnostic and research applications. In recent years, CNN-based models have leaded to breakthroughs in the task of segmentation, howe…
MS-GWNN:multi-scale graph wavelet neural network for breast cancer diagnosis
Mo Zhang, Quanzheng Li
Breast cancer is one of the most common cancers in women worldwide, and early detection can significantly reduce the mortality rate of breast cancer. It is crucial to take multi-sc…
PGU-net+: Progressive Growing of U-net+ for Automated Cervical Nuclei Segmentation
Jie Zhao, Lei Dai, Mo Zhang +5
Automated cervical nucleus segmentation based on deep learning can effectively improve the quantitative analysis of cervical cancer. However, accurate nuclei segmentation is still…
Multi-label Detection and Classification of Red Blood Cells in Microscopic Images
Wei Qiu, Jiaming Guo, Xiang Li +4
Cell detection and cell type classification from biomedical images play an important role for high-throughput imaging and various clinical application. While classification of sing…
ASCNet: Adaptive-Scale Convolutional Neural Networks for Multi-Scale Feature Learning
Mo Zhang, Jie Zhao, Xiang Li +2
Extracting multi-scale information is key to semantic segmentation. However, the classic convolutional neural networks (CNNs) encounter difficulties in achieving multi-scale inform…
Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)
Yu Zhao, Xiang Li, Wei Zhang +5
Simultaneous modeling of the spatio-temporal variation patterns of brain functional network from 4D fMRI data has been an important yet challenging problem for the field of cogniti…