322 citations · 1.2k across the 34 of their papers we have counts for
34 papers
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…
Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features
Frank Kulwa, Chen Li, Marcin Grzegorzek +3
The use of Environmental Microorganisms (EMs) offers a highly efficient, low cost and harmless remedy to environmental pollution, by monitoring and decomposing of pollutants. This…
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…
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…
EBHI:A New Enteroscope Biopsy Histopathological H&E Image Dataset for Image Classification Evaluation
Weiming Hu, Chen Li, Xiaoyan Li +9
Background and purpose: Colorectal cancer has become the third most common cancer worldwide, accounting for approximately 10% of cancer patients. Early detection of the disease is…
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…
EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification and Detection Methods Evaluation
Peng Zhao, Chen Li, Md Mamunur Rahaman +7
Environmental microorganisms (EMs) are ubiquitous around us and have an important impact on the survival and development of human society. However, the high standards and strict re…
EMDS-7: Environmental Microorganism Image Dataset Seventh Version for Multiple Object Detection Evaluation
Hechen Yang, Chen Li, Xin Zhao +10
The Environmental Microorganism Image Dataset Seventh Version (EMDS-7) is a microscopic image data set, including the original Environmental Microorganism images (EMs) and the corr…
Applications of Artificial Neural Networks in Microorganism Image Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to Popular Convolutional Neural Network and Potential Visual Transformer
Jinghua Zhang, Chen Li, Yimin Yin +2
Microorganisms are widely distributed in the human daily living environment. They play an essential role in environmental pollution control, disease prevention and treatment, and f…
A Comparison for Patch-level Classification of Deep Learning Methods on Transparent Environmental Microorganism Images: from Convolutional Neural Networks to Visual Transformers
Hechen Yang, Chen Li, Jinghua Zhang +5
Nowadays, analysis of Transparent Environmental Microorganism Images (T-EM images) in the field of computer vision has gradually become a new and interesting spot. This paper compa…
A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers
Peng Zhao, Chen Li, Md Mamunur Rahaman +5
In recent years, deep learning has made brilliant achievements in Environmental Microorganism (EM) image classification. However, image classification of small EM datasets has stil…
A Comparison for Anti-noise Robustness of Deep Learning Classification Methods on a Tiny Object Image Dataset: from Convolutional Neural Network to Visual Transformer and Performer
Ao Chen, Chen Li, Haoyuan Chen +6
Image classification has achieved unprecedented advance with the the rapid development of deep learning. However, the classification of tiny object images is still not well investi…
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…
A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: From Classical Methods to Deep Learning Approaches
Pingli Ma, Chen Li, Md Mamunur Rahaman +5
Microorganisms play a vital role in human life. Therefore, microorganism detection is of great significance to human beings. However, the traditional manual microscopic detection m…
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 State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformers
Xintong Li, Weiming Hu, Chen Li +5
To increase the objectivity and accuracy of pathologists' work, artificial neural network(ANN) methods have been generally needed in the segmentation, classification, and detection…
A Comprehensive Review of Image Analysis Methods for Microorganism Counting: From Classical Image Processing to Deep Learning Approaches
Jiawei Zhang, Chen Li, Md Mamunur Rahaman +6
Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techni…