Sheng Lian (连盛) College of Computer and Data Science, Fuzhou University School of Informatics, Xiamen University (Ph.D.) Schulich School of Medicine and Dentistry, Western University (UWO), Canada (Visiting) Google Scholar | ORCID Email: shenglian [at] fzu.edu.cn  |  lancerlian [at] 163.com I am currently a Lecturer, Master Supervisor, and University-appointed Associate Researcher at the College of Computer and Data Science, Fuzhou University. I was recognized as a Fujian Provincial High-Level Talent. I received my Ph.D. from the Department of Artificial Intelligence, Xiamen University (XMU) under the supervision of Prof. Shaozi Li. I was also a joint Ph.D. student at the Department of Medical Imaging and Medical Biophysics, Western University (UWO), Canada, supervised by Prof. Shuo Li. I received my B.S. degree from Huazhong University of Science and Technology (HUST) in 2014. My research interests include intelligent medical image analysis, computer vision, artificial intelligence, and machine learning.

I am seeking self-motivated Master students (admitted via recommendation or national exam) with strong programming skills and solid mathematical/English background. Research directions include computer vision, medical image analysis, machine learning, remote sensing image analysis, and molecular property prediction.
Office: Room 130, Building No.4, College of Computer and Data Science.
Email: shenglian [at] fzu.edu.cn

(* corresponding author; † equal contribution)
Full list: Google Scholar

DOI	EUTNet: Edge Uncertainty-Aware Consistency and Topology-Constrained Semi-Supervised Medical Image Segmentation Q. Wen, J. He, X. Wei, S. Lian*, et al. Biomedical Signal Processing and Control (BSPC), 2026 (SCI-1区, IF:5.1)
PDF	CoDiff: Towards Reliable Pseudo-Labels via Collaborative Difference Learning for Semi-Supervised Medical Image Segmentation X. Wei, S. Lian*, W. Chen, H. Zhong, J. Chen, H. Xu IEEE International Conference on Multimedia & Expo (ICME), 2026 (CCF-B)
PDF	PromptFix: Anatomy-Aware Text Prompting for Semi-Supervised Lumbar MRI Segmentation H. Xu, S. Lian*, Y. Wang, J. Chen, J. Liu, L. Li IEEE International Conference on Multimedia & Expo (ICME), 2026 (CCF-B)
DOI	Advancing Fine-Grained Spine Segmentation through Visual-Language Model with Omni- and Pixel-Level Semantic Enhancements J. Cai, S. Lian*, et al. PRCV, 2025
DOI	Fine-grained epicardial adipose tissue segmentation in cardiac CT images with position priors and edge enhancement S. Lian*, Q. Yuan, Q. Su, et al. Biomedical Engineering Letters, 2025 (SCI-3区)
DOI	AD-Det: Boosting Object Detection in UAV Images with Focused Small Objects and Balanced Tail Classes Z. Li, S. Lian*, D. Pan, Y. Wang, W. Liu Remote Sensing, 2025 (SCI-1区, IF:4.2)
DOI	Enhancing semi-supervised medical image segmentation with boundary awareness and Competitive Contrastive Learning Z. Lin, Z. Li, J. Su, L. Li, S. Lian* Biomedical Signal Processing and Control (BSPC), 2025 (SCI-1区)
DOI	Age at onset mediates genetic impact on disease severity in facioscapulohumeral muscular dystrophy F. Zheng, Y. Lin, L. Qiu, ..., S. Lian*, Z. Wang* Brain, 2024 (SCI-1区Top, IF:14.5)
DOI	Towards accurate abdominal tumor segmentation: A 2D model with Position-Aware and Key Slice Feature Sharing J. He, Z. Luo, S. Lian, S. Su, S. Li Computers in Biology and Medicine, 2024 (SCI-1区)
DOI	Cutting-Edge Machine Learning in Biomedical Image Analysis: Editorial S. Lian*, Z. Luo Bioengineering, 2024 (SCI-2区)
DOI	VCLlPSeg: Voxel-wise CLIP-Enhanced model for Semi-Supervised Medical Image Segmentation L. Li, S. Lian, Z. Luo, B. Wang, S. Li MICCAI, 2024 (CCF-B, 领域顶会)
DOI	Reconstruct Incomplete Relation for Incomplete Modality Brain Tumor Segmentation J. Su, Z. Luo, C. Wang, S. Lian, X. Lin, S. Li Neural Networks, 2024 (SCI-1区Top, IF:6.0)
DOI	Contour-aware consistency for semi-supervised medical image segmentation L. Li, S. Lian, Z. Luo, B. Wang, S. Li Biomedical Signal Processing and Control (BSPC), 2024 (SCI-1区)
DOI	Mutual learning with reliable pseudo label for semi-supervised medical image segmentation J. Su, Z. Luo, S. Lian, D. Lin, S. Li Medical Image Analysis (MedIA), 2024 (SCI-1区Top, IF:11.1)
DOI	Consistency learning with dynamic weighting and class-agnostic regularization for semi-supervised medical image segmentation J. Su, Z. Luo, S. Lian, D. Lin, S. Li Biomedical Signal Processing and Control (BSPC), 2024 (SCI-1区)
DOI	Automatic Epicardial Adipose Tissue Segmentation in Cardiac CT with Position Regularization Q. Yuan, Q. Su, Z. Li, Q. Wen, Z. Lin, D. Chai, S. Lian* ICIC, 2024 (CCF-C)
DOI	Learning multi-organ segmentation via partial- and mutual-prior from single-organ datasets S. Lian*, L. Li*, Z. Luo, Z. Zhong, B. Wang, S. Li Biomedical Signal Processing and Control (BSPC), 2023 (SCI-1区)
PDF	Symmetrical supervision with transformer for few-shot medical image segmentation Y. Niu, Z. Luo, S. Lian, L. Li, S. Li, H. Song IEEE BIBM, 2022 (CCF-B)
DOI	APRIL: Anatomical Prior-guided ReInforcement Learning for Accurate Carotid Lumen Diameter and Intima-media Thickness Measurement S. Lian, Z. Luo, C. Feng, S. Li, S. Li Medical Image Analysis (MedIA), 2021 (SCI-1区Top)
DOI	A global and local enhanced residual u-net for accurate retinal vessel segmentation S. Lian, L. Li, G. Lian, X. Xiao, Z. Luo, S. Li IEEE/ACM TCBB, 2021 (SCI-1区, CCF-B)
DOI	Learning Consistency- and Discrepancy-Context for 2D Organ Segmentation L. Li†, S. Lian†, Z. Luo, B. Wang, S. Li, S. Li MICCAI, 2021 (Early accept, CCF-B, 领域顶会)
DOI	Leveraging virtual and real person for unsupervised person re-identification F. Yang, Z. Zhong, Z. Luo, S. Lian, S. Li IEEE Transactions on Multimedia (TMM), 2019 (SCI-1区Top, CCF-A)
DOI	Attention guided U-Net for accurate iris segmentation S. Lian, Z. Luo, Z. Zhong, X. Lin, S. Su, S. Li Journal of Visual Communication and Image Representation (JVCIR), 2018 (SCI-2区, CCF-C)

• National Natural Science Foundation of China (NSFC) Youth Program, “Semi-supervised epicardial adipose tissue segmentation with dual text prompts and uncertainty awareness”, 2026-2028, Principal Investigator (PI).
• Fujian Provincial Natural Science Foundation (Youth Program), “Prior-guided 2.5D fine-grained segmentation of epicardial adipose tissue”, 2023-2026, PI.
• Fujian Provincial Education Research Project, “Efficient epicardial fat segmentation with inter-frame correlation”, 2023-2024, PI.
• National Natural Science Foundation of China, “Deep learning for person re-identification in big data scenarios”, 2019-2022, Participant.
• National Natural Science Foundation of China (Youth Program), “Vehicle detection and fine-grained classification in complex traffic surveillance”, 2019-2021, Participant.
• Ministry of Education – Cloud & Data Integration Fund, “Intelligent diagnosis system for infectious ocular surface diseases”, 2017-2019, Participant.

Awards: Supervised graduate students (Yuan, Li, Lin, etc.) have received university academic scholarships.
Placements (selected): Lin (China Electronics Technology Group), Yuan (CMB招银), Li (DiDi Global), Pan (China CITIC Bank).

• Committee Member, Medical Image Computing Young Scholars (MICS)
• Member, CCF Technical Committee on Computer Vision / Digital Medicine
• Guest Editor, Bioengineering (Special Issue on “Recent Advance of Machine Learning in Biomedical Image Analysis”)
• Technical Committee (TC), MILLAND Workshop (MICCAI 2023)
• Youth Editorial Board Member, Meta-Radiology
• Program Committee, BIBM 2025 (CCF-B)
• Invited Reviewer: IEEE TNNLS, MedIA, IEEE TMI, Knowledge-Based Systems, Pattern Recognition, MICCAI, IEEE TGRS, IEEE TCSVT, IEEE CIM, Neurocomputing, JVCIR, Scientific Reports, ICME, ICPR, IJCNN, etc.

Machine Learning (Course Materials) – Undergraduate course, Fuzhou University.
Honors: “Yangteng Award for Excellent Teaching”, Second Prize in “Best Lecture” competition.

• CS Journal/Conference Ranking (CCF)
• Recent arXiv papers on Computer Vision
• Linggle – Language Reference Search Engine
• Science Topics by ScienceDirect
• Recent MedIA Articles
• Recent IEEE TMI Articles
• Dive into Deep Learning
• Tips for Writing Technical Papers
• Pattern Recognition and Machine Learning (Bishop)
• A Course in Machine Learning
• ReadPaper & “Ten Questions” for Papers

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