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检索条件"机构=Society for Medical Image Computing and Computer Assisted Intervention"
75 条 记 录,以下是1-10 订阅
REMOTE: Real-time Ego-motion Tracking for Various Endoscopes via Multimodal Visual Feature Learning
arXiv
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arXiv 2025年
作者: Shao, Liangjing Chen, Benshuang Zhao, Shuting Chen, Xinrong Academy for Engineering & Technology Fudan University China Shanghai Key Laboratory of Medical Image Computing and Computer-Assisted Intervention Fudan University China
Real-time ego-motion tracking for endoscope is a significant task for efficient navigation and robotic automation of endoscopy. In this paper, a novel framework is proposed to perform real-time ego-motion tracking for... 详细信息
来源: 评论
Exploring CLIP’s Dense Knowledge for Weakly Supervised Semantic Segmentation
arXiv
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arXiv 2025年
作者: Yang, Zhiwei Meng, Yucong Fu, Kexue Tang, Feilong Wang, Shuo Song, Zhijian Academy for Engineering and Technology Fudan University Shanghai200433 China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention China Digital Medical Research Center School of Basic Medical Sciences Fudan University China Shandong Computer Science Center National Supercomputer Center in Jinan China
Weakly Supervised Semantic Segmentation (WSSS) with image-level labels aims to achieve pixel-level predictions using Class Activation Maps (CAMs). Recently, Contrastive Language-image Pre-training (CLIP) has been intr... 详细信息
来源: 评论
DM-Mamba: Dual-domain Multi-scale Mamba for MRI Reconstruction
arXiv
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arXiv 2025年
作者: Meng, Yucong Yang, Zhiwei Song, Zhijian Shi, Yonghong Fu, Kexue Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai200032 China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai200032 China Academy of Engineering and Technology Fudan University Shanghai200433 China Jinan China
The accelerated MRI reconstruction poses a challenging ill-posed inverse problem due to the significant undersampling in k-space. Deep neural networks, such as CNNs and ViT, have shown substantial performance improvem... 详细信息
来源: 评论
Weakly Semi-supervised Whole Slide image Classification by Two-level Cross Consistency Supervision
arXiv
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arXiv 2025年
作者: Qu, Linhao Li, Shiman Luo, Xiaoyuan Liu, Shaolei Guo, Qinhao Wang, Manning Song, Zhijian Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai China Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Shanghai China Department of Gynecologic Oncology Shanghai Cancer Center Fudan University Shanghai China Department of Oncology Shanghai Medical College Fudan University Shanghai China
computer-aided Whole Slide image (WSI) classification has the potential to enhance the accuracy and efficiency of clinical pathological diagnosis. It is commonly formulated as a Multiple Instance Learning (MIL) proble... 详细信息
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DDFP: Data-dependent frequency prompt for source free domain adaptation of medical image segmentation
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Knowledge-Based Systems 2025年 324卷
作者: Siqi Yin Shaolei Liu Manning Wang Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai 200032 China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai 200032 China
Domain adaptation addresses the challenge of model performance degradation caused by domain gaps. In the typical setup for unsupervised domain adaptation, labeled data from a source domain and unlabeled data from a ta...
来源: 评论
Decoupled deep hough voting for point cloud registration
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Frontiers of computer Science 2024年 第2期18卷 147-155页
作者: Mingzhi YUAN Kexue FU Zhihao LI Manning WANG Digital Medical Research Center School of Basic Medical SciencesFudan UniversityShanghai 200032China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai 200032China
Estimating rigid transformation using noisy correspondences is critical to feature-based point cloud ***,a series of studies have attempted to combine traditional robust model fitting with deep *** them,DHVR proposed ... 详细信息
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A learnable self-supervised task for unsupervised domain adaptation on point cloud classification and segmentation
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Frontiers of computer Science 2023年 第6期17卷 147-149页
作者: Shaolei LIU Xiaoyuan LUO Kexue FU Manning WANG Zhijian SONG Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai 200032China Digital Medical Research Center School of Basic Medical ScienceFudan UniversityShanghai 200032China
1 Introduction Deep neural networks have exhibited excellent performance in supervised tasks on point clouds,such as classification,segmentation[1]and registration[2].In supervised learning schemes,manual labeling of ... 详细信息
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SS-Pro:a simplified siamese contrastive learning approach for protein surface representation
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Frontiers of computer Science 2024年 第5期18卷 243-245页
作者: Ao SHEN Mingzhi YUAN Yingfan MA Manning WANG Digital Medical Research Center School of Basic Medical ScienceFudan UniversityShanghai 200032China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai 200032China
Protein surface serves as an important representation of protein structure,revealing how protein interacts with other biomolecules to perform its *** forms the basis for pharmaceutical and fundamental biological resea... 详细信息
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An efficient dual-branch framework via implicit self-texture enhancement for arbitrary-scale histopathology image super-resolution
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Scientific Reports 2025年 第1期15卷 1-18页
作者: Minghong Duan Linhao Qu Manning Wang Chenxi Zhang Zhijian Song Zhiwei Yang Digital Medical Research Center School of Basic Medical Sciences Fudan University Shanghai 200032 China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai 200032 China Academy for Engineering and Technology Fudan University Shanghai 200433 China
High-quality whole-slide scanning is expensive, complex, and time-consuming, thus limiting the acquisition and utilization of high-resolution histopathology images in daily clinical work. Deep learning-based single-im...
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Evaluation of uncertainty estimation methods in medical image segmentation: Exploring the usage of uncertainty in clinical deployment
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computerized medical Imaging and Graphics 2025年 124卷
作者: Shiman Li Mingzhi Yuan Xiaokun Dai Chenxi Zhang Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai 200032 China Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Shanghai 200032 China Digital Medical Research Center Academy for Engineering and Technology Fudan University Shanghai 200032 China
Uncertainty estimation methods are essential for the application of artificial intelligence (AI) models in medical image segmentation, particularly in addressing reliability and feasibility challenges in clinical depl...
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