检索结果-内蒙古大学图书馆

Decoupled deep hough voting for point cloud registration

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 a hough voting-based method,achieving new state-of-the-art ***,we find voting on rotation and translation simultaneously hinders achieving better ***,we proposed a new hough voting-based method,which decouples rotation and translation ***,we first utilize hough voting and a neural network to estimate *** based on good initialization on rotation,we can easily obtain accurate rigid *** experiments on 3DMatch and 3DLoMatch datasets show that our method achieves comparable performances over the state-of-the-art *** further demonstrate the generalization of our method by experimenting on KITTI dataset.

关键词： point cloud registration robust model fitting deep learning hough voting

来源：评论

学校读者我要写书评

暂无评论

SS-Pro:a simplified siamese contrastive learning approach for protein surface representation

引用

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 research[1].Datadriven deep learning methods in protein surface representation face challenges of label scarcity,since labeled data are typically obtained through wet lab experiments.

关键词： revealing representation simplified

来源：评论

学校读者我要写书评

暂无评论

A learnable self-supervised task for unsupervised domain adaptation on point cloud classification and segmentation

引用

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 massive point clouds is needed for model ***,point clouds captured from different scenarios exist inevitable distribution discrepancy,and model trained from one domain always generalize badly in another *** reduce the doamin distribution discrepancy,many studies[3–6]have emerged for point cloud unsupervised domain adaptation(UDA)by learning domain-invariant features,where[5]proposed using adaptive nodes to align the local features between the source and the target domains[3,4],and[6]proposed utilizing self-supervised tasks to help capture highly transferable feature representations.

关键词： point cloud utilizing

来源：评论

学校读者我要写书评

暂无评论

Typicality-and instance-dependent label noise-combating:a novel framework for simulating and combating real-world noisy labels for endoscopic polyp classification

引用

Visual computing for Industry,Biomedicine,and Art 2024年第1期7卷 300-315页

作者： Yun Gao Junhu Fu Yuanyuan Wang Yi Guo School of Information Science and Technology Fudan UniversityShanghai 200433China Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Shanghai 200433China

Learning with noisy labels aims to train neural networks with noisy *** models handle instance-inde-pendent label noise(IIN)well;however,they fall short with real-world *** medical image classification,atypical samples frequently receive incorrect labels,rendering instance-dependent label noise(IDN)an accurate representa-tion of real-world ***,the current IDN approaches fail to consider the typicality of samples,which hampers their ability to address real-world label noise *** alleviate the issues,we introduce typicality-and instance-dependent label noise(TIDN)to simulate real-world noise and establish a TIDN-combating framework to combat label ***,we use the sample’s distance to decision boundaries in the feature space to repre-sent *** TIDN is then generated according to *** establish a TIDN-attention module to combat label noise and learn the transition matrix from latent ground truth to the observed noisy labels.A recursive algorithm that enables the network to make correct predictions with corrections from the learned transition matrix is *** experiments demonstrate that the TIDN simulates real-world noise more closely than the existing IIN and ***,the TIDN-combating framework demonstrates superior classification performance when training with simulated TIDN and actual real-world noise.

关键词： Noisy label Instance-dependent label noise Noisy label simulation Real-world label noise Polyp classification

来源：评论

学校读者我要写书评

暂无评论

NETrack: A Lightweight Attention-Based Network for Real-Time Pose Tracking of Nasal Endoscope Based on Endoscopic image 21st

NETrack: A Lightweight Attention-Based Network for Real-Tim...

引用

21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Shao, Liangjing Chen, Benshuang Chen, Xinrong Academy for Engineering and Technology Fudan University Shanghai200438 China Shanghai Key Laboratory for Medical Imaging Computing and Computer Assisted Intervention Fudan University Shanghai200032 China

ISBN: (纸本)9789819601271

Vision-based real-time pose tracking of endoscope is significant for navigation and automation of endoscopy. In this work, a deep learning-based framework is proposed for vision-based real-time pose tracking of nasal endoscope based on endoscopic images. Specifically, an attention-based module is introduced into the feature encoder to extract and integrate multi-dimensional and multi-scale information. Furthermore, a novel pose encoder is proposed to extract more complicated representation from the feature map for pose vector prediction. The proposed method is compared with state-of-the-art methods on the dataset, which consists of endoscopic videos and endoscope poses obtaining by an optical tracking system. The experimental results demonstrate that the proposed network achieves better performance than state-of-the-art works for real-time nasal endoscope pose estimation. The average tracking error of our method is 5.78 mm, while the relative translation error and rotation error are respectively 0.48 mm and 0.22 degree on average. In addition, the average inference speed of our network is 46 fps, which achieves the real-time requirement. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Endoscopy

来源：评论

学校读者我要写书评

暂无评论

Dual Attention Poser: Dual Path Body Tracking Based on Attention

Dual Attention Poser: Dual Path Body Tracking Based on Atten...

引用

2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Di, Xinhan Dai, Xiaokun Zhang, Xinkang Chen, Xinrong Fudan Universiry Academy for Engineering&Technology China Deepearthgo Fudan University Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention China

ISBN: (纸本)9798350302493

Currently, mixed reality head-mounted displays tracking the full body of users is an important human-computer interaction mode through the pose of the head and the hands. Unfortunately, users' virtual representation and experience is limited due to high reconstruction error when simple transformer network architecture is applied. In this paper, we present a novel model, named Dual Attention Poser, which can learn the whole body reconstruction at a high accuracy. The proposed model consists of three key modules. Among them, dual-path attention encoder is designed to extract feature of the sparse signals. Cross attention mixer module enable the fusion of representation in the double path. Attention-gated-mlp decoder is applied to decode the hidden feature from the sparse input through attention gate. Test results on the AMASS dataset show that Dual Attention Poser can reduce the error by up to 18.2% in comparison with the state-of-the-art results. © 2023 IEEE.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Forebrain excitatory neuron-specific loss of Brpf1 attenuates excitatory synaptic transmission and impairs spatial and fear memory

引用

Neural Regeneration Research 2024年第5期19卷 1133-1141页

作者： Baicheng Zhao Hang Zhang Ying Liu Gaoyu Zu Yuxiao Zhang Jiayi Hu Shuai Liu Linya You Department of Human Anatomy&Histoembryology School of Basic Medical SciencesFudan UniversityShanghaiChina Shanghai Key Laboratory of Brain Functional Genomics(Ministry of Education) Affiliated Mental Health Center(ECNU)School of Psychology and Cognitive ScienceEast China Normal UniversityShanghaiChina Shanghai Changning Mental Health Center ShanghaiChina NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai ShanghaiChina Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai ShanghaiChina

Bromodomain and plant homeodomain(PHD)finger containing protein 1(Brpf1)is an activator and scaffold protein of a multiunit complex that includes other components involving lysine acetyltransferase(KAT)6A/6B/***1,KAT6A,and KAT6B mutations were identified as the causal genes of neurodevelopmental disorders leading to intellectual *** previous work revealed strong and specific expression of Brpf1 in both the postnatal and adult forebrain,especially the hippocampus,which has essential roles in learning and ***,we hypothesized that Brpf1 plays critical roles in the function of forebrain excitatory neurons,and that its deficiency leads to learning and memory *** test this,we knocked out Brpf1 in forebrain excitatory neurons using *** found that Brpf1 deficiency reduced the frequency of miniature excitatory postsynaptic currents and downregulated the expression of genes Pcdhgb1,Slc16a7,Robo3,and Rho,which are related to neural development,synapse function,and memory,thereby damaging spatial and fear memory in *** findings help explain the mechanisms of intellectual impairment in patients with BRPF1 mutation.

关键词： behavioral test Brpf1 CAMKIIa-Cre intellectual disability miniature excitatory postsynaptic current mRNA-Seq

来源：评论

学校读者我要写书评

暂无评论

Diffusion Model with Self-supervised Training for Subject-aware Photoplethysmography Recovery

Diffusion Model with Self-supervised Training for Subject-aw...

引用

2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023

作者： Wang, Daomiao Hu, Qihan Feng, Xujian Yang, Cuiwei Fudan University Center for Biomedical Engineering School of Information Science and Technology Shanghai China Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Shanghai China

ISBN: (纸本)9798350300260

Photoplethysmography (PPG) has emerged as a promising technology for wearable personal healthcare due to its non-invasive and cost-effective nature. However, owing to the vulnerability to various noise, the useful PPG signals are few and the usability of PPG-based systems are limited. In this paper, we address the challenge of recovering extremely corrupted PPG waveforms with severe distortions, which lead to missing data. Specifically, we propose a novel diffusion-based framework that incorporates remaining values and subject-aware embedding, along with a self-supervised generative training strategy. Extensive experiments were performed on two datasets under three missing rates and two missing patterns. Our proposed model achieves significant improvements of nearly 100% over existing imputation models on quantitative metrics, and together with the visualization, demonstrating its effectiveness for data distribution generation and corrupted PPG restoration. Our proposed method also provides a new perspective for PPG denoising. © 2023 IEEE.

关键词： Deep generative model Diffusion model Motion artifact Photoplethysmography Self-supervised training

来源：评论

学校读者我要写书评

暂无评论

A Contrast-Enhanced Null Subtraction Imaging Method using Dynamic DC Bias in Ultrafast Ultrasound imaging

引用

IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 2025年第6期72卷 755-771页

作者： Yan, Xin Yang, Xiaodong Jing, Lingling Guo, Wei Wang, Yingqi Su, Xinwei Wang, Yuanyuan Shenyang University of Technology School of Information Science and Engineering Shenyang110870 China Ultrasound Department of Anshan Central Hospital Anshan114000 China CO. Ltd Suzhou215123 China Fudan University Department of Electronic Engineering and the Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Shanghai200433 China

Enhancing the resolution and contrast of ultrafast ultrasound imaging is imperative for the accuracy of clinical diagnostics. Null subtraction imaging (NSI) is a nonlinear beamforming technique capable of significantly enhancing lateral resolution. However, it suffers from issues of low-quality speckle pattern and poor contrast performance. To address this issue, we propose a novel contrast-enhanced NSI method that utilizes dynamic DC bias. Innovatively, we construct the dynamic DC bias using a generalized coherence factor (GCF) and a sigmoid transformation function that adapts the DC value based on the signal characteristics of different imaging regions. Furthermore, a normalization scheme is proposed to optimize the beamforming output, ensuring uniform pixel intensity throughout the final image. Simulation, phantom, and in vivo data are utilized for ultrasound beamforming to evaluate the performance of the proposed method. Quantitative results show that the proposed method significantly enhances the contrast ratio (CR) by 197%, the contrast-to-noise ratio (CNR) by 341%, the speckle signal-to-noise ratio (sSNR) by 302%, and the generalized contrast-to-noise ratio (gCNR) by 106% compared to the original NSI (in phantom). Point target imaging results indicate that the proposed method achieves a main lobe width slightly wider than the original NSI method, but much narrower than those of DAS and GCF. These findings confirm that the proposed method significantly enhances imaging contrast while preserving high resolution, which is of great significance for the further clinical application of ultrafast ultrasound imaging. © 1986-2012 IEEE.

关键词： Phantoms

来源：评论

学校读者我要写书评

暂无评论

IMAGGS: a radiogenomic framework for identifying multi-way associations in breast cancer subtypes

引用

Journal of Genetics and Genomics 2024年第4期51卷 443-453页

作者： Shuyu Liang Sicheng Xu Shichong Zhou Cai Chang Zhiming Shao Yuanyuan Wang Sheng Chen Yunxia Huang Yi Guo Department of Electronic Engineering School of Information Science and TechnologyFudan UniversityShanghai 200433China The Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention(MICCAI)of Shanghai Shanghai 200032China Shanghai Key Laboratory of Metabolic Remodeling and Health Institute of Metabolism and Integrative BiologyFudan UniversityShanghai 200433China Department of Ultrasound Fudan University Shanghai Cancer CenterDepartment of OncologyShanghai Medical CollegeFudan UniversityShanghai 200032China Department of Breast Surgery Fudan University Shanghai Cancer CenterDepartment of OncologyShanghai Medical CollegeFudan UniversityShanghai 200032China

Investigating correlations between radiomic and genomic profiling in breast cancer(BC)molecular subtypes is crucial for understanding disease mechanisms and providing personalized *** present a well-designed radiogenomic framework image–gene–gene set(IMAGGS),which detects multi-way associations in BC subtypes by integrating radiomic and genomic *** dataset consists of 721 patients,each of whom has 12 ultrasound(US)images captured from different angles and gene mutation *** better characterize tumor traits,12 multi-angle US images are fused using two distinct ***,we analyze complex many-to-many associations between phenotypic and genotypic features using a machine learning algorithm,deviating from the prevalent one-to-one relationship pattern observed in previous *** radiomic and genomic features are screened using these *** addition,gene set enrichment analysis is performed to investigate the joint effects of gene sets and delve deeper into the biological functions of BC *** further validate the feasibility of IMAGGS in a glioblastoma multiforme dataset to demonstrate the scalability of IMAGGS across different modalities and *** together,IMAGGS provides a comprehensive characterization for diseases by associating imaging,genes,and gene sets,paving the way for biological interpretation of radiomics and development of targeted therapy.

关键词： IMAGGS Radiogenomic framework "lmage-gene-geneset"associations Molecular subtypes Breast cancer

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：