岳广辉，男，副教授，特聘研究员，硕士生导师、博士生导师、博士后合作导师。2019年6月在天津大学获博士学位，2017-2019年于新加坡南洋理工大学计算机科学与工程学院Lin Weisi教授（IEEE/IET Fellow）课题组从事研究工作。2019年7月进入深圳大学从事教学科研工作。岳博士主要开展医学图像分析、计算机辅助诊断、图像/视频质量评价及优化、机器学习及其应用等领域的研究。截止目前，发表期刊/会议论文70余篇（含第一/通讯SCI论文40余篇），申请并授权国家发明专利20余项，部分成果获天津市科学技术进步奖一等奖。主持国家自然科学基金面上项目、青年项目、广东省基础与应用基础基金面上项目、深圳市优秀科技创新人才培养项目、深圳市医学研究专项资金（人才提升型项目）等纵向课题10余项。担任中国生物医学工程学会数字医疗及医疗信息化分会委员、中国自动化学会青年工作委员、广东省医学会人工智能分会学术委员、医学图像计算青年研讨会委员。担任多媒体信号处理会议（2023 IEEE MMSP）领域主席、国际图像处理会议（2024 IEEE ICIP）领域主席、中国控制会议（2024 CCC）领域主席。担任IEEE TIP/TMI/TMM/TCSVT/TNNLS/TII/TIE/TIM/J.BHI/TASE/ TNSRE、Elsevier SP/DSP/JVCI、IET IP/EL等二十余个期刊的审稿人。主授课程为《机器学习与Python》、《高等数学（医）》、《人工智能的临床应用实践》及《医学图像处理与应用》，教学评测平均值在全校前20%。

图像/视频质量评价及优化

医学图像分割

医学图像分类

1.国家自然科学基金面上项目，2024/01-2027/12，主持

2.广东省自然科学基金青年提升项目，2024/01-2026/12，主持

3.深圳市医学研究专项资金（人才提升型-青年项目），2025/01-2027/12，主持

课题组聚焦于计算机辅助诊断、医学信息处理等前沿领域，以图像处理、深度学习技术为手段解决相关科学难题，实验室软硬件齐全，拥有多台高性能深度学习图形工作站及服务器，可满足深度学习相关的研究工作。课题组与国外多个名校的科研团队以及国内知名企业、医院构建了长期合作关系，全力支持学生开展研究工作，可推荐成果优秀、性格良好者交流学习。本人会积极与学生互动、给予一线科研指导，课题组氛围融洽，成员来自五湖四海，精诚协作、积极向上，已经连续三年获得研究生国家奖学金，部分硕士生毕业后入职华为、科大讯飞等企业从事研发工作、本科生前往中山大学继续深造。本课题组长期招募博士后、研究生（含博士生、硕士生）、本科生，重点招收拥有学术追求、计划从事算法研发和科研岗的学生(有继续读博深造计划的优先考虑)，期待热爱人工智能及医学图像处理方向（最好掌握基本的编程、图像处理和机器学习知识），努力踏实勤奋的你加入实验室。感兴趣者请把简历发送至yueguanghui@szu.edu.cn。

1.图像/视频质量评价及优化

[1]Guanghui Yue,Lixin Zhang, et al., Subjective and Objective Quality Assessment of Colonoscopy Videos,IEEE Transactions on Medical Imaging, 2025, 44(2): 841-854.(Top期刊,中科院1区)

[2]Guanghui Yue, Shaoping Zhang, et al., Pyramid Network with Quality-Aware Contrastive Loss for Retinal Image Quality Assessment,IEEE Transactions on Medical Imaging, 2025, 44(3): 1416-1431.(Top期刊,中科院1区)

[3]Guanghui Yue, Chunping Hou, et al., Combining local and global measures for DIBR-synthesized image quality evaluation,IEEE Transactions on Image Processing, 2019, 28(4): 2075-2088.(Top期刊,中科院1区)

[4]Guanghui Yue, Jie Gao, et al., Deep Pyramid Network for Low-Light Endoscopic Image Enhancement,IEEE Transactions on Circuits and Systems for Video Technology, 2024, 34 (5): 3834 - 3845.(Top期刊,中科院1区)

[5]Guanghui Yue, Di Cheng, et al., Semi-Supervised Authentically Distorted Image Quality Assessment with Consistency-Preserving Dual-Branch Convolutional Neural Network,IEEE Transactions on Multimedia, 2023, 25: 6499 - 6511.(Top期刊,中科院1区)

[6]Guanghui Yue, Di Cheng, et al., Perceptual Quality Assessment of Enhanced Colonoscopy Images: A Benchmark Dataset and an Objective Method,IEEE Transactions on Circuits and Systems for Video Technology, 2023, 33(10): 5549 - 5561.(Top期刊,中科院1区)

[7]Yu Luo, Bijia You,Guanghui Yue*, and Jie Ling, Pseudo-supervised Low-light Image Enhancement with Mutual Learning,IEEE Transactions on Circuits and Systems for Video Technology, 2024, 34(1):85-96.(通讯，Top期刊,中科院1区)

[8]Yu Luo, Xuanrong Chen, Jie Ling, Chao Huang, Wei Zhou, andGuanghui Yue*,Unsupervised Low-Light Image Enhancement with Self-Paced Learning,IEEE Transactions on Multimedia, 2025, 27:1808-1820.(Top期刊,中科院1区)

2.医学图像分割

[1]Guanghui Yue, Shangjie Wu, et al., Boundary-Guided Feature-Aligned Network for Colorectal Polyp Segmentation,IEEE Transactions on Circuits and Systems for Video Technology, 2025, accepted, in press, DOI: 10.1109/TCSVT.2025.3542969.(Top期刊,中科院1区)

[2]Guanghui Yue, Shangjie Wu, et al., Progressive Region-to-Boundary Exploration Network for Camouflaged Object Detection,IEEE Transactions on Multimedia, 2025, 27: 236 - 248.(Top期刊,中科院1区)

[3]Guanghui Yue, Houlu Xiao, et al., Dual-Constraint Coarse-to-Fine Network for Camouflaged Object Detection,IEEE Transactions on Circuits and Systems for Video Technology, 2024, 34 (5): 3286 - 3298.(Top期刊,中科院1区)

[4]Guanghui Yue, Guibin Zhuo, et al., Boundary Uncertainty Aware Network for Automated Polyp Segmentation,Neural Networks, 2024, 170: 390-404.(Top期刊,中科院1区)

[5]Guanghui Yue,Shangjie Wu,et al., Adaptive Context Aggregation Network with Prediction-aware Decoding for Multimodal Brain Tumor Segmentation,IEEE Transactions on Instrumentation and Measurement, 2024, 73: 1-11.(Top期刊,中科院2区)

[6]Guanghui Yue,Siying Li,et al., Attention-Guided Pyramid Context Network for Polyp Segmentation in Colonoscopy Images,IEEE Transactions on Instrumentation and Measurement, 2023, 72: 1-13.(Top期刊,中科院2区)

[7]Guanghui Yue, Guibin Zhuo, et al., Adaptive Cross-Feature Fusion Network with Inconsistency Guidance for Multi-Modal Brain Tumor Segmentation,IEEE Journal of Biomedical and Health Informatics, 2023, accepted, in press, DOI: 10.1109/J.BHI.2023.3347556.(Top期刊,中科院2区)

[8]Guanghui Yue, Wanwan Han, et al.,Boundary Constraint Network with Cross Layer Feature Integration for Polyp Segmentation,IEEE Journal of Biomedical and Health Informatics, 2022, 26(8): 4090 - 4099.(Top期刊,中科院1区)

3.医学图像分类

[1]Guanghui Yue,Peishan Wei, et al., Toward Multicenter Skin Lesion Classification Using Deep Neural Network with Adaptively Weighted Balance Loss,IEEE Transactions on Medical Imaging, 2023, 42(1): 119-131.(Top期刊,中科院1区)

[2]Guanghui Yue,Peishan Wei,et al., Automated Endoscopic Image Classification via Deep Neural Networkwith Class Imbalance Loss,IEEE Transactions on Instrumentation and Measurement, 2023, 72: 1-11.(Top期刊,中科院2区)

[3]Guanghui Yue,Yuan Li, et al.,Attention-Driven Cascaded Network for Diabetic Retinopathy Grading from Fundus Images,Biomedical Signal Processing and Control, 2023, 80: 104370.(中科院2区)

[4]Guanghui Yue^#,Peishan Wei^#, et al., Specificity-aware Federated Learning with Dynamic Feature Fusion Network for Imbalanced Medical Image Classification,IEEE Journal of Biomedical and Health Informatics, 2024, 28(11): 6373 - 6383.(^#共同一作，Top期刊,中科院2区)

[5]Peishan Wei, Tianwei Zhou, Weide Liu, Jie Du, Tianfu Wang, andGuanghui Yue(岳广辉)*, FedPDN: Personalized Federated Learning with Inter-class Similarity Constraint for Medical Image Classification through Parameter Decoupling,IEEE Transactions on Instrumentation and Measurement, 2025,74: 1-13.(通讯，Top期刊,中科院2区)

[6]Bin Jiang,Yuchen Shang,Guanghui Yue(岳广辉)*,et al.,Long-Tailed Federated Learning in Internet of Medical Things Based on Ensemble Distillation and Imbalanced Calibration,IEEE Transactions on Consumer Electronics, 2025, accepted, in press, DOI: 10.1109/TCE.2025.3537062.(通讯，中科院2区)