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检索条件"机构=Shanghai Key Laboratory for Medical Imaging Computing and Computer Assisted Intervention"
142 条 记 录,以下是121-130 订阅
排序:
Clomipramine inhibits microglial NLRP3 inflammasome in the hippocampus of depressive rats
Clomipramine inhibits microglial NLRP3 inflammasome in the h...
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中国解剖学会2021年年会
作者: Wang Yalin Zhang Shanshan Yue Na Liu Guixue Huang Huijie Han Qiuqin Gong Wenqing Chen Xiaorong Zhang Yaodong Yu Jin Xiao Honglei Qin Song Li Wensheng Liu Qiong Department of Integrative Medicine and Neurobiology School of Basic Medical Sciences Fudan University Department of Anatomy Histology and EmbryologySchool of Basic Medical SciencesFudan University Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Children's Hospital Affiliated to Zhengzhou University Henan Neural Development Engineering Research Center
Neuroinflammation is implicated in the pathophysiology of *** reduction of hippocampal volume in depression remains controversial because of interindividual variability in clinical ***,we studied the effects of clomip... 详细信息
来源: 评论
Separate and Conquer: Decoupling Co-occurrence via Decomposition and Representation for Weakly Supervised Semantic Segmentation
arXiv
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arXiv 2024年
作者: Yang, Zhiwei Fu, Kexue Duan, Minghong Qu, Linhao Wang, Shuo Song, Zhijian Academy for Engineering and Technology Fudan University China Digital Medical Research Center School of Basic Medical Sciences Fudan University China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention China Shandong Computer Science Center National Supercomputer Center in Jinan China
Attributed to the frequent coupling of co-occurring objects and the limited supervision from image-level labels, the challenging co-occurrence problem is widely present and leads to false activation of objects in weak... 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
key-Point Based Automated Diagnosis for Alveolar Dehiscence in Mandibular Incisors Using Convolutional Neural Network
SSRN
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SSRN 2022年
作者: Liu, Tianyu Ye, Yingzhi Liu, Chengcheng Chen, Jing Liu, Yuehua Xing, Wenyu Ta, Dean Academy for Engineering and Technology Fudan University Shanghai200433 China Department of Orthodontics Shanghai Stomatological Hospital School of Stomatology Fudan University Shanghai200001 China Shanghai Key Laboratory of Craniomaxillofacial Development and Diseases Fudan University Shanghai200001 China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai200032 China Center for Medical Engineering School of Information Science and Technology Fudan University Shanghai200438 China
The aim of this study was to propose an automated diagnosis method for alveolar dehiscence in the anterior teeth using convolutional neural network (CNN).The Cone-beam computed tomography (CBCT) scanning was performed... 详细信息
来源: 评论
Intracardiac Electrogram Signals key Feature Points Recognition Using Dense Convolutional Network
Intracardiac Electrogram Signals Key Feature Points Recognit...
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Pattern Recognition and Machine Learning (PRML), IEEE International Conference on
作者: Jiang Yihang Gu Kaihao Wu Xiaomei Department of Biomedical Engineering School of information Science and Technology Fudan University Shanghai China Department of Biomedical Engineering Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention (MICCAI) of Shanghai School of information Science and Technology Fudan University Academy for Engineering and Technology Shanghai Engineering Research Center of Assistive Devices Shanghai China Yiwu Research Institute of Fudan University Zhejiang China
During radiofrequency ablation procedures for atrial fibrillation patients, physicians can assist in locating ablation targets by analyzing the conduction pathways and low-voltage areas of the intracardiac electrogram... 详细信息
来源: 评论
Recognition of temporal lobe epilepsy based on high throughput analysis of MRI images
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Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 2016年 37卷 78-82页
作者: Lian, Yuxi Yu, Jinhua Wang, Yuanyuan Shi, Zhifeng Chen, Liang Department of Electronic Engineering Fudan University Shanghai200433 China Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Shanghai200032 China Department of Neurosurgery Huashan Hospital Fudan University Shanghai200400 China
Temporal lobe epilepsy is a usual kind of epileptic *** recognition of temporal lobe epilepsyfrom MRI (magnetic resonance imaging) images can avoid the harm of radiation generated by PET (position emission computed to... 详细信息
来源: 评论
DEEP RECURSIVE EMBEDDING FOR HIGH-DIMENSIONAL DATA
arXiv
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arXiv 2021年
作者: Zhou, Zixia Zu, Xinrui Wang, Yuanyuan Lelieveldt, Boudewijn P.F. Tao, Qian The Department of Electronic Engineering Fudan University Shanghai200433 China University of Twente Drienerlolaan 5 Enschede7522 NB Netherlands Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Shanghai200032 China The Division of Image Processing Department of Radiology Leiden University Medical Center Albinusdreef 2 Leiden2333 ZA Netherlands The Department of Imaging Physics Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands
Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this paper, we propose to combine deep neural networks (DNN) with mathematics-guided embedding rules for h... 详细信息
来源: 评论
Deep recursive embedding for high-dimensional data
arXiv
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arXiv 2021年
作者: Zhou, Zixia Wang, Yuanyuan Lelieveldt, Boudewijn P.F. Tao, Qian The Department of Electronic Engineering Fudan University Shanghai200433 China The Department of Electronic Engineering Fudan University Shanghai200433 China Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Shanghai200032 China The Division of Image Processing Department of Radiology Leiden University Medical Center Albinusdreef 2 Leiden2333 ZA Netherlands The Division of Image Processing Department of Radiology Leiden University Medical Center Albinusdreef 2 Leiden2333 ZA Netherlands
t-distributed stochastic neighbor embedding (t-SNE) is a well-established visualization method for complex high-dimensional data. However, the original t-SNE method is nonparametric, stochastic, and often cannot well ... 详细信息
来源: 评论
EndoBoost: a plug-and-play module for false positive suppression during computer-aided polyp detection in real-world colonoscopy (with dataset)
arXiv
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arXiv 2022年
作者: Wang, Haoran Zhu, Yan Qin, Wenzheng Zhang, Yizhe Zhou, Pinghong Li, Quanlin Wang, Shuo Song, Zhijian Digital Medical Research Center School of Basic Medical Sciences Fudan University Shanghai200032 China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai200032 China Endoscopy Center Endoscopy Research Institute Zhongshan Hospital Fudan University Shanghai200032 China Shanghai Collaborative Innovation Center of Endoscopy Shanghai200032 China School of Computer Science and Engineering Nanjing University of Science and Technology Jiangsu210014 China
The advance of computer-aided detection systems using deep learning opened a new scope in endoscopic image analysis. However, the learning-based models developed on closed datasets are susceptible to unknown anomalies... 详细信息
来源: 评论
Predicting Ejection Fraction from Electrocardiogram Signals using a Multi-task Learning Model
Predicting Ejection Fraction from Electrocardiogram Signals ...
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International Workshop on Wearable and Implantable Body Sensor Networks (BSN)
作者: Gaoyan Zhong Yueyi Wang Sen Liu Xintao Deng Aiguo Wang Cuiwei Yang Center for Biomedical Enginering School of Information Science and Technology Fudan Shanghai China Department of Cardiology Xinghua City People’s Hospital Jiangsu China Center for Biomedical Enginering School of Information Science and Technology Fudan The Key Laboratory of Medical Imaging Computing and Computer Assisted Intercention of Shanghai Shanghai China
The aim of this study was to investigate the feasibility and effectiveness of using electrocardiogram (ECG) signals to predict ejection fraction (EF) in an extremely imbalanced dataset. We collected ECG signals from 9...
来源: 评论