脑影像人工智能

论文“DyBrainFormer: Decoding Dynamic Brain Semantics with Hierarchical Transformer for Brain-Multimedia Association”被会议BIBM2025 conference接收

论文“HubRL: A Reinforcement Learning Framework for Brain Hub Identification via Dynamic-Static Network Fusion”被会议BIBM2025 conference接收

团队发明专利《一种基于自监督Graph-Transformer的多模态大脑网络重要区域识别方法》于2025年8月8日获得授权

论文 “Characterizing and differentiating brain states through a CS-KBRs framework for highlighting the synergy of common and specific brain regions” 在期刊《Computerized Medical Imaging and Graphics》 (CMIG) 发表

论文 “Identifying influential nodes in brain networks via self-supervised graph-transformer” 在期刊《Computers in Biology and Medicine》 (CIBM) 发表

论文 “Exploring Brain Function-Structure Connectome Skeleton via Self-Supervised Graph-Transformer Approach” 被会议MICCAI 2023接收

论文 “Joint Representation of Functional and Structural Profiles for Identifying Common and Consistent 3-Hinge Gyral Folding Landmark” 被会议MICCAI 2023接收

论文“A NOVEL MULTI-MODALITY FRAMEWORK FOR EXPLORING BRAIN CONNECTIVITY HUBS VIA REINFORCEMENT LEARNING APPROACH”被会议 “IEEE International Symposium on Biomedical Imaging”接收

论文“A hybrid learning framework for fine-grained interpretation of brain spatiotemporal patterns during naturalistic functional magnetic resonance imaging”被期刊Frontiers in Human Neuroscience接收