322 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- China Medical UniversityTW7 papers
- Northeastern UniversityUS6 papers
- Chinese Academy of SciencesCN4 papers
- Shenyang Institute of AutomationCN3 papers
- Chengdu University of Information TechnologyCN2 papers
- Nanjing University of Science and TechnologyCN2 papers
- Stevens Institute of TechnologyUS2 papers
- First Affiliated Hospital of Liaoning Medical UniversityCN1 paper
- Shenyang UniversityCN1 paper
- Shenzhen Institutes of Advanced TechnologyCN1 paper
- University of Chinese Academy of SciencesCN1 paper
- University of LübeckDE1 paper
7 papers
IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach
Haoyuan Chen, Chen Li, Xiaoyan Li +8
In recent years, colorectal cancer has become one of the most significant diseases that endanger human health. Deep learning methods are increasingly important for the classificati…
DeepCervix: A Deep Learning-based Framework for the Classification of Cervical Cells Using Hybrid Deep Feature Fusion Techniques
Md Mamunur Rahaman, Chen Li, Yudong Yao +4
Cervical cancer, one of the most common fatal cancers among women, can be prevented by regular screening to detect any precancerous lesions at early stages and treat them. Pap smea…
Dynamic radiomics: a new methodology to extract quantitative time-related features from tomographic images
Fengying Che, Ruichuan Shi, Jian Wu +6
The feature extraction methods of radiomics are mainly based on static tomographic images at a certain moment, while the occurrence and development of disease is a dynamic process…
Local Label Point Correction for Edge Detection of Overlapping Cervical Cells
Jiawei Liu, Huijie Fan, Qiang Wang +5
Accurate labeling is essential for supervised deep learning methods. However, it is almost impossible to accurately and manually annotate thousands of images, which results in many…
A Comprehensive Review for MRF and CRF Approaches in Pathology Image Analysis
Yixin Li, Chen Li, Xiaoyan Li +7
Pathology image analysis is an essential procedure for clinical diagnosis of many diseases. To boost the accuracy and objectivity of detection, nowadays, an increasing number of co…
A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks
Xiaomin Zhou, Chen Li, Md Mamunur Rahaman +6
Breast cancer is one of the most common and deadliest cancers among women. Since histopathological images contain sufficient phenotypic information, they play an indispensable role…
Gastric histopathology image segmentation using a hierarchical conditional random field
Changhao Sun, Chen Li, Jinghua Zhang +7
For the Convolutional Neural Networks (CNNs) applied in the intelligent diagnosis of gastric cancer, existing methods mostly focus on individual characteristics or network framewor…