239 citations · 437 across the 29 of their papers we have counts for
12 papers · 1 filter
EBHI-Seg: A Novel Enteroscope Biopsy Histopathological Haematoxylin and Eosin Image Dataset for Image Segmentation Tasks
Liyu Shi, Xiaoyan Li, Weiming Hu +15
Background and Purpose: Colorectal cancer is a common fatal malignancy, the fourth most common cancer in men, and the third most common cancer in women worldwide. Timely detection…
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…
A Comparative Study of Gastric Histopathology Sub-size Image Classification: from Linear Regression to Visual Transformer
Weiming Hu, Haoyuan Chen, Wanli Liu +5
Gastric cancer is the fifth most common cancer in the world. At the same time, it is also the fourth most deadly cancer. Early detection of cancer exists as a guide for the treatme…
Application of Graph Based Features in Computer Aided Diagnosis for Histopathological Image Classification of Gastric Cancer
Haiqing Zhang, Chen Li, Shiliang Ai +7
The gold standard for gastric cancer detection is gastric histopathological image analysis, but there are certain drawbacks in the existing histopathological detection and diagnosi…
Application of Transfer Learning and Ensemble Learning in Image-level Classification for Breast Histopathology
Yuchao Zheng, Chen Li, Xiaomin Zhou +8
Background: Breast cancer has the highest prevalence in women globally. The classification and diagnosis of breast cancer and its histopathological images have always been a hot sp…
TOD-CNN: An Effective Convolutional Neural Network for Tiny Object Detection in Sperm Videos
Shuojia Zou, Chen Li, Hongzan Sun +6
The detection of tiny objects in microscopic videos is a problematic point, especially in large-scale experiments. For tiny objects (such as sperms) in microscopic videos, current…
An application of Pixel Interval Down-sampling (PID) for dense tiny microorganism counting on environmental microorganism images
Jiawei Zhang, Xin Zhao, Tao Jiang +7
This paper proposes a novel pixel interval down-sampling network (PID-Net) for dense tiny object (yeast cells) counting tasks with higher accuracy. The PID-Net is an end-to-end con…
A Survey of Semen Quality Evaluation in Microscopic Videos Using Computer Assisted Sperm Analysis
Wenwei Zhao, Pingli Ma, Chen Li +4
The Computer Assisted Sperm Analysis (CASA) plays a crucial role in male reproductive health diagnosis and Infertility treatment. With the development of the computer industry in r…
A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements
Jiawei Zhang, Chen Li, Md Mamunur Rahaman +6
With the acceleration of urbanization and living standards, microorganisms play increasingly important roles in industrial production, bio-technique, and food safety testing. Micro…
A State-of-the-art Survey of U-Net in Microscopic Image Analysis: from Simple Usage to Structure Mortification
Jian Wu, Wanli Liu, Chen Li +7
Image analysis technology is used to solve the inadvertences of artificial traditional methods in disease, wastewater treatment, environmental change monitoring analysis and convol…
What Can Machine Vision Do for Lymphatic Histopathology Image Analysis: A Comprehensive Review
Xiaoqi Li, Haoyuan Chen, Chen Li +6
In the past ten years, the computing power of machine vision (MV) has been continuously improved, and image analysis algorithms have developed rapidly. At the same time, histopatho…