检索结果-内蒙古大学图书馆

Changes in brain functional network connectivity after stroke

Neural Regeneration Research 2014年第1期9卷 51-60页

作者： Wei Li Yapeng Li Wenzhen Zhu Xi Chen Key Laboratory of Image Processing and Intelligent Control Ministry of Education Department of Control Science and Engineering Huazhong University of Science and Technology Department of Radiology Tongji HospitalTongji Medical CollegeHuazhong University of Science and Technology

Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.

关键词： nerve regeneration brain injury stroke motor areas functional magnetic resonanceimaging brain network independent component analysis functional network connectivity neuralplasticity NSFC grant neural regeneration

来源：评论

学校读者我要写书评

暂无评论

A NOVEL CONVOLUTIONAL NEURAL NETWORK BASED ON ADAPTIVE MULTI-SCALE AGGREGATION AND BOUNDARY-AWARE FOR LATERAL VENTRICLE SEGMENTATION ON MR imageS 47

A NOVEL CONVOLUTIONAL NEURAL NETWORK BASED ON ADAPTIVE MULTI...

引用

2022 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2022

作者： Ye, Fei Wang, Zhiqiang Zhu, Sheng Li, Xuanya Hu, Kai Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan411105 China Department of Radiology Affiliated Hospital of Xiangnan University Chenzhou423000 China Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province Xiangnan University Chenzhou423000 China Baidu Inc. Beijing100085 China

ISBN: (纸本)9781665405409

In this paper, we propose a novel convolutional neural network based on adaptive multi-scale feature aggregation and boundary-aware for lateral ventricle segmentation (MB-Net), which mainly includes three parts, i.e., an adaptive multi-scale feature aggregation module (AMSFM), an embedded boundary refinement module (EBRM), and a local feature extraction module (LFM). Specifically, the AMSFM is used to extract multi-scale features through the different receptive fields to effectively solve the problem of distinct target regions on magnetic resonance (MR) images. The EBRM is intended to extract boundary information to effectively solve blurred boundary problems. The LFM can make the extraction of local information based on spatial and channel attention mechanisms to solve the problem of irregular shapes. Finally, extensive experiments are conducted from different perspectives to evaluate the performance of the proposed MB-Net. Furthermore, we also verify the robustness of the model on other public datasets, i.e., COVID-SemiSeg and CHASE DB1. The results show that our MB-Net can achieve competitive results when compared with state-of-the-art methods. © 2022 IEEE

关键词： Magnetic resonance

来源：评论

学校读者我要写书评

暂无评论

The Design and Development of Computer Network Quality Course Website

The Design and Development of Computer Network Quality Cours...

引用

2010 2nd International Conference on Education Technology and Computer(第二届IEEE教育技术与计算机国际会议 ICETC 2010)

作者： Yu Yao Yong Li Wei Yang Fu-xiang Gao Key Laboratory of Medical Image Computing (Northeastern University) Ministry of EducationSchool of Key Laboratory of Medical Image Computing (Northeastern University) Ministry of Education School o School of Software Northeastern University Shenyang China School of Information Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9781424463671;9781424463688;9781424463701

During the construction of computer network quality course to improve the quality of computer network course, the paper designs and develops the computer network quality course website. The development of the website is based on B/S architecture and MVC design pattern and adopts the Struts framework. The website is enough to incarnate the user-centered development idea and provides an excellent intercourse platform for teachers and students. The paper shows the design of the website function modules, and specifically describes the development of main function modules and the update and maintenance of the website.

关键词： quality courses website design computer network MVC

来源：评论

学校读者我要写书评

暂无评论

An Unsupervised Domain Adaptation Model Based on Multi-Level Joint Alignment for Multi-Modal Cardiac image Segmentation

引用

Procedia Computer Science 2023年 226卷 106-112页

作者： Jiapeng Li Yimou Lv Lisheng Xu Lin Qi College of Medicine and Biological Information Engineering Northeastern University Shenyang 110169 China Engineering Research Center of Medical Imaging and Intelligent Analysis Ministry of Education Shenyang 110169 China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University Shenyang 110169 China

Unsupervised Domain Adaptation has greatly boosted the performance of multi-modal medical segmentation when there are only source domain labels and no labels in the target domain. Many previous work relies on Convolutional Neural Networks for distribution or instance alignment, however, the receptive field of CNN makes it overly concerned with texture and local semantic information of images, while losing the global style information and semantic information and lacking relationships between local and global semantics. In order to address these issues, we propose a two-stage, multi-level framework for unsupervised domain adaptation, which consists of an image translation network and a Transformer-based domain adaptation segmentation network, jointly aligning the data distribution in the source and target domains from the image, feature and output level through adversarial learning. Experimental results indicate that our method can achieve satisfactory results and outperform other state-of-the-art medical image segmentation methods.

关键词： Unsupervised domain adaptation Cardiac image segmentation Adversarial learning Multi-modal segmentation

来源：评论

学校读者我要写书评

暂无评论

Indoor Multi-Anchor Collaborative Localization for Unmanned Systems

Indoor Multi-Anchor Collaborative Localization for Unmanned ...

引用

IEEE International Conference on Robotics and Biomimetics

作者： Beijia Tai Yangjie Wei Guangyu Zhang Yuqing He Siyao Cui Key Laboratory of Intelligent Computing in Medical Image Ministry of Education College of Computer Science and Engineering Northeastern University Shenyang China Shenyang Institute of Automation Chinese Academy of Science Shenyang China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Accurate tracking of unmanned devices is essen-tial for higher-level decision-making in collaborative confrontation scenarios. However, the robustness of current positioning methods based on Ultra-Wideband (UWB) is limit, and the positioning error is unstable. This paper presents a collabo-rative localization algorithm specifically designed for indoor unmanned systems, which leverages UWB technology combined with Least Squares (LS) and Extended Kalman Filter (EKF) models to achieve anchor calibration, as well as precise and stable positioning of unmanned devices. First, the positions of anchors is estimated using fixed-point ranging information; Second, the positions of anchors are simultaneously corrected while locating the tags on unmanned devices. The experimental results show that our algorithm achieves positioning accuracy within 10 cm in the three-dimensional space, even with a ranging error of 5 cm.

关键词： Location awareness Accuracy Three-dimensional displays Autonomous systems Collaboration Distance measurement Robustness Calibration Robots Ultra wideband technology

来源：评论

学校读者我要写书评

暂无评论

Automated detection of suspected lung nodules in CT images using improved surface normal overlap algorithm

引用

Journal of Computational Information Systems 2012年第12期8卷 5111-5118页

作者： Luan, Guoxin Wei, Ying Xue, Dingyu School of Information Science and Engineering Northeastern University Shenyang 110004 China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University China

An improved surface normal overlap algorithm based on local 3-D shape constraints and surface decisionmaking projection is proposed for detect suspected pulmonary nodules in this paper. The method consists of several steps. First, anti-geometric diffusion is used as a preprocessing step. Then original region of interests in pulmonary parenchyma is segmented with adaptive threshold method. Shape index geometric feature is calculated for each voxel within the ROI. Voxel surface normal of original ROI is constrained in the surface decision-making projection. Last suspected lung nodules can be detected with local maximum method. Experiment results indicate that the improved algorithm has the ability of sphere selection, could detect both solid nodules and Ground-Glass nodules. The improved algorithm could detect suspected pulmonary nodules effectively, and has higher sensitivity. © 2012 Binary Information Press.

关键词： Computerized tomography

来源：评论

学校读者我要写书评

暂无评论

Incorporating dynamic attention gating mechanism and pre-trained embedding for Chinese clinical named entity recognition

引用

Procedia Computer Science 2023年 226卷 113-119页

作者： Zhenming Qiu Anyu Pan Lin Qi College of Medicine and Biological Information Engineering Northeastern University Shenyang 110169 China Engineering Research Center of Medical Imaging and Intelligent Analysis Ministry of Education Shenyang 110169 China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University Shenyang 110169 China

Clinical Named Entity Recognition (CNER) serves as a cornerstone in clinical research and healthcare informatics, with its primary goal being the discernment and categorization of clinical terminologies present within Electronic medical Records (EMRs). While deep learning has significantly improved CNER's performance, these models still face challenges in identifying rare or unseen entities. Our study unveils an innovative DAGM-BiLSTM-CRF model that seamlessly integrates data-driven deep learning strategies with human knowledge to surmount this limitation. The distinctive features of this model lie in its integration of a pre-trained character embedding layer, adept at encapsulating nuanced semantic variations at the granularity of individual characters. Furthermore, it incorporates a bidirectional Long Short-Term Memory (BiLSTM) layer, proficient in deriving contextually relevant information by traversing the sequence from both endpoints. The most noteworthy aspect of our model is the inclusion of a Dynamic Attention Gating Mechanism (DAGM) that dynamically recalibrates attention weights based on the traits of the input sequence and a Conditional Random Fields (CRF) layer that considers interdependencies among output labels within a sequence. The evaluation was carried out on the CCKS-2017 CNER benchmark dataset to underscore the superiority of our model over existing cutting-edge methods, thereby validating its proficiency in deciphering the intricacies of Chinese electronic medical records.

关键词： Clinical named entity recognition deep learning dynamic attention gating mechanism

来源：评论

学校读者我要写书评

暂无评论

Discrete-Time Simulation Method for Worm Propagation Model with Pulse Quarantine Strategy

引用

Procedia Engineering 2011年 15卷 4162-4167页

作者： Yu Yao Hao Guo Ge Yu Fu-xiang Gao Key Laboratory of Medical Image Computing (Ministry of Education) Northeastern University Shenyang 110819 China School of Information Science and Engineering Northeastern University Shengyang 110819 China

In this paper, discrete-time simulation method for worm propagation model with pulse quarantine strategy is proposed. Such method is firstly applied to traditional Kermack-Mckendrick model and is verified to be effective. Then, considering practical factors, worm propagation model with pulse quarantine strategy is simulated in the method. Through the comparison between numerical curves and simulation ones, discrete-time simulation method can well simulate worm propagation under pulse quarantine strategy. Finally, the algorithm of the method is given and analyzed.

关键词： Worm propagation model with pulse quarantine strategy Discrete-time simulation Algorithm

来源：评论

学校读者我要写书评

暂无评论

CAB: Empathetic Dialogue Generation with Cognition, Affection and Behavior

arXiv

引用

arXiv 2023年

作者： Gao, Pan Han, Donghong Zhou, Rui Zhang, Xuejiao Wang, Zikun School of Computer Science and Engineering Northeastern University Shenyang China Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education Northeastern University Shenyang China Swinburne University of Technology Australia

Empathy is an important characteristic to be considered when building a more intelligent and humanized dialogue agent. However, existing methods did not fully comprehend empathy as a complex process involving three aspects: cognition, affection and behavior. In this paper, we propose CAB, a novel framework that takes a comprehensive perspective of cognition, affection and behavior to generate empathetic responses. For cognition, we build paths between critical keywords in the dialogue by leveraging external knowledge. This is because keywords in a dialogue are the core of sentences. Building the logic relationship between keywords, which is overlooked by the majority of existing works, can improve the understanding of keywords and contextual logic, thus enhance the cognitive ability. For affection, we capture the emotional dependencies with dual latent variables that contain both interlocutors’ emotions. The reason is that considering both interlocutors’ emotions simultaneously helps to learn the emotional dependencies. For behavior, we use appropriate dialogue acts to guide the dialogue generation to enhance the empathy expression. Extensive experiments demonstrate that our multi-perspective model outperforms the state-of-the-art models in both automatic and manual evaluation. © 2023, CC BY.

关键词： Knowledge management

来源：评论

学校读者我要写书评

暂无评论

Vulnerability Analysis for Network Connectivity: A Prioritizing Critical Area Approach

Vulnerability Analysis for Network Connectivity: A Prioritiz...

引用

GLOBECOM 2020 - 2020 IEEE Global Communications Conference

作者： Shumei Liu Yao Yu Lei Guo Phee Lep Yeoh Branka Vucetic Yonghui Li Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang China School of Electrical and Information Engineering University of Sydney Australia Chongqing University of Posts and Telecommunications China

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

Analyzing network vulnerability, especially connectivity vulnerability, is vital for network security planning. Traditionally, network vulnerability analysis methods separate the studies of global connectivity vulnerability and critical area vulnerability, and thus ignore joint failure of network connectivity and critical-area integrity that may cause grave damage to a network. To this end, this paper proposes a prioritizing critical area approach for connectivity analysis to identify the corresponding vulnerable elements. Specifically, we consider the worst-case scenario of a network and aim at finding the minimum disruption-cost set of elements whose removal not only severely damages network connectivity but also disrupts the critical-area integrity. Since the above optimization problem is NP-hard, a heuristic algorithm based on spectral partitioning is developed to solve it. Simulation results validate the effectiveness of our proposed scheme in accurately identifying the vulnerable elements in critical areas to prevent significant loss in the overall network connectivity and performance.

关键词： Measurement Simulation Planning Partitioning algorithms Security Communication networks Optimization

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

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

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

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

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：