Meng Wei 个人学术档案 - 学术资源搜索

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Yalin ZhengUniversity of Liverpool在 liv.ac.uk 的电子邮件经过验证
Fabien ScalzoAssociate Professor, Computer Science/Neurology, University of California Los Angeles (UCLA)在 cs.ucla.edu 的电子邮件经过验证
Kunakorn Atchaneeyasakul, MD MPHDepartment of Neurology, University of California Los Angeles在 mednet.ucla.edu 的电子邮件经过验证
David S LiebeskindProfessor of Neurology在 mednet.ucla.edu 的电子邮件经过验证
Tom VercauterenProfessor of Interventional Image Computing, King's College London在 kcl.ac.uk 的电子邮件经过验证
Miaojing ShiProfessor at Tongji University, Visiting Senior Lecturer at King's College London在 kcl.ac.uk 的电子邮件经过验证
Zhenghang ZhongMaster student, RWTH Aachen University在 rwth-aachen.de 的电子邮件经过验证

Meng Wei

在 imperial.ac.uk 的电子邮件经过验证


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Deep Learning for Hemorrhagic Lesion Detection and Segmentation on Brain CT Images M Wei, L Li, B Liu, K Atchaneeyasakul, F Zhou, Z Pan, S Kumar, J Zhang, ... IEEE Journal of Biomedical and Health Informatics, 2020	113	2020
CNN-GCN aggregation enabled boundary regression for biomedical image segmentation Y Meng, M Wei, D Gao, Y Zhao, X Yang, X Huang, Y Zheng Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020	59	2020
Regression of Instance Boundary by Aggregated CNN and GCN Y Meng, M Wei, D Gao, Y Zhao, X Yang, X Huang, Y Zheng European Conference on Computer Vision, 190-207, 2020	31	2020
Text promptable surgical instrument segmentation with vision-language models Z Zhou, O Alabi, M Wei, T Vercauteren, M Shi Advances in Neural Information Processing Systems 36, 28611-28623, 2023	13	2023
SegMatch: A semi-supervised learning method for surgical instrument segmentation M Wei, C Budd, LC Garcia-Peraza-Herrera, R Dorent, M Shi, ... arXiv preprint arXiv:2308.05232, 2023	4	2023
Enhancing surgical instrument segmentation: integrating vision transformer insights with adapter M Wei, M Shi, T Vercauteren International Journal of Computer Assisted Radiology and Surgery, 1-8, 2024		2024
Large Model driven Radiology Report Generation with Clinical Quality Reinforcement Learning Z Zhou, M Shi, M Wei, O Alabi, Z Yue, T Vercauteren arXiv preprint arXiv:2403.06728, 2024		2024

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