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检索条件"机构=Society for Medical Image Computing and Computer Assisted Intervention"
76 条 记 录,以下是41-50 订阅
Towards Label-efficient Automatic Diagnosis and Analysis: A Comprehensive Survey of Advanced Deep Learning-based Weakly-supervised, Semi-supervised and Self-supervised Techniques in Histopathological image Analysis
arXiv
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arXiv 2022年
作者: Qu, Linhao Liu, Siyu Liu, Xiaoyu Wang, Manning Song, Zhijian Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Shanghai200032 China
Histopathological images contain abundant phenotypic information and pathological patterns, which are the gold standards for disease diagnosis and essential for the prediction of patient prognosis and treatment outcom... 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
来源: 评论
Boosting Point-BERT by Multi-choice Tokens
arXiv
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arXiv 2022年
作者: Fu, Kexue Yuan, Mingzhi Wang, Manning Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai China
Masked language modeling (MLM) has become one of the most successful self-supervised pre-training task. Inspired by its success, Point-BERT, as a pioneer work in point cloud, proposed masked point modeling (MPM) to pr... 详细信息
来源: 评论
Reducing Domain Gap in Frequency and Spatial domain for Cross-modality Domain Adaptation on medical image Segmentation
arXiv
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arXiv 2022年
作者: Liu, Shaolei Yin, Siqi Qu, Linhao Wang, Manning Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai200032 China Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention China
Unsupervised domain adaptation (UDA) aims to learn a model trained on source domain and performs well on unlabeled target domain. In medical image segmentation field, most existing UDA methods depend on adversarial le... 详细信息
来源: 评论
FAST: a dual-tier few-shot learning paradigm for whole slide image classification  24
FAST: a dual-tier few-shot learning paradigm for whole slide...
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Proceedings of the 38th International Conference on Neural Information Processing Systems
作者: Kexue Fu Xiaoyuan Luo Linhao Qu Shuo Wang Ying Xiong Ilias Maglogiannis Longxiang Gao Manning Wang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China and Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Digital Medical Research Center School of Basic Medical Sciences Fudan University and Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Fudan University University of Piraeus
The expensive fine-grained annotation and data scarcity have become the primary obstacles for the widespread adoption of deep learning-based Whole Slide images (WSI) classification algorithms in clinical practice. Unl...
来源: 评论
OpenAL: An Efficient Deep Active Learning Framework for Open-Set Pathology image Classification
arXiv
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arXiv 2023年
作者: Qu, Linhao Ma, Yingfan Yang, Zhiwei Wang, Manning Song, Zhijian Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai200032 China Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Shanghai200032 China Academy for Engineering & Technology Fudan University Shanghai200433 China
Active learning (AL) is an effective approach to select the most informative samples to label so as to reduce the annotation cost. Existing AL methods typically work under the closed-set assumption, i.e., all classes ... 详细信息
来源: 评论
POS-BERT: Point Cloud One-Stage BERT Pre-Training
arXiv
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arXiv 2022年
作者: Fu, Kexue Gao, Peng Liu, Shaolei Zhang, Renrui Qiao, Yu Wang, Manning Digital Medical Research Center School of Basic Medical Sciences Fudan University China Shanghai AI Lab China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention China
Recently, the pre-training paradigm combining Transformer and masked language modeling has achieved tremendous success in NLP, images, and point clouds, such as BERT. However, directly extending BERT from NLP to point... 详细信息
来源: 评论
Robust Point Cloud Registration Framework Based on Deep Graph Matching(TPAMI Version)
arXiv
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arXiv 2022年
作者: Fu, Kexue Luo, Jiazheng Luo, Xiaoyuan Liu, Shaolei Zhang, Chenxi Wang, Manning The Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai200032 China The Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai200032 China
3D point cloud registration is a fundamental problem in computer vision and robotics. Recently, learning-based point cloud registration methods have made great progress. However, these methods are sensitive to outlier... 详细信息
来源: 评论
Rethinking Multiple Instance Learning for Whole Slide image Classification: A Good Instance Classifier is All You Need
arXiv
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arXiv 2023年
作者: Qu, Linhao Ma, Yingfan Luo, Xiaoyuan Guo, Qinhao Wang, Manning Song, Zhijian Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai200032 China Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Shanghai200032 China Department of Gynecologic Oncology Fudan University Shanghai Cancer Center 270 Dong-An Road Shanghai200032 China
Weakly supervised whole slide image classification is usually formulated as a multiple instance learning (MIL) problem, where each slide is treated as a bag, and the patches cut out of it are treated as instances. Exi... 详细信息
来源: 评论
A Learnable self-supervised task for unsupervised domain adaptation on point clouds
arXiv
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arXiv 2021年
作者: Luo, Xiaoyuan Liu, Shaolei Fu, Kexue Wang, Manning Song, Zhijian Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention
Deep neural networks have achieved promising performance in supervised point cloud applications, but manual annotation is extremely expensive and time-consuming in supervised learning schemes. Unsupervised domain adap... 详细信息
来源: 评论