Lequan Yu

16.5k total citations · 10 hit papers
107 papers, 7.0k citations indexed

About

Lequan Yu is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Lequan Yu has authored 107 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Computer Vision and Pattern Recognition, 47 papers in Radiology, Nuclear Medicine and Imaging and 42 papers in Artificial Intelligence. Recurrent topics in Lequan Yu's work include Radiomics and Machine Learning in Medical Imaging (27 papers), Medical Image Segmentation Techniques (24 papers) and Advanced Neural Network Applications (24 papers). Lequan Yu is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (27 papers), Medical Image Segmentation Techniques (24 papers) and Advanced Neural Network Applications (24 papers). Lequan Yu collaborates with scholars based in Hong Kong, China and United States. Lequan Yu's co-authors include Pheng‐Ann Heng, Hao Chen, Jing Qin, Qi Dou, Chi‐Wing Fu, Xin Yang, Xiaomeng Li, Xiaojuan Qi, Lei Xing and Shujun Wang and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Lequan Yu

95 papers receiving 6.8k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks

2016 775 citations Lequan Yu, Hao Chen et al. IEEE Transactions on Medical Imaging profile →
VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images

2017 506 citations Hao Chen, Lequan Yu et al. profile →
Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks

2016 471 citations Hao Chen, Lequan Yu et al. IEEE Transactions on Medical Imaging profile →
Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection

2016 423 citations Hao Chen, Lequan Yu et al. IEEE Transactions on Biomedical Engineering profile →
3D deeply supervised network for automated segmentation of volumetric medical images

2017 418 citations Lequan Yu, Hao Chen et al. Medical Image Analysis profile →
DCAN: Deep contour-aware networks for object instance segmentation from histology images

2016 351 citations Hao Chen, Lequan Yu et al. Medical Image Analysis profile →
Transformation-Consistent Self-Ensembling Model for Semisupervised Medical Image Segmentation

2020 343 citations Xiaomeng Li, Lequan Yu et al. IEEE Transactions on Neural Networks and Learning Systems profile →
DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation

2016 328 citations Hao Chen, Lequan Yu et al. profile →
CANet: Cross-Disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading

2019 295 citations Xiaomeng Li, Xiaowei Hu et al. IEEE Transactions on Medical Imaging profile →
nnFormer: Volumetric Medical Image Segmentation via a 3D Transformer

2023 287 citations Hong-Yu Zhou, Jiansen Guo et al. IEEE Transactions on Image Processing profile →

Peers

Countries citing papers authored by Lequan Yu

Since Specialization

Citations

This map shows the geographic impact of Lequan Yu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lequan Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lequan Yu more than expected).

Fields of papers citing papers by Lequan Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lequan Yu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lequan Yu. The network helps show where Lequan Yu may publish in the future.

Co-authorship network of co-authors of Lequan Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Lequan Yu. A scholar is included among the top collaborators of Lequan Yu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lequan Yu. Lequan Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Personalizing Federated Instrument Segmentation With Visual Trait Priors in Robotic Surgery 2025 ·IEEE Transactions on Biomedical Engineering ·Jialang Xu, (unknown), Lequan Yu, Danail Stoyanov, Yueming Jin, Evangelos B. Mazomenos	1
2	TAD-Graph: Enhancing Whole Slide Image Analysis via Task-Aware Subgraph Disentanglement 2025 ·IEEE Transactions on Medical Imaging ·(unknown), (unknown), (unknown), Yuming Jiang, (unknown), Liansheng Wang, Lequan Yu	1
3	Potential Anti-Inflammatory Constituents from Aesculus wilsonii Seeds 2024 ·Molecules ·Ping Zhang, Lequan Yu, (unknown), Jingya Ruan, Fei Li, Lijie Wu, Yi Zhang, Tao Wang	3
4	A Novel Platform Featuring Nanomagnetic Ligand Fishing Based on Fixed-Orientation Immobilized Magnetic Beads for Screening Potential Cyclooxygenase-2 Inhibitors from Panax notoginseng Leaves 2024 ·Molecules ·Fan Zhang, Fan Sun, Lequan Yu, Fei Li, Lixia Liu, Xiaoyan Cao, Yi Zhang, Lijie Wu	1
5	Multi-task heterogeneous graph learning on electronic health records 2024 ·Neural Networks ·(unknown), Guosheng Yin, Kyongtae T. Bae, Lequan Yu	2
6	Modality-Aware Distillation Network for Microvascular Invasion Prediction of Hepatocellar Carcinoma From MRI Images 2024 ·IEEE Transactions on Biomedical Engineering ·Yinghao Zhang, Zhihong Liu, Lei Zhu, Huanhuan Chong, Huazhu Fu, Lequan Yu, Ping Li, Jing Qin, Dagan Feng, Liansheng Wang	0
7	FMMAS-OCT: Aberration correction for high-resolution cellular imaging 2023 ·Optics and Lasers in Engineering ·Xin Ge, Jin He, Si Chen, Guangming Ni, (unknown), (unknown), Lequan Yu, Linbo Liu, En Bo	1
8	RECIST-Induced Reliable Learning: Geometry-Driven Label Propagation for Universal Lesion Segmentation 2023 ·IEEE Transactions on Medical Imaging ·(unknown), Lequan Yu, Liansheng Wang	6
9	nnFormer: Volumetric Medical Image Segmentation via a 3D Transformer breakdown → 2023 ·IEEE Transactions on Image Processing ·Hong-Yu Zhou, Jiansen Guo, Yinghao Zhang, Xiaoguang Han, Lequan Yu, Liansheng Wang, Yizhou Yu	287
10	Shared-Specific Feature Learning With Bottleneck Fusion Transformer for Multi-Modal Whole Slide Image Analysis 2023 ·IEEE Transactions on Medical Imaging ·(unknown), Lequan Yu, Xin Ding, Xuehong Liao, Liansheng Wang	10
11	Leveraging data-driven self-consistency for high-fidelity gene expression recovery 2022 ·Nature Communications ·Md Tauhidul Islam, Jen‐Yeu Wang, (unknown), Xiaomeng Li, (unknown), Shengtian Sang, Lequan Yu, Liyue Shen, Wei Zhao, Lei Xing	8
12	Lymph Node Metastasis Prediction From Whole Slide Images With Transformer-Guided Multiinstance Learning and Knowledge Transfer 2022 ·IEEE Transactions on Medical Imaging ·(unknown), Lequan Yu, Xin Ding, Xuehong Liao, Liansheng Wang	38
13	All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-Supervised Medical Image Segmentation 2022 ·IEEE Journal of Biomedical and Health Informatics ·Zhe Xu, Yixin Wang, Donghuan Lu, Lequan Yu, Jiangpeng Yan, Jie Luo, Kai Ma, Yefeng Zheng, Raymond Kai‐Yu Tong	58
14	MuRCL: Multi-Instance Reinforcement Contrastive Learning for Whole Slide Image Classification 2022 ·IEEE Transactions on Medical Imaging ·(unknown), Lequan Yu, (unknown), Rongshan Yu, Defu Zhang, Liansheng Wang	30
15	Combining Monte Carlo with Deep Learning: Predicting High-resolution, Low-noise Dose Distributions Using a Generative Adversarial Network for Fast and Precise Monte Carlo Simulations 2020 ·International Journal of Radiation OncologyBiologyPhysics ·Varun Vasudevan, Charles Huang, Eric Simiele, Lequan Yu, Lei Xing, Emil Schüler	2
16	Unsupervised Detection of Distinctive Regions on 3D Shapes 2020 ·ACM Transactions on Graphics ·Xianzhi Li, Lequan Yu, Chi‐Wing Fu, Daniel Cohen‐Or, Pheng‐Ann Heng	16
17	Transformation-Consistent Self-Ensembling Model for Semisupervised Medical Image Segmentation breakdown → 2020 ·IEEE Transactions on Neural Networks and Learning Systems ·Xiaomeng Li, Lequan Yu, Hao Chen, Chi‐Wing Fu, Lei Xing, Pheng‐Ann Heng	343
18	Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation 2020 ·Medical Image Analysis ·Yingda Xia, Dong Yang, Zhiding Yu, Fengze Liu, Jinzheng Cai, Lequan Yu, Zhuotun Zhu, Daguang Xu, Alan Yuille, Holger R. Roth	163
19	Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation 2019 ·IEEE Transactions on Medical Imaging ·Shujun Wang, Lequan Yu, Xin Yang, Chi‐Wing Fu, Pheng‐Ann Heng	199
20	CANet: Cross-Disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading breakdown → 2019 ·IEEE Transactions on Medical Imaging ·Xiaomeng Li, Xiaowei Hu, Lequan Yu, Lei Zhu, Chi‐Wing Fu, Pheng‐Ann Heng	295

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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