Wenqi Li

Active 2002–2026

252
Papers
22,168
Citations
60
h-index
158
i10-index

Citations

Citations per year for Wenqi Li1884: 1 citations1963: 1 citations1971: 2 citations1976: 1 citations1978: 1 citations1985: 2 citations1989: 2 citations1990: 3 citations1993: 1 citations1996: 1 citations2002: 3 citations2003: 4 citations2005: 1 citations2006: 5 citations2007: 6 citations2008: 1 citations2009: 2 citations2010: 18 citations2011: 19 citations2012: 15 citations2013: 23 citations2014: 32 citations2015: 46 citations2016: 74 citations2017: 81 citations2018: 275 citations2019: 785 citations2020: 1,133 citations2021: 1,505 citations2022: 1,509 citations2023: 1,625 citations2024: 2,092 citations2025: 1,670 citations2026: 405 citations2027: 1 citations1885–1962: no citations, so these years are not shown1964–1970: no citations, so these years are not shown1972–1975: no citations, so these years are not shown1977: no citations, so this year is not shown1979–1984: no citations, so these years are not shown1986–1988: no citations, so these years are not shown1991–1992: no citations, so these years are not shown1994–1995: no citations, so these years are not shown1997–2001: no citations, so these years are not shown2004: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorChina: 3,502 citing papers, 23.5% of this breakdownUnited States: 2,295 citing papers, 15.4% of this breakdownUnited Kingdom: 998 citing papers, 6.7% of this breakdownGermany: 700 citing papers, 4.7% of this breakdownIndia: 667 citing papers, 4.5% of this breakdownCanada: 487 citing papers, 3.3% of this breakdownFrance: 397 citing papers, 2.6% of this breakdownAustralia: 375 citing papers, 2.5% of this breakdownSouth Korea: 364 citing papers, 2.4% of this breakdownItaly: 335 citing papers, 2.2% of this breakdownNetherlands: 294 citing papers, 2% of this breakdownSwitzerland: 286 citing papers, 1.9% of this breakdown
0%23.5%Other 28.3%

Fields

  • Computer Science36.1%
  • Medicine26.7%
  • Biochemistry, Genetics and Molecular Biology10%
  • Engineering8.2%
  • Neuroscience7%
  • Agricultural and Biological Sciences4.6%
  • Other7.4%

Topics

  • Advanced Neural Network Applications6.2%
  • Medical Image Segmentation Techniques4.9%
  • Radiomics and Machine Learning in Medical Imaging4.5%
  • AI in cancer detection4.2%
  • Brain Tumor Detection and Classification3.4%
  • Privacy-Preserving Technologies in Data3.2%
  • Other73.6%

Coauthors

All papers

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  1. The Future of Digital Health with Federated Learning

    Authors: , , , , , , , , , , , , , , , , - npj Digital Medicine, npj Digit. Medicine 2020 cited by 2,532

  2. Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations

    Authors: , , , , - Lecture notes in computer science, DLMIA/ML-CDS@MICCAI 2017 cited by 2,579

  3. MONAI: An open-source framework for deep learning in healthcare

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Yunguan Fu, Benjamin M. Gorman, Hans J. Johnson, Brad Genereaux, Barbaros S. Erdal, Vikas Gupta, Andres Diaz‐Pinto, Andre Dourson, Lena Maier‐Hein, Paul F. Jaeger, Michael Baumgartner, Jayashree Kalpathy-Cramer, Mona G. Flores, Justin Kirby, Lee Cooper, Holger R. Roth, Daguang Xu, David Bericat, Ralf Floca, S. Kevin Zhou, Haris Shuaib, Keyvan Farahani, Klaus Maier‐Hein, Stephen Aylward, Prerna Dogra, Sébastien Ourselin, Andrew Feng - arXiv (Cornell University), CoRR 2022 cited by 591

  4. Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks

    Authors: , , , , , - Neurocomputing 2019 cited by 640

  5. Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning

    Authors: , , , , , , , , , , - IEEE Transactions on Medical Imaging, IEEE Trans. Medical Imaging 2018 cited by 864

  6. DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation

    Authors: , , , , , , , , , , - IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Trans. Pattern Anal. Mach. Intell. 2018 cited by 497

  7. 2017 Robotic Instrument Segmentation Challenge

    Authors: , , , , , , , , , , , , , , , , , , - arXiv (Cornell University), CoRR 2019 cited by 216

  8. Weakly-Supervised Convolutional Neural Networks for Multimodal Image Registration

    Authors: , , , , , , , , , , , , , - Medical Image Analysis, Medical Image Anal. 2018 cited by 461

  9. NVIDIA FLARE: Federated Learning from Simulation to Real-World

    Authors: , , , , , , , , , , , , , , , , , , , , , , - IEEE Data Eng. Bull. 2023 cited by 97

  10. Berberine ameliorates depression-like behaviors in mice via inhibiting NLRP3 inflammasome-mediated neuroinflammation and preventing neuroplasticity disruption

    Authors: , , , , , , , , , - Journal of Neuroinflammation 2023 cited by 145

  11. Automatic Brain Tumor Segmentation Based on Cascaded Convolutional Neural Networks With Uncertainty Estimation

    Authors: , , , - Frontiers in Computational Neuroscience, Frontiers Comput. Neurosci. 2019 cited by 251

  12. An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI

    Authors: , , , , , , , , , , , , , - NeuroImage 2019 cited by 293

  13. Automatic Brain Tumor Segmentation Using Cascaded Anisotropic Convolutional Neural Networks

    Authors: , , , - Lecture notes in computer science, BrainLes@MICCAI 2017 cited by 528

  14. Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis

    Authors: , , , , , , , - IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022 cited by 764

  15. NiftyNet: a deep-learning platform for medical imaging

    Authors: , , , , , , , , , , , , , , , , - Computer Methods and Programs in Biomedicine, Comput. Methods Programs Biomed. 2018 cited by 557

  16. Phosphoantigens glue butyrophilin 3A1 and 2A1 to activate Vγ9Vδ2 T cells

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Eric Oldfield, Rey‐Ting Guo, Yonghui Zhang - Nature 2023 cited by 126

  17. The triangular relationship between traditional Chinese medicines, intestinal flora, and colorectal cancer

    Authors: , , , , , , , , , , , - Medicinal Research Reviews 2023 cited by 93

  18. Automatic Brain Tumor Segmentation Using Convolutional Neural Networks with Test-Time Augmentation

    Authors: , , , - Lecture notes in computer science, BrainLes@MICCAI (2) 2018 cited by 159

  19. Federated Learning for Breast Density Classification: A Real-World Implementation

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer - Lecture notes in computer science, DART/DCL@MICCAI 2020 cited by 124

  20. Whole-genome sequencing of cultivated and wild peppers provides insights into Capsicum domestication and specialization

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Shimin Bi, Xiuwei Yang, Weipeng Li, Huimin Cai, Xirong Luo, Salvador Montes‐Hernández, Marco Antonio Leyva‐González, Zhiqiang Xiong, Xiujing He, Lijun Bai, Shu Tan, Xiangqun Tang, Dan Liu, Jinwen Liu, Shangxing Zhang, Maoshan Chen, Lu Zhang, Li Zhang, Yinchao Zhang, Weiqin Liao, Yan Zhang, Min Wang, Xiaodan Lv, Bo Wen, Hongjun Liu, Hemi Luan, Yonggang Zhang, Shuang Yang, Xiaodian Wang, Jiaohui Xü, Xueqin Li, Shuai Cheng Li, Junyi Wang, Alain Palloix, Paul W. Bosland, Yingrui Li, Anders Krogh, Rafael F. Rivera-Bustamante, Luís Herrera‐Estrella, Ye Yin, Jiping Yu, Kailin Hu, Zhiming Zhang - National Academy of Sciences, Proceedings of the National Academy of Sciences 2014 cited by 819

  21. VISTA3D: Versatile Imaging SegmenTation and Annotation model for 3D Computed Tomography

    Authors: , , , , , , , , , , , , , - IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025 cited by 46

  22. On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task

    Authors: , , , , , - Lecture notes in computer science, IPMI 2017 cited by 348

  23. From Sora What We Can See: A Survey of Text-to-Video Generation

    Authors: , , , , , , , , - arXiv (Cornell University), CoRR 2024 cited by 28

  24. Fine‐tuning the amylose content of rice by precise base editing of the Wx gene

    Authors: , , , , , , , , , , , , , , , - Plant Biotechnology Journal 2020 cited by 161