239 citations · 760 across the 11 of their papers we have counts for
11 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…
CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron
Wanli Liu, Chen Li, Ning Xu +9
Cervical cancer is the seventh most common cancer among all the cancers worldwide and the fourth most common cancer among women. Cervical cytopathology image classification is an i…
GasHisSDB: A New Gastric Histopathology Image Dataset for Computer Aided Diagnosis of Gastric Cancer
Weiming Hu, Chen Li, Xiaoyan Li +9
Background and Objective: Gastric cancer has turned out to be the fifth most common cancer globally, and early detection of gastric cancer is essential to save lives. Histopatholog…
Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformers
Wanli Liu, Chen Li, Md Mamunur Rahamana +8
Cervical cancer is a very common and fatal type of cancer in women. Cytopathology images are often used to screen for this cancer. Given that there is a possibility that many error…
GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection
Haoyuan Chen, Chen Li, Ge Wang +9
In this paper, a multi-scale visual transformer model, referred as GasHis-Transformer, is proposed for Gastric Histopathological Image Detection (GHID), which enables the automatic…
A Hierarchical Conditional Random Field-based Attention Mechanism Approach for Gastric Histopathology Image Classification
Yixin Li, Xinran Wu, Chen Li +7
In the Gastric Histopathology Image Classification (GHIC) tasks, which are usually weakly supervised learning missions, there is inevitably redundant information in the images. The…
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…
A Multi-scale CNN-CRF Framework for Environmental Microorganism Image Segmentation
Jinghua Zhang, Chen Li, Frank Kulwa +6
To assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multiscale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper. The…
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…
Stochastic Model Pruning via Weight Dropping Away and Back
Haipeng Jia, Xueshuang Xiang, Da Fan +3
Deep neural networks have dramatically achieved great success on a variety of challenging tasks. However, most successful DNNs have an extremely complex structure, leading to exten…