Publications
J: journal | C: (peer-reviewed) conference | B: (edited) book | BC: book chapter | CA: conference abstract / P: Preprint
Papers with ERA2010 rating A*/A are highlighted by the index in bold.
2025
J94. Z. Wang, L. Wang, X. Li, and L. Zhou*, "Diagnostic Captioning by Cooperative Task Interactions and Sample-graph Consistency", IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), 2025
J93. X. Yang, G. Lin, Z. Chen, and L. Zhou*, "Neural Vector Fields: Generalizing Distance Vector Fields by Codebooks and Zero-Curl Regularization", IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), 2025
J92. ZL. Chen, Y. Li, Z. Wang, P. Gao, J. Barthelemy, L. Zhou, and L. Wang, "Enhancing Radiology Report Generation via Multi-Phased Supervision", IEEE Transactions on Medical Imaging (IEEE-TMI), 2025 (accepted)
J91. L. Yang, Z. Chen*, K. Wang, and L. Zhou*, "Improving CXR Bone Suppression by Exploiting Domain-level and Instance-level Information", IEEE Transactions on Medical Imaging (IEEE-TMI), 2025 (* co-corresponding authors)
J90. E. Guo, Z.C. Wang, Z. Zhao, and L. Zhou*, "Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels", IEEE Transactions on Medical Imaging (IEEE-TMI), 2025
J89. Y. Li, Y. Liu, Z. Wang, X. Liang, L. Liu, L. Wang, and L. Zhou, "S-RRG-Bench: Structured Radiology Report Generation with Fine-Grained Evaluation Framework ", Meta-Radiology, 2025
J88. S. Li, J. Zhang, L. Qi, L. Zhou, Y. Shi, and Y. Gao, "Diversity-enhanced Collaborative Mamba for Semi-supervised Medical Image Segmentation", IEEE Transactions on Medical Imaging (IEEE-TMI), 2025
J87. Z. Cheng, J. Guo, J. Zhang, L. Qi, L. Zhou, Y. Shi, and Y. Gao, "Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation", IEEE Transactions on Medical Imaging (IEEE-TMI), 2025 (IEEE-TMI X/Twitter recommendation)
J86. Y. Yang, W. Xi, L. Zhou, and J. Tang, "Rebalanced Vision-Language Retrieval Considering Structure-Aware Distillation", IEEE Transactions on Image Processing (IEEE-TIP), 2025 (accepted on December 2024）
J85. P. Zeng, X. Zeng, Y. Wang, L. Zhou, C. Zu, X. Wu, J. Zhou, and D. Shen, "Multi-modal Long-Short Distance Attention-based Transformer-GAN for PET Reconstruction with Auxiliary MRI", IEEE Transactions on Circuits and Systems for Video Technology (IEEE-TSCVT), 2025 (accepted)
J84. X. Tian, J. Sved, Y. Chen; L. Li, L. Zhou, L. Nguyen, R. Minasian, and X. Yi, "Deep Learning-Enhanced Microwave Photonic Sensing with Inverse-Design Assisted Fabry-Pérot Cavity", IEEE/OPTICA PUBLISHING GROUP Journal of Lightwave Technology (JLT), 2025
C101. X. Yue, Z. Wang, Y. Wang, W. Zhang, X. Liu, W. Ouyang, L. Bai, and L. Zhou, "Understand Before You Generate: Self-Guided Training for Autoregressive Image Generation", Conference on Neural Information Processing Systems (NeurIPS), 2025
C100. Z. Sun*, S. Piao*, H. Jin, C. Dong, L. Yue, W. Chen, and L. Zhou, "AWF: Adaptive Weight Fusion for Enhanced Class Incremental Semantic Segmentation", IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2025
C99. T. Han, W. Xu, J. Gong, X. Yue, S. Guo, L. Zhou, and L. Bai, "InfGen: A Resolution-Agnostic Paradigm for Scalable Image Synthesis", International Conference on Computer Vision (ICCV), Hawai'i, 2025
C98. T. Chen, S. Yang, J. Wang, L. Bai, H. Ren, and L. Zhou*, "SurgSora: Object-Aware Diffusion Model for Controllable Surgical Video Generation", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Korea, 2025
C97. Q. Lyu, Y. Wang, T. Chen, E. Guo, and L. Zhou*, "WiD-PET: PET Image Reconstruction from Low-Dose Data Using a Wavelet-Informed Diffusion Model with Fast Inference", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Korea, 2025
C96. J. Cui, L. Wen, Y. Fei, B. Liu, L. Zhou, D. Shen, and Y. Wang, "HiLa: Hierarchical Vision-Language Collaboration for Cancer Survival Prediction", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Korea, 2025
C95. X. Zeng, P. Zeng, Y. Wang, J. Cui, L. Zhou, C. Jiang, H. Zhang, and D. Shen, "MAK-GAN: Multi-level Adaptive Convolutional Kernels for Asymmetric Multi-modal PET Reconstruction", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Korea, 2025
C94. D. Chao, Y. Zhang, L. Zhou, and Y. Yang, "Enriching Category Representations with LLMs Towards Robust Zero-Shot OOD Detection", European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2025 (accepted)
C93. E. Guo, Z. Zhao, ZC. Wang, T. Chen, Y. Liu, and L. Zhou*, "DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labels", The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
C92. ZL. Chen, P. Gao, Y. Lee, J. Barthelemy, L. Zhou, and L. Wang, "Optimizing Efficiency and Visual-Textual Alignment for LLM-Based Radiology Report Generation", IEEE International Conference on Multimedia and Expo (ICME), 2025
C91. L. Yang, Z. Wang*, and L. Zhou*, "MedVisioChat: a Multimodal Large Language Model Framework for Interpretable Diagnosis With Visual Grounding in CXRs", IEEE International Symposium on Biomedical Imaging (ISBI), Houston, USA, 2025 (* co-corresponding authors)
C90. L. Yang, Z. Wang*, Z. Chen, X. Liang, and L. Zhou*, "MedXChat: a Unified Multimodal Large Language Model Framework Towards CXRs Understanding and Generation", IEEE International Symposium on Biomedical Imaging (ISBI), Houston, USA, 2025 (* co-corresponding authors, oral presentation)
C89. W. Xu, V. Ila, L. Zhou, and C.T. Jin, "TB-HSU: Hierarchical 3D Scene Understanding with Contextual Affordances", Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI), Philadelphia, USA, 2025
2024
J83. X. Liang, Y. Guod, H. Zhang, X. Wang, D. Li., Y. Liu, J. Zhang, L. Zhou, and S. Qiu, "Neuroimaging Signatures and a Deep Learning Modeling for Early Diagnosing and Predicting Non-Pharmacological Therapy Success for Subclinical Depression Comorbid Sleep Disorders in College Students", International Journal of Clinical and Health Psychology, 2024 (accepted in Nov 2024)
J82. J. Zhang, X. Wu, X. Tang, L. Zhou, L. Wang, W. Wu and D. Shen, "Asynchronous Functional Brain Network Construction with Spatiotemporal Transformer for MCI Classification", IEEE Transactions on Medical Imaging (IEEE-TMI), 2024
J81. Y. Xu, L. Wen, Z. Jiao, J. Xiao, L. Zhou, Y. Luo, J. Zhou, X. Peng, and Y. Wang, "DSANet: Dual-path Segmentation-guided Attention Network for Radiotherapy Dose Prediction from CT images Only", Knowledge-based System, 2024
J80. Y. Liu*, Y. Li *, Z. Wang*, X. Liang, L. Wang, L. Liu, L. Cui, Z. Tu, L. Wang, and L. Zhou, "A Comprehensive Study of GPT-4v’s Multimodal Capabilities in Medical Imaging", Meta-Radiology: arXiv, 2024
J79. L. Papa, P. Russo, I. Amerini, and L. Zhou*, "A Survey on Efficient Vision Transformers: Algorithms, Techniques, and Performance Benchmarking”, IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), 2024
J78. F. E Enriquez-Mier-y-Teran, L. Zhou, S. R. Meikle, and A. Z. Kyme, "A Deep Neural Network for Positioning and Inter-crystal Scatter Identification in Multiplexed PET Detectors", Physics in Medicine and Biology, 2024
J77. L. Hu, Y. Yang, C. Zu, J. Zhang, Z. Jiao, X. Wu, J. Zhou, L. Zhou, and Y. Wang, "CL-TransFER: Collaborative Learning based Transformer for Facial Expression Recognition with Masked Reconstruction Pattern Recognition", Pattern Recognition (PR), 2024
J76. L. Wen, Y. Xu, Z. Feng, J. Zhou, L. Zhou, and Y. Wang, "Semi-supervised Domain Adaptation for Semantic Segmentation via Active Learning with Feature-and Semantic-Level Alignments", IEEE Transactions on Intelligent Vehicles (IEEE-TIV), 2024
J75. J. Cui, Y. Wang, L. Zhou, Y. Fei, J. Zhou, and D. Shen, "3D Point-based Multi-Modal Context Clusters GAN for Low-Dose PET Image Denoising", IEEE Transactions on Circuits and Systems for Video Technology (IEEE-TCSVT), 2024
J74. J. Zhang, Y. Guo, L. Zhou, L. Wang, W. Wu, and D. Shen, "Constructing Hierarchical Attentive Functional Brain Networks for Early AD Diagnosis", Medical Image Analysis (MedIA), 2024
J73. Z. Wang, L. Liu, L. Wang, and L. Zhou*, "R2GenGPT: Radiology Report Generation with Frozen LLMs", Meta-Radiology, Special Issue "LLM/ChatGPT/GPT-4 for Medical Imaging", 2024
J72. Y. Wang, Y. Luo, C. Zu, B Zhan, Z. Jiao, Xi Wu, J. Zhou*, D. Shen, and L. Zhou*， “3D Multi-Modality Transformer-GAN for High-quality PET Reconstruction”, Medical Image Analysis (MedIA), 2024
J71. C. Tang, X. Zeng, L. Zhou, Q. Zhou, P. Wang, X.Wu, H. Ren, J. Zhou, and Y. Wang, "Semi-supervised Medical Image Segmentation via Hard Positives oriented Contrastive Learning", Pattern Recognition (PR), 2024
J70. X. Tian, Y. Chen, Y. Yan, L. Li, L. Zhou, L. Nguyen, and X. Yi, "Wide-range Operation of Microwave Photonic Sensor Using Recurrent Neural Network", Journal of Lightwave Technology (JLT), 2024
J69. Y. Chen, X. Tian, J. Sved, L. Li, L. Zhou, L. Nguyen, and X. Yi, "Reflective Microring Resonator Based Microwave Photonic Sensor Incorporating Self-Attention Assisted Convolutional Neural Network", Applied Optics, 2024
J68. X. Yi, X. Tian, L. Zhou, L. Li, L. Nguyen, and R. Minasian, "Integrated Microresonator-based Microwave Photonic Sensors Assisted by Machine Learning", Journal of Lightwave Technology (JLT), 2024
C88. Z. Chen, L. Zhou, Z. Hu, and D. Xu, "Group-aware Parameter-efficient Updating for Content-Adaptive Neural Video Compression", ACM Multimedia (MM), Melbourne, Australia, 2024
C87. Z. Wang, L. Wang*, Z. Zhao, M. Wu, C. Lyu, H., Li, D. Cai, L. Zhou*, S. Shi, and Z. Tu*, "Gpt4video: A Unified Multimodal Large Language Model for Instruction-followed Understanding and Safety-aware Generation", ACM Multimedia (MM), Melbourne, Australia, 2024 (Oral Presentation, *co-corresponding authors, Best Paper Nomination)
C86. Z. Zhao, ZC. Wang, L. Wang*, Y. Yuan, and L. Zhou*, "Alternate Diverse Teaching for Semi-supervised Medical Image Segmentation", European Conference on Computer Vision (ECCV), Milano, Italy, 2024
C85. ZC Wang, Z. Zhao, Y. Wu, L. Zhou*, and D. Xu*, "Progressive Target-Styled Feature Augmentation for Unsupervised Domain Adaptation on Point Clouds", European Conference on Computer Vision (ECCV), Milano, Italy, 2024
C84. Y. Li, Z. Wang, Y. Liu, L. Wang, L. Liu, and L. Zhou*, “KARGEN: Knowledge-enhanced Automated Radiology Report Generation Using Large Language Models” International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Morocco, 2024 (Early Accept)
C83. Y. Liu, Z. Wang, Y. Li, X. Liang, L. Liu, L. Wang, and L. Zhou*, “MRScore: Evaluating Radiology Report Generation with LLM-based Reward System” International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Morocco, 2024 (Early Accept)
C82. T. Chen, Q. Lyu, L. Bai, E. Guo, H. Gao, X. Yang, H. Ren, and L. Zhou*, "LighTDiff: Surgical Endoscopic Image Low-Light Enhancement with T-Diffusion", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Morocco, 2024 (Early Accept, MICCAI'24 Best Paper Honorable Mention (2 of 1))
C81. Y. Yue, M. Proctor, L. Zhou, R. Gupta, T. Piyadasa1, A. Gully, K. Ballard, and C. Jin, "Towards Speech Classification from Acoustic and Vocal Tract Data in Real-time MRI", Interspeech, Kos Island, Greece, 2024
C80. Z. Fu, K. Song, L. Zhou, and Y. Yang, "Noise-Aware Image Captioning with Progressively Exploring Mismatched Words", Thirty-Eight AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024
C79. X. Liu, Z Chen, L. Zhou, D. Xu, W. Xi, G. Bai, Y. Zhao, and J. Zhao, "UFDA: Universal Federated Domain Adaptation with Practical Assumptions", Thirty-Eight AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024
C78. Y. Duan, Z. Zhao, L. Qi, L. Zhou, L. Wang, and Y. Shi, "Roll With the Punches: Expansion and Shrinkage of Soft Label Selection for Semi-supervised Fine-Grained Learning", Thirty-Eight AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024
2023
J67. JD. Zhang, Z. Cui, L. Zhou*, Y. Sun, Z. Li*, Z. Liu, and D. Shen*, "Breast Fibroglandular Tissue Segmentation for Automated BPE Quantification with Iterative Cycle-consistent Semi-supervised Learning", IEEE Transactions on Medical Imaging (IEEE T-MI), 2023 (*co-corresponding authors)
J66. X. Yang, G. Lin, and L. Zhou*, "Single-view 3D Mesh Reconstruction for Seen and Unseen Categories", IEEE Transactions on Image Processing (IEEE T-IP), 2023 (accepted)
J65. E. Guo, H. Fu, L. Zhou, and D. Xu, "Bridging Synthetic and Real Images: a Transferable and Multiple Consistency aided Fundus Image Enhancement Framework", IEEE Transactions on Medical Imaging (IEEE T-MI), 2023 (accepted)
J64. J. Zhang, Z. Zhang, L. Wang, L. Zhou, X. Zhang, M. Liu, W. Wu, “Kernel-based Feature Aggregation Framework in Point Cloud Networks”, Pattern Recognition (PR), 2023 (accepted)
J63. M. Tang, Z. Wang, Z. Zeng, X. Li, and L. Zhou, "Stay in Grid: Improving Video Captioning via Fully Grid-level Representation", IEEE Transactions on Circuits and Systems for Video Technology (IEEE T-CSVT), 2023 (accepted)
J62. Y. Duan, Z. Zhao, L. Qi, L. Wang, L. Zhou, Y. Shi, and Y. Gao, "MutexMatch: Semi-supervised Learning with Mutex-based Consistency Regularization", IEEE Transactions. on Neural Networks and Learning Systems (IEEE T-NNLS), 2023
J61. JD. Zhang, Z. Cui, Z. Shi, Y. Jiang, Z. Zhang, X. Dai, Z. Yang, Y. Gu, L. Zhou, C. Han, X. Huang, C. Ke, S. Li, Z. Xu, F. Gao, L. Zhou, R. Wang, J. Liu, J. Zhang, Z. Ding, K. Sun, Z. Li, Z. Liu, and D. Shen, "A Robust and Efficient AI Assistant for Breast Tumor Segmentation from DCE-MRI via a Spatial-temporal Framework", Patterns (Cell Press), 2023 (accepted）
J60. F. Liu, J. Yang, M. Feng, Z. Cui, X. He, L. Zhou*, J. Feng*, and D. Shen*, "Does Perfect Filtering Really Guarantee Perfect Phase Correction for Diffusion MRI Data?", Computerised Medical Imaging and Graphics (CMIG), 2023 (* co-corresponding authors)
J59. X. Tian, Y. Yan, Y. Chen, L. Li, L. Zhou, L. Nguyen, R. Minasian, and X. Yi， "Deep Learning Enhanced Time-Domain Microwave Photonic Sensor", Journal of Lightwave Technology (JLT), 2023
J58. X. Tian, L. Zhou, L. Li, G. Gunawan, L. Nguyen, and X. Yi, "Deep Learning Assisted Microwave Photonic Dual-parameter Sensing", Journal of Selected Topics in Quantum Electronics (JSTQE), 2023
J57. J. Sved, S. Song, Y. Chen, L. Zhou, R. Minasian, and X. Yi, "Machine Learning Assisted Two-Dimensional Beam-Steering for Integrated Optical Phased Arrays", Optics Communications, 2023
C77. JD. Zhang, Q. Chen, L. Zhou, Z. Cui, F. Gao, Z. Li, Q. Feng, and D. Shen, "MoSID: Modality-Specific Information Disentanglement from Multi-parametric MRI for Breast Tumor Segmentation", MICCAI Workshop on Cancer Prevention through Early Detection, 2023
C76. X. Tian, Y. Chen, Y. Yan, L. Li, L. Zhou, L. Nguen, and X. Yi, "Deep Learning Assisted Wide-range Microwave Photonic Sensing", IEEE International Topical Meeting on Microwave Photonics (IEEE MWP), 2023
C75. X. Tian, L. Li, L. Zhou, L. Nguyen, R. Minasian, and X. Yi, "Integrated Microwave Photonic Sensors", International Conference on Optical Communications and Networks (ICOCN), 2023
C74. Z. Zhao, M. Zhao, Y. Liu, D. Yin, and L. Zhou*, "Entropy-based Optimization on Individual and Global Predictions for Semi-Supervised Learning", ACM Multimedia (MM), Canada, 2023
C73. Z. Chen, L. Relic, R. Azevedo, Y. Zhang, M. Gross, D. Xu, L. Zhou, and C. Schroers, "Neural Video Compression with Spatio-Temporal Cross-Covariance Transformers", ACM Multimedia (MM), Canada, 2023
C72. B. P. Voutharoja, L. Wang, and L. Zhou, "Automatic Radiology Report Generation by Learning with Increasingly Hard Negatives", European Conference on Artificial Intelligence (ECAI), Kraków, Poland, 2023 (oral presentation)
C71. Z. Zhang, L. Wang, L. Zhou, and P. Koniusz, "Learning Spatial-context-aware Global Visual Feature Representation for Instance Image Retrieval", International Conference on Computer Vision (ICCV), Paris, 2023
C70. G. Gui, Z. Zhao, L. Qi, L. Zhou, L. Wang, and Y. Shi, “Enhancing Sample Utilization through Sample Adaptive Augmentation in Semi-Supervised Learning”, International Conference on Computer Vision (ICCV), Paris, 2023
C69. Y. Duan, Z. Zhao, L. Qi, L. Zhou, L. Wang, and Y. Shi, "Class Transition Tracking Based Pseudo-Rectifying Guidance for Semi-supervised Learning with Non-random Missing Labels", International Conference on Computer Vision (ICCV), Paris, 2023
C68. S. Long, Z. Zhao, J. Yuan, Z. Tan, J. Liu, L. Zhou, S. Wang, and J. Wang, "Task-Oriented Multi-Modal Mutual Leaning for Vision-Language Models", International Conference on Computer Vision (ICCV), Paris, 2023
C67. Z. Han, Y. Wang, L. Zhou, P. Wang, B. Yan, J. Zhou, Y. Wang, and D. Shen, "Contrastive Diffusion Model with Auxiliary Guidance for Coarse-to-Fine PET Reconstruction", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Canada, 2023 (Early Accept)
C66. Z. Wang, L. Liu, L. Wang and L. Zhou*, “METransformer: Radiology Report Generation by Transformer with Multiple Expert Learners,” The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
C65. X. Yang, G. Lin, Z. Chen, and L. Zhou*, "Neural Vector Fields: Implicit Representation by Explicit Learning", The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
C64. Z. Zhao, S. Long, J. Pi, J. Wang, and L. Zhou*, "Instance-specific and Model-adaptive Supervision for Semi-supervised Semantic Segmentation", The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
C63. Z. Zhao, L. Yang, S. Long, J. Pi, L. Zhou, and J. Wang, "Augmentation Matters: A Simple-yet-Effective Approach to Semi-supervised Semantic Segmentation", The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
C62. ZC. Wang, Z. Zhao, X. Xing, D. Xu, X. Kong, and L. Zhou*, "Conflict-Based Cross-View Consistency for Semi-Supervised Semantic Segmentation", The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
C61. S. Rahman, P. Koniusz, L. Wang, L. Zhou, P. Moghadam and C. Sun, "Learning Partial Correlation based Deep Visual Representation for Image Classification," The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2023
C60. Y. Liu, Z. Wang, D. Xu, and L. Zhou*, "Q2ATransformer: Improving Medical VQA by an Answer Querying Decoder", Information Processing in Medical Imaging (IPMI), Argentina, 2023 (Oral Presentation, *corresponding author) [Code]
C59. C Tang, X Zeng, L. Zhou, X. Wu, J. Zhou, P. Wang, and Y. Wang, “Leveraging Hard Positives For Contrastive Learning In Semi-Supervised Medical Image Segmentation”, IEEE International Symposium on Biomedical Imaging (ISBI)， 2023
2022
J56. J. Zhang, L. Zhou, L. Wang, M. Liu, and D. Shen, "Diffusion Kernel Attention Network for Brain Disorder Classification", IEEE Transactions on Medical Imaging (IEEE T-MI), 2022
J55. Z. Wang, H. Han, L. Wang, X. Li, and L. Zhou*, "Automated Radiographic Report Generation Purely on Transformer: A Multi-criteria Supervised Approach", IEEE Transactions on Medical Imaging (IEEE T-MI), 2022 (* corresponding author)
J54. X. Tian, G. Gunawa, L. Zhou, L. Li, L. Nguyen, R. Minasian, and X. Yi*, "Athermal Microwave Photonic Sensor Based on Single Microring Resonance Assisted by Machine Learning", Journal of Lightwave Technology (JLT), 2022
J53. B. Zhan, L. Zhou, Z. Li, X. Wu, Y. Pu, J. Zhou, Y. Wang*, and D. Shen, "D2FE-GAN: Decoupled Dual Feature Extraction based GAN for MRI Image Synthesis", Knowledge-Based Systems (KBS), 2022 (accepted in June 2022)
J52. K. Wang, Y. Wang, B. Zhan, Y. Yang, C. Zu, X. Wu, J. Zhou, D. Nie, and L. Zhou, "An Efficient Semi-supervised Framework with Multi-Task and Curriculum Learning for Medical Image Segmentation", International Journal of Neural Systems, 2022 (accepted in June 2022)
J51. M. Yuan, G. Yang, Shijie Song, L. Zhou, R. Minasian, and X. Yi*, "Inverse Design of Nano-photonic Wavelength Demultiplexer with a Deep Neural Network Approach", Optics Express (OE), 2022 (accepted in June 2022)
J50. P. Zhuang, Y. Guo, Z. Yu, L. Zhou, L. Bai, D. Liang, Z. Wang, Y. Wang, and W. Ouyang, "Action Recognition with Motion Diversification and Dynamic Selection", IEEE Transactions on Image Processing (IEEE T-IP), 2022
J49. K. Wang, B. Zhan, C. Zu, X. Wu, J. Zhou, L. Zhou, and Y. Wang, "Semi-supervised Medical Image Segmentation via a Tripled-uncertainty Guided Mean Teacher Model with Contrastive Learning", Medical Image Analysis (MedIA), 2022 (accepted)
J48. R. Zeng, J. Lv, H. Wang, L. Zhou, M. Barnett, F. Calamante, and C. Wang, "FOD-Net: A Deep Learning Method for Fiber Orientation Distribution Angular Super-Resolution", Medical Image Analysis (MedIA), 2022 (accepted)
J47. Y. Shi, C. Zu, M. Hong, L. Zhou, L. Wang, X. Wu, J. Zhou, D. Zhang, and Y., Wang, "ASMFS: Adaptive-Similarity-based Multi-modality Feature Selection for Classification of Alzheimer's Disease", Pattern Recognition (PR), 2022
J46. Z. Zhang, L. Wang, Y. Wang, L. Zhou, J. Zhang, and F. Wang, "Dataset-driven Unsupervised Object Discovery for Region-based Instance Image Retrieval", IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), 2022
J45. Y. Luo, L. Zhou, B. Zhan, Y. Fei, J. Zhou, Y. Wang, and D. Shen, "Adaptive Rectification based Adversarial Network with Spectrum Constraint for High-quality PET Image Synthesis", Medical Image Analysis (MedIA), 2022
C58. G. Guan, Z. Zhao, L. Qi, L. Zhou, L. Wang, and Y. Shi, "Improving Barely Supervised Learning by Discriminating Unlabeled Samples with Super-Class", Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022
C57. Y. Duan, L. Qi, L. Wang, L. Zhou, Y. Shi, "RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning", European Conference on Computer Vision (ECCV), Tel-Aviv, Israel, 2022
C56. Z. Wang, M. Tang, L. Wang, X. Li, and L. Zhou*, "A Medical Semantic-Assisted Transformer for Radiographic Report Generation", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Singapore, 2022 (*corresponding author)
C55. P. Zeng, L. Zhou, C. Zu, X. Zeng, Z. Jiao, X. Wu, J. Zhou, D. Shen, and Y. Wang*, "3D CVT-GAN: A 3D Convolutional Vision Transformer-GAN for PET Reconstruction", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Singapore, 2022
C54. Z. Zhao, L. Zhou*, Y. Duan, L. Wang, L. Qi, and Y. Shi*, "DC-SSL: Addressing Mismatched Class Distribution in Semi-supervised Learning", IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2022 (accepted)
C53. Z. Zhao, L. Zhou*, L. Wang, Y. Shi*, and Y. Gao, "LaSSL: Label-guided Self-training for Semi-supervised Learning", Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2022 (Oral Presentation, * co-corresponding authors) [code]
2021
BC6. J. Zhang*, Y. Wang*, C. Zu*, B. Yu*, L. Wang, and L. Zhou, "Medical Imaging Based Diagnosis Through Machine Learning and Data Analysis", In: Pham T.D., Yan H., Ashraf M.W., Sjöberg F. (eds) Advances in Artificial Intelligence, Computation, and Data Science. Computational Biology. Springer, Cham (Print ISBN: 978-3-030-69950-5, * equally contributed)
J44. R. Su, D. Xu, L. Zhou, and W. Ouyang, "Improving Weakly Supervised Temporal Action Localization by Exploiting Multi-resolution Information in Temporal Domain", IEEE Transactions on Image Processing (IEEE T-IP), 2021 (accepted in May 2021)
J43. X. Wu, L. Bi*, M. Fulhama, D. D. Feng, L. Zhou, and J. Kim*, "Unsupervised Brain Tumor Segmentation using a Bilateral Symmetric Driven Adversarial Network", Neurocomputing, 2021 (accepted in May 2021)
J42. M. Dashtbani, L. Zhou, B. Yu, N. Young, K. Moore, A. Evans; R. Fulton, and A. Kyme, "Efficient Radiation Dose Reduction in Whole-Brain CT Perfusion Imaging Using a 3D GAN: Performance and Clinical Feasibility", Physics in Medicine and Biology, 2021 (accepted in February 2021)
J41. B. Yu, L. Zhou*, L. Wang*, W. Yang, M. Yang, P. Bourgeat, and J. Fripp, "SA-LuT-Nets: Learning Sample-adaptive Intensity Lookup Tables for Brain Tumor Segmentation", IEEE Transactions on Medical Imaging (IEEE T-MI), 2021 (* co-corresponding authors, accepted in January 2021)
J40. B. Zhan, D. Li, Y. Wang, Z. Ma, X. Wu, J. Zhou, and L. Zhou, "LR-cGAN: Latent representation based conditional generative adversarial network for multi-modality MRI synthesis", Biomedical Signal Processing and Control (BSPC), 2021 (accepted in January 2021)
J39. P. Tang, C. Zu, M. Hong, R. Yan, X. Peng, J. Xiao, X. Wu, J. Zhou, L. Zhou, and Y Wang, "DA-DSUnet: Dual Attention-based Dense SU-net for Automatic Head-and-neck Tumor Segmentation in MRI Images", Neurocomputing 2021 (accepted)
J38. J. Zhang, Y. Shi, J. Sun, L. Wang, L. Zhou, Y. Gao, and D. Shen, "Interactive Medical Image Segmentation via A Point-based Interaction", Artificial Intelligence in Medicine, 2021 (Accepted)
C52. S. Huang, W. Yang, L. Wang, L. Zhou, and M. Yang, "Few-shot Unsupervised Domain Adaptation with Image-to-Class Sparse Similarity Encoding", ACM International Conference on Multimedia (ACM MM), 2021
C51. Y. Luo, Y. Wang*, C. Zu, B. Zhan, X. Wu, J. Zhou, D. Shen*, and L. Zhou*, "3D Transformer-GAN for High-quality PET Reconstruction", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Strasburg, France, 2021 (*co-corresponding authors)
C50. K. Wang, B. Zhan, C. Zu, X. Wu, J. Zhou, L. Zhou, and Y. Wang, "Tripled-uncertainty Guided Mean Teacher Model for Semi-supervised Medical Image Segmentation", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Strasburg, France, 2021
C49. Z. Wang, L. Zhou*, L. Wang, and X. Li, "A Self-boosting Framework for Automated Radiographic Report Generation", IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2021 (* corresponding author, accepted)
C48. G. Gunawan, X. Tian, L. Zhou, L. Li, L. Nguyen, X. Yi, "Machine Learning Assisted Temperature Insensitive Microwave Photonic Sensor Based on Single Microring Resonance" , 2021 International Topical Meeting on Microwave Photonics (MWP 2021), Matsue: Institute of Electrical and Electronics Engineers (IEEE)
2020
BC5. D. Shen, L. Zhou, and M. Liu, "Deep Learning Models with Applications to Brain Image Analysis", Neural Engineering (Print ISBN: 978-3-030-43394-9, edited by Bin He), Springer, p433-462, 2020
BC4. B. Yu, Y. Wang, L. Wang, D. Shen and L. Zhou, "Medical Image Synthesis via Deep Learning", Deep Learning in Medical Image Analysis (ISBN-13: 978-3030331276, edited by Gobert Lee and Hiroshi Fujita), 2020
J37. J. Zhang, L. Wang, L. Zhou and W. Li, “Beyond Covariance: SICE and Kernel based Visual Feature Representation”, International Journal of Computer Vision (IJCV) 2020 (accepted in August, 2020)
J36. S. Rahman, L. Wang, C. Sun, and L. Zhou, "Deep Learning based HEp-2 Image Classification: A Comprehensive Review", Medical Image Analysis (MedIA), 2020 (accepted in June 2020)
J35. Z. Zhou, L. Zhou* and K. Shen, "Dilated Conditional Generative Adversarial Network for Bone Suppression in Chest Radiographs with Enforced Semantic Features", Medical Physics, 2020 (accepted in June 2020)
J34. R. Su, D. Xu, L. Zhou, and W. Ouyang, “Progressive Cross-stream Cooperation in Spatial and Temporal Domain for Action Localization,” IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), 2020 (accepted in May 2020)
J33. Z. Zhang, D. Xu, W. Ouyang and L. Zhou, "Dense Video Captioning using Graph-based Sentence Summarization", IEEE Transactions on Multimedia (IEEE T-MM), 2020 (accepted in May 2020)
J32. T. Liu, N. D. Truong, A. Nikpour, L. Zhou, and O. Kavehei, "Epileptic Seizure Classification with Symmetric and Hybrid Bilinear Models", IEEE Journal of Biomedical and Health Informatics (JBHI), 2020 (accepted in March 2020)
J31. J. Huang, L. Zhou, L. Wang, and D. Zhang, "Attention-Diffusion-Bilinear Neural Network for Brain Network Analysis", IEEE Transactions on Medical Imaging (IEEE T-MI), 2020 (accepted in Feb 2020)
J30. B. Yu, L. Zhou*, L. Wang*, Y. Shi, J. Fripp, and P. Bourgeat, "Sample-adaptive GANs: Linking Global and Local Mappings for Cross-modality MR Image Synthesis", IEEE Transactions on Medical Imaging (IEEE T-MI), 2020 (*co-corresponding authors, accepted in Jan 2020)
C47. K. Tian, C. Lin, M. Sun, L. Zhou, J. Yan, and W. Ouyang, "Improving Auto-Augment via Augmentation-Wise Weight Sharing", Annual Conference on Neural Information Processing Systems (NeurlPS), 2020
C46. X. Yang, B. Wang, K. Chen, X. Zhou, S. Yi, W. Ouyang, and L. Zhou*, "BriNet: Towards Bridging the Intra-class and Inter-class Gaps in One-Shot Segmentation", British Computer Vision Conference (BMVC), Manchester, UK, 2020 (Oral Presentation, * corresponding author) [Code]
C45. S. Rahman, L. Wang, C. Sun, and L. Zhou, "ReDro: Efficiently Learning Large-sized SPD Visual Representation", European Conference on Computer Vision (ECCV), Glasgow, UK, 2020
C44. B. Yu, L. Zhou*, L. Wang*, W. Yang, M. Yang, P. Bourgeat, and J. Fripp, "Learning Sample-adaptive Intensity Lookup Table for Brain Tumor Segmentation", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Lima, Peru, 2020
2019
B5 D. Zhang, L. Zhou, B. Jie, and M. Liu, (Eds) "Graph Learning in Medical Imaging", 1st International Workshop GLMI, in conjunction with MICCAI 2019, Proceedings, Springer (ISBN: 978-3-030-35816-7), 2019
J29. B. Yu, L. Zhou*, L. Wang*, Y. Shi, J. Fripp, and P. Bourgeat, "Ea-GANs: Edge-aware Generative Adversarial Networks for Cross-modality MR Image Synthesis", IEEE Transactions on Medical Imaging (IEEE T-MI), 2019 (*co-corresponding authors, winning the Dolby Scientific Paper Competition in Jan 2020) [Code]
J28. J. Huang, Q. Zhu, M. Wang, L. Zhou, Z. Zhang, and D. Zhang, "Coherent Pattern in Multi-layer Brain Networks: Application to Epilepsy Identification", IEEE Journal of Biomedical and Health Informatics (JBHI), accepted in December 2019
J27. N.D. Truong, L. Kuhlmann, M.R. Bonyadi, D. Querlioz, L. Zhou, and O. Kavehei, "Epileptic Seizure Forecasting with Generative Adversarial Networks", IEEE Access 2019, In Press
C43. H. Wang, L. Zhou, and L. Wang, "Missed Detection vs False Alarm: Adversarial Learning for Small Object Segmentation", International Conference on Computer Vision (ICCV), Seoul, Korea, 2019 [Code]
C42. L. Qi, L. Wang, J. Huo, L. Zhou, Y. Shi. and Y. Gao, "A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-ID", International Conference on Computer Vision (ICCV), Seoul, Korea, 2019
C41. J. Huang, L. Zhou, L. Wang*, and D. Zhang*,"Integrating Functional and Structural Connectivities via Diffusion-Convolution-Bilinear Neural Network", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI) , Shenzhen, China, 2019 (early accept)
C40. R. Su, W. Ouyang, L. Zhou, and D. Xu, "Improving Action Localization by Progressive Cross-stream Cooperation", IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019
C39. Z. Zhou, X. Guo, W. Yang, Y. Shi, L. Zhou, L. Wang, and M. Yang, "Cross-Modal Attention-Guided Convolutional Network for Multi-Modal Cardiac Segmentation", 10th International Workshop on Machine Learning for Medical Imaging (MLMI), in conjunction with MICCAI2019, Shenzhen, China, 2019 (oral)
C38. N. D. Truong, L. Zhou, and O. Kavehei, “Semi-supervised Seizure Prediction with Generative Adversarial Networks,” Proc. International Engineering in Medicine and Biology Conference (EMBC), Berlin, Germany, 2019.
CA8. M.D. Moghari, L. Zhou, B. Yu, K. Moore, N. Young, R. Fulton and A. Kyme, “Estimation of Full-dose 4D CT Perfusion Images from Low-dose Images Using Conditional Generative Adversarial Networks”, IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC) 2019
CA7. J. Sun, R. Alam, L. Zhou, and A. McEwan, "Measurement of Body Fat in Premature and Term Infants by Near-Infrared Spectroscopy", PSANZ (The Perinatal Society of Australia and New Zealand ) Annual Congress 2020
2018
B4. L. Zhou, I. Rekik, C. Yan, and G. Wu (Eds.), Neuroinformatics special issue on "High Performance Computing in Bio-medical Informatics", ISSN: 1539-2791 (Print) 1559-0089 (Online), 2018
J26. Y. Wang, L. Zhou*, B. Yu, L. Wang, C. Zu, D.S. Lalush, W. Lin, X. Wu, J. Zhou, and D. Shen* , "3D Auto-context-based Locality Adaptive Multi-modality GANs for PET Synthesis ", IEEE Transactions on Medical Imaging (IEEE T-MI), 2019 (*co-corresponding authors, accepted in November 2018)
J25. Z. Gao, L. Wang, and L. Zhou, "A Probabilistic Approach to Cross-region Matching based Image Retrieval", IEEE Transactions on Image Processing (IEEE T-IP), 2018 (accepted in September, 2018)
J24. Y. Wang, B. Yu, L. Wang, C. Zu, D.S. Lalush, W. Lin, X. Wu, J. Zhou, D. Shen*, and L. Zhou*, "3D Conditional Generative Adversarial Networks for High-quality PET Image Estimation at Low Dose", Neuroimage, 2018 (*co-corresponding authors)
C37. M. Engin, L. Wang, L. Zhou, and X. Liu, "DeepKSPD: Learning Kernel-matrix-based SPD Representation for Fine-grained Image Recognition", European Conference on Computer Vision (ECCV), Munich, Germany, 2018
C36. Y. Zhao, L. Wang, L. Zhou, Y. Shi, and Y. Gao, "Modeling Diffusion Process by Deep Neural Networks for Image Retrieval", British Machine Vision Conference (BMVC), Newcastle, UK, 2018 (spotlight presentation)
C35. Y. Wang, L. Zhou*, L. Wang, B. Yu, C. Zu, D.S. Lalush, W. Lin, X. Wu, J. Zhou, and D. Shen*, "Locality Adaptive Multi-modality GANs for High-quality PET Image Synthesis", International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI) , Granada, Spain, 2018 (*co-corresponding authors)
C34. Z. Zhang, L. Wang, Y. Wang, L. Zhou, J. Zhang and F. Chen, “Instance Image Retrieval by Aggregating Sample-based Discriminative Characteristics”, ACM International Conference on Multimedia Retrieval (ICMR), Yokohama, Japan, 2018 (oral presentation)
C33. C. Zu, Y. Wang, L. Zhou, L. Wang, and D. Zhang, “Multi-modality Feature Selection with Adaptive Similarity Learning for Classification of Alzheimer's Disease”, IEEE International Symposium on Biomedical Imaging (ISBI), Washington DC, USA, 2018 (oral presentation)
C32. B. Yu, L. Zhou*, L. Wang, J. Fripp, and P. Bourgeat, “3D cGAN based Cross-modality MR Image Synthesis for Brain Tumor Segmentation”, IEEE International Symposium on Biomedical Imaging (ISBI), Washington DC, USA, 2018 (*corresponding author, oral presentation)
C31. Y. Wang, B. Yu, L. Wang, C. Zu, Y. Luo, X. Wu, J. Zhou, and L. Zhou*, “Tumor Segmentation via Multi-modality Joint Dictionary Learning”, IEEE International Symposium on Biomedical Imaging (ISBI), Washington DC, USA, 2018 (*corresponding author)
C30. P. Tian, L. Qi, Y. Shi, L. Zhou, Y. Gao, and D. Shen, “A Novel Image-specific Transfer Approach for Prostate Segmentation in MR Images”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Alberta, Canada, 2018
C29. J. Wu, L. Zhou, C. Cai, J. Shen, and S.K. Lau, “Data Fusion for MaaS: Opportunities and Challenges”, IEEE 22nd International Conference on Computer Supported Cooperative Work in Design (CSCWD), Nanjing, China, 2018
2017
B3. K. Suzuki, L. Zhou, and Q. Wang (Eds): Special issue on "Machine learning in medical imaging", Pattern Recognition 63: 465-467, 2017
J23. H. An, L. Zhou, Y. Yu, H. Fan, F. Fan, S. Tan, Z. Wang, Z B, J. Shi, F. Yang, X. Zhang, Y. Tan, and X. Huang, “Serum NCAM Levels and Cognitive Deficits in First Episode Schizophrenia Patients versus Health Controls”, Schizophrenia Research, 2017 (online in June, 2017)
J22. W. Li, Y. Gao, L. Wang, L. Zhou, J. Huo, and Y. Shi, "OPML: A One-Pass Closed-Form Solution for Online Metric Learning”, Pattern Recognition (PR), 2017 (accepted in March 2017)
J21. H. Ni, J. Qin, L. Zhou, Z. Zhao, J. Wang, and F. Hou, “Network Analysis in Detection of Early-stage Mild Cognitive Impairment”, Physica A: Statistical Mechanics and its Applications, 2017 (accepted in March 2017)
C28. L. Zhou, L. Wang, J. Zhang, Y. Shi and Y. Gao, "Revisiting Distance Metric Learning for SPD Matrix based Visual Representation", IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, USA, 2017
C27. Z. Gao, L. Wang, L. Zhou, and M. Yang, “Infomax Principle Based Pooling of Deep Convolutional Activations for Image Retrieval”, IEEE International Conference on Multimedia and Expo (ICME), Hong Kong, 2017 (Finalist of the World's FIRST 10K Best Paper Award at IEEE ICME 2017)
2016
J20. L. Zhou, L. Wang, L. Liu, P. Ogunbona, and D. Shen, “Learning Discriminative Bayesian Networks from High-dimensional Continuous Neuroimaging Data”, IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI), 2016.
J19. L. Wang, L. Liu, and L. Zhou, “A Graph-embedding Approach to Hierarchical Visual Word Mergence”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 2016.
J18. Z. Gao, L. Wang, L. Zhou, and J. Zhang, “HEp-2 Cell Image Classification with Deep Convolutional Neural Networks”, IEEE Journal of Biomedical and Health Informatics (IEEE JBHI, originally IEEE T-ITB), 2016
J17. J. Zhang, L. Zhou, and L. Wang, “Subject-adaptive Integration of Multiple SICE Brain Networks with Different Sparsity”, Pattern Recognition (PR), 2016 (accepted in Sept. 2016)
C26. Y. Zhao, L. Wang, I. Comor, Z. Gao, W. Zhang, and L. Zhou, “Semi-supervised Weight Learning for the Spatial Search Method in ConvNet-based Image Retrieval”, The International Conference on Digital Image Computing Techniques and Applications (DICTA), Gold Coast, Australia, 2016 (oral presentation)
C25. I. Comor, Y. Zhao, Z. Gao, W. Zhang, L. Zhou, and L. Wang, “Image Descriptors from ConvNets: Comparing Global Pooling Methods for Image Retrieval”, The International Conference on Digital Image Computing Techniques and Applications (DICTA), Gold Coast, Australia, 2016 (oral presentation)
2015
B2. L. Zhou, L. Wang, Q. Wang, and Y. Shi (Eds.), "Machine Learning in Medical Imaging" – 6th international workshop, MLMI2015, Held inConjunction with MICCAI 2015 in Munich, Germany, Proceedings, Springer (ISBN: 978-3-319-24888-2), 2015
J16. H. Ni, L. Zhou, X. Ning, and L. Wang, “Exploring Multifractal-based Features for Mild Alzheimer’s Disease Classification”, Magnetic Resonance in Medicine (MRM), 2015 (accepted in June 2015,)
J15. J. Zhang, L. Wang, L. Zhou, and W. Li, “Learning Discriminative Stein Kernel for SPD Matrices and Its Applications”, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 2015 (accepted in May 2015)
J14. J. Zhang, L. Zhou, L. Wang, and W. Li, “Functional Brain Network Classification with Compact Representation of SICE Matrices”, IEEE Transactions on Biomedical Engineering (T-BME), 2015 (accepted in Jan 2015)
J13. H. Ni, L. Zhou, P. Zeng, X. Huang, H. Liu, X. Ning, “Multifractal Analysis of White Matter Structural Changes on 3D Magnetic Resonance Imaging between Normal Ageing and Early Alzheimer’s Disease”, Chinese Physics B (English Edition), 2015 (accepted in March 2015, SCI-indexed)
C24. L. Wang, J. Zhang, L. Zhou, C. Tang, and W. Li, “Beyond Covariance: Feature Representation with Nonlinear Kernel Matrices”, International Conference on Computer Vision (ICCV), Santiago, Chile, 2015
2014
B1. G. Wu, D. Zhang, and L. Zhou (Eds.), "Machine Learning in Medical Imaging" – 5th international workshop, MLMI2014, Held in Conjunction with MICCAI 2014 in Boston, USA, Proceedings, Springer (ISBN: 978-3-319-10580-2), 2014
J12. (accepted in Dec 2014)
C23. L. Zhou, L. Wang, and P. Ogunbona, “Discriminative Sparse Inverse Covariance Matrix: Application in Brain Functional Network Classification”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Ohio, USA, 2014
C22. L. Zhou, L. Wang, L. Liu, P. Ogunbona, and D. Shen, “Max-margin Based Learning for Discriminative Bayesian Network from Neuroimaging Data”, International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), Boston, USA, 2014
C21. J. Zhang, L. Zhou, L. Wang, L. Li, “Exploring Compact Representation of SICE Matrices for Functional Brain Network Classification”, MICCAI Workshop on Machine Learning in Medical Imaging (MLMI), Boston, USA, 2014 (oral presentation).
C20. Z. Gao, J. Zhang, L. Zhou and L. Wang, “HEp-2 Cell Image Classification with Convolutional Neural Networks”, The 1st Workshop on Pattern Recognition Techniques for Indirect Immunofluorescence Images Analysis in International Conference on Pattern Recognition (ICPR), Sweden, 2014 (invited paper, oral presentation)
C19. Y. Zhao, Z. Gao, L. Wang and L. Zhou, “Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering”, The International Conference on Digital Image Computing: Techniques and Applications (DICTA), Wollongong, Australia, 2014 (oral presentation)
CA6. V. Doré, P. Bourgeat, L. Zhou, J. Fripp, R. Martins, L. Macaulay, D. Ames, C. L. Masters, B. Brown, C. C. Rowe, O. Salvado, and V. L. Villemagne. "Automated Reporting of Amyloid PET Quantification on Brain Surface through a Web Interface", In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC), Copenhagen, Denmark, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2014
2013
BC3. L. Zhou, L. Wang, L. Liu, P. Ogunbona and D. Shen, "Support Vector Machines for Neuroimage Analysis: Interpretation from Discrimination", Support Vector Machines Applications, Springer (ISBN: 978-3-319-02300-7), 2013
BC2. L. Wang, L. Liu, L. Zhou and K.L. Chan, "Application of SVMs to the Bag-of-features Model – A Kernel Perspective", Support Vector Machines Applications, Springer (ISBN: 978-3-319-02300-7), 2013
J11. L. Wang, L. Zhou, C. Shen, L. Liu and H. Liu, “A Hierarchical Word-merging Algorithm with Class Separability Measure”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013 (accepted in August 3, 2013)
J10. L. Zhou, O. Salvado, V. Dore, P. Bourgeat, P. Raniga, S. L. Macaulay, D. Ames, C. L. Masters, K. A. Ellis, V. L. Villemagne, C. C. Rowe, and J. Fripp, “MR-less Surface-based Amyloid Assessment based on 11C PiB PET”, PLoS One, 2013 (accepted in November 2013)
J9. F. Liu, L. Zhou, C. Shen, J. Yin. “Multiple Kernel Learning in the Primal for Multi-modal Alzheimer's Disease Classification”, IEEE Journal on Biomedical and Health Informatics (originally titled IEEE Transactions on Information Technology in Biomedicine, accepted in September 30, 2013)
J8. V. Dore, V. L. Villemagne, P. Bourgeat, J. Fripp, O. Acosta, G. Chetelat, L. Zhou, R. Martins, K. Ellis, C. L. Masters, D. Ames, , O. Salvado, and C. C. Rowe. “Cross-sectional and Longitudinal Analysis of the Relationship between A Deposition, Cortical Thickness and Memory in Cognitively Unimpaired Individuals and Alzheimer’s Disease”, JAMA Neurology 2013;70(7):903-911
C18. L. Zhou, L. Wang, L. Liu, P. Ogunbona, and D. Shen, “Discriminative Brain Effective Connectivity Analysis for Alzheimers Disease: A Kernel Learning Approach upon Sparse Gaussian Bayesian Network”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Oregon, USA, 2013
C17. L. Wang, J. Zhang, L. Zhou, and W. Li, “A Fast Approximate AIB Algorithm for Distributional Word Clustering”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Oregon, USA, 2013
C16. J. Zhang, L. Wang, L. Liu, L. Zhou, W. Li. “Accelerating the Divisive Information-Theoretic Clustering of Visual Words”, International Conference on Digital Image Computing Techniques and Applications (DICTA), Tasmania, Australia, 2013.
CA5. V. Dore, P. Bourgeat, L. Zhou, J. Fripp, R. Martins, L. Macaulay, C. Masters, D. Ames, K.A. Ellis, C. Rowe, O. Salvado, and V. Villemagne. "MR-less Cortical Surface-projection of PET Scans with 11C and 18F Labeled Radiotracers", In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC), Boston, USA & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2013
2012
J7. Y. Li, Y. Wang, G. Wu, F. Shi, L. Zhou, W. Lin, and D. Shen, “Discriminant Analysis of Longitudinal Cortical Thickness Changes in Alzheimer's Disease Using Dynamic and Network Features”, Neurobiology of Aging, 2012
C15. L. Zhou, O. Salvado, V. Dore, P. Bourgeat, P. Raniga, V. L. Villemagne, C. C. Rowe, and J. Fripp, “MR-less Surface-based Amyloid Estimation by Subject-specific Atlas Selection and Bayesian Fusion”, In Proc. International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), France, October 2012
C14. P. Bourgeat, P. Raniga, V. Dore, L. Zhou, S.L. Macaulay, R. Martins, C. Masters, D. Ames, K. A. Ellis, V. Villemagne, C. Rowe, O. Salvado, and J. Fripp. “Manifold Driven MR-less PiB SUVR Normalisation”, In MICCAI 2012 Workshop on Novel Imaging Biomarkers for Alzheimer's Disease and Related Disorders (NIBAD'12), Nice, France, October 2012.
CA4. L. Zhou, V. Dore, J. Fripp, P. Bourgeat ,P. Raniga, R. Martins, L. Macaulay, C. Masters, D. Ames, K. A. Ellis, V. Villemagne, C. Rowe, O. Salvado, and AIBL research group. "MRI-independent Automated Surface-projection of Amyloid Imaging Scans", In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC), Canada, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2012
CA3. P. Bourgeat, J. Fripp, P. Raniga, V. Dore, L. Zhou, R. Martins, L. Macaulay, C. Masters, D. Ames, K.A. Ellis, V. Villemagne, C. Rowe, O. Salvado, and AIBL research group, "Longitudinal Modeling of Joint PiB/MRI Changes in Alzheimer’s Disease", In Alzheimer's Association International Conference in Alzheimer's Disease 2012, Vancouver (AAIC), Canada, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2012
CA2. P. Bourgeat, O. Salvado, P. Raniga, V. Dore, L. Zhou, R. Martins, L. Macaulay, C. Masters, D. Ames, K. A. Ellis, V. Villemagne, C. Rowe,J.Fripp, and AIBL research group, "Classification of Alzheimer’s subject based on PiB-MR Manifold learning", In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC), Canada, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2012.
CA1. V. Dore, J. Fripp, P. Bourgeat, O. Acosta, L. Zhou, P. Raniga, R. Martins, L. Macaulay, K. Ellis, C. Masters, D. Ames, V. Villemagne, C. Rowe, O. Salvado and AIBL research group, "Longitudinal Analysis of Cortical Thickness in PiB+ and PiB- Healthy Elderly Controls", In Alzheimer's Association International Conference in Alzheimer's Disease (AAIC) Canada, & Alzheimer’s and Dementia: journal of Alzheimer’s Association, 2012.
2011
BC1. C.Y. Wee*, D. Zhang*, L. Zhou*, P.T. Yap, and D. Shen. "Machine Learning Techniques for AD/MCI Diagnosis and Prognosis" (invited book chapter). Machine Learning in Healthcare Informatics, Springer, 2011. (* equally contribute)
J6. L. Zhou, Y. Wang, Y. Li, P.T. Yap, and D. Shen. “Hierarchical Anatomical Brain Networks for MCI Prediction: Revisiting Volumetric Measures”, PLoS One, 2011
J5. D. Zhang, Y. Wang, L. Zhou, H. Yuan, and D. Shen, “Multimodal Classification of Alzheimer's Disease and Mild Cognitive Impairment”, NeuroImage, 55(3):856-67, April 2011 (One of the three most-downloaded papers in Neuroimage 2011)
C13. L. Zhou, Y. Wang, Y. Li, P.T. Yap, and D. Shen, “Hierarchical Anatomical Brain Networks for MCI Prediction by Partial Least Square Analysis”, In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 11), Colorado Springs, USA, June 2011
C12. L. Zhou, S. Liao, W. Li, and D. Shen, “Learning-based Prostate Localization for Image Guided Radiation Therapy”, In IEEE International Symposium on Biomedical Imaging (ISBI), Chicago, USA, March 2011 (invited paper, oral presentation)
C11. L. Zhou and O. Salvado, “A Comparison Study of Ellipsoid Fitting for Pose Normalization of Hippocampal Shapes”, In Proceedings of International Conference on Digital Image Computing: Techniques and Applications (DICTA), Brisbane, Australia, December 2011
2010
J4. L. Zhou, L. Wang, and C. Shen, “Feature Selection with Redundancy Constrained Class Separability”, IEEE Transactions on Neural Networks, 2010 (IEEE TNN)
C10. L. Zhou, L. Wang, C. Shen, and N. Barnes, “Hippocampal Shape Classification Using Redundancy Constrained Feature Selection”, In Proc. International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), China, September 2010 (MICCAI Travel Award)
2009
J3. L. Zhou, R. Hartley, L. Wang, P. Lieby, and N. Barnes, "Identifying Anatomical Shape Difference by Regularized Discriminative Direction", IEEE Transactions on Medical Imaging, 28(6), June 2009, pp937-950
J2. L. Zhou, P. Lieby, N. Barnes, C. Reglade-Meslin, J. Walker, N. Cherbuin, and R. Hartley, "Hippocampal Shape Analysis for Alzheimer’s Disease Using an Efficient Hypothesis Test and Regularized Discriminative Deformation", Hippocampus, 19(6), June 2009, pp533-540
C9. Q. Shi, L. Zhou, L. Cheng, D. Schuurmans, “Discriminative Maximum Margin Object Categorization with Exact Inference”, The 5th International Conference on Image and Graphics (ICIG), September, Xi'An China, 2009
2008
J1. L. Wang, K.L. Chan, P. Xue, and L. Zhou, “A Kernel-induced Space Selection Approach to Model Selection of KLDA”, IEEE Transactions on Neural Networks, 19(12), December 2008, pp2116-2131
C8. L. Zhou, R. Hartley, L. Wang, P. Lieby, N. Barnes, “Regularized Discriminative Direction for Shape Analysis”, In Proc. International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), USA, September 2008, pp628-635
C7. L. Wang, L. Zhou, and C. Shen, "A Fast Algorithm for Creating A Compact and Discriminative Visual Codebook", 10th European Conference on Computer Vision (ECCV), France, October 2008, pp719-732
2007
C6. L. Zhou, R. Hartley, P. Lieby, N. Barnes, K. Anstey, N. Cherbuin and P. Sachdev, “A Study of Hippocampal Shape Difference Between Genders by Efficient Hypothesis Test and Discriminative Deformation”, In Proc. International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI) Australia, September 2007, pp375-383
Before 2006
C5. L. Zhou, Y. Wang, C. Goh, R. Kockro and L. Serra. “Stereoscopic Visualization and Editing of Automatic Abdominal Aortic Aneurysms (AAA) Measurements for Stent Graft Planning”, Proceedings of SPIEs Electronic Imaging, 16-19 January, San Jose, CA, USA, 2006.
C4. R. Kockro, X. Liang, C. Goh, L. Zhou, C. Zhu, T. Yeo, and L. Serra. “DexRay: An Augmented Reality Surgical Navigation System”, Proceedings of Conference of European Association of Neurosurgical Societies, September, Portugal, 2003.
C3. L. Zhou, I. Atmosukarto, W.K. Leow, and Z. Huang. “Reconstruting Surface Discontinuities by Intersecting Tangent Planes of Advancing Mesh Frontiers”, Proceedings of Computer Graphics International, 3-5 July, Bradford, UK, 2002.
C2. I. Atmosukarto, L. Zhou, W.K. Leow, and Z. Huang. “Polygonizing Nonuniformly Distributed 3D Points by Advancing Mesh Frontier”, Proceedings of Computer Graphics International, July, HK, 2001.
C1. W. Leow, Z. Huang, L. Zhou, I. Atmosukarto, and Y. Zhang. “Acquiring 3D Models from Images for Multimedia Systems”, Proceedings of Multimedia Modeling, November, HK,2000.