322 citations · 714 across the 25 of their papers we have counts for
25 papers
Self-supervised Noise2noise Method Utilizing Corrupted Images with a Modular Network for LDCT Denoising
Yuting Zhu, Qiang He, Yudong Yao +1
Deep learning is a very promising technique for low-dose computed tomography (LDCT) image denoising. However, traditional deep learning methods require paired noisy and clean datas…
NL-CS Net: Deep Learning with Non-Local Prior for Image Compressive Sensing
Shuai Bian, Shouliang Qi, Chen Li +2
Deep learning has been applied to compressive sensing (CS) of images successfully in recent years. However, existing network-based methods are often trained as the black box, in wh…
Quadratic Graph Attention Network (Q-GAT) for Robust Construction of Gene Regulatory Networks
Hui Zhang, Xuexin An, Qiang He +4
Gene regulatory relationships can be abstracted as a gene regulatory network (GRN), which plays a key role in characterizing complex cellular processes and pathways. Recently, grap…
3D PETCT Tumor Lesion Segmentation via GCN Refinement
Hengzhi Xue, Qingqing Fang, Yudong Yao +1
Whole-body PET/CT scan is an important tool for diagnosing various malignancies (e.g., malignant melanoma, lymphoma, or lung cancer), and accurate segmentation of tumors is a key p…
QS-ADN: Quasi-Supervised Artifact Disentanglement Network for Low-Dose CT Image Denoising by Local Similarity Among Unpaired Data
Yuhui Ruan, Qiao Yuan, Chuang Niu +4
Deep learning has been successfully applied to low-dose CT (LDCT) image denoising for reducing potential radiation risk. However, the widely reported supervised LDCT denoising netw…
Quasi-supervised Learning for Super-resolution PET
Guangtong Yang, Chen Li, Yudong Yao +2
Low resolution of positron emission tomography (PET) limits its diagnostic performance. Deep learning has been successfully applied to achieve super-resolution PET. However, common…
Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature Representation
Tingting Shen, Junhang Li, Can Tong +4
Nonnegative matrix factorization (NMF) has been widely used to dimensionality reduction in machine learning. However, the traditional NMF does not properly handle outliers, so that…
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…
Subspace Nonnegative Matrix Factorization for Feature Representation
Junhang Li, Jiao Wei, Can Tong +6
Traditional nonnegative matrix factorization (NMF) learns a new feature representation on the whole data space, which means treating all features equally. However, a subspace is of…
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…
Improving the Level of Autism Discrimination through GraphRNN Link Prediction
Haonan Sun, Qiang He, Shouliang Qi +2
Dataset is the key of deep learning in Autism disease research. However, due to the few quantity and heterogeneity of samples in current dataset, for example ABIDE (Autism Brain Im…
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…
Entropy Regularized Iterative Weighted Shrinkage-Thresholding Algorithm (ERIWSTA): An Application to CT Image Restoration
Bingxue Wu, Jiao Wei, Chen Li +2
The iterative weighted shrinkage-thresholding algorithm (IWSTA) has shown superiority to the classic unweighted iterative shrinkage-thresholding algorithm (ISTA) for solving linear…
An Entropy Weighted Nonnegative Matrix Factorization Algorithm for Feature Representation
Jiao Wei, Can Tong, Bingxue Wu +4
Nonnegative matrix factorization (NMF) has been widely used to learn low-dimensional representations of data. However, NMF pays the same attention to all attributes of a data point…
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…
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…
A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approaches
Chen Li, Xintong Li, Md Rahaman +8
With the development of computer-aided diagnosis (CAD) and image scanning technology, Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis. There…
EMDS-5: Environmental Microorganism Image Dataset Fifth Version for Multiple Image Analysis Tasks
Zihan Li, Chen Li, Yudong Yao +7
Environmental Microorganism Data Set Fifth Version (EMDS-5) is a microscopic image dataset including original Environmental Microorganism (EM) images and two sets of Ground Truth (…
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…
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…
Review of Machine-Learning Methods for RNA Secondary Structure Prediction
Qi Zhao, Zheng Zhao, Xiaoya Fan +3
Secondary structure plays an important role in determining the function of non-coding RNAs. Hence, identifying RNA secondary structures is of great value to research. Computational…