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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Rui Wang Wanli Yang Kuntao Xiao Yi Sun Shurong Sheng Zhao Lv Jiahong Gao Auhui University Hefei China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Anhui Province Key Laboratory of Multimodal Cognitive Computation Hefei China Center for MRI Research Academy for Advanced Interdisciplinary Studies Peking University Beijing China Beijing City Key Lab for Medical Physics and Engineering Institute of Heavy Ion PhysicsSchool of Physics Peking University Beijing China McGovern Institute for BrainResearch Peking University Beijing China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Anatomical landmark detection, a pivotal research area in medical image processing, holds immense value in surgical navigation, image registration, and related fields. Traditional machine learning methods struggle with generalization and robustness. Current supervised end-to-end approaches lacks in-terpretability in capturing global information, and GPU memory constraints restrict their application to extensive 3D medical image datasets. Moreover, existing methods overlook intrinsic geometric cues within images and point sets. Herein, we introduce a novel anatomical landmark detection framework that integrates deep learning’s representation capabilities with global geometric information derived from images and point sets (DL2G). This approach facilitates anatomical landmark localization in a local-to-global fashion. Initially, we train a deep feature descriptor based on self-supervised contrastive learning, which is further used to screen candidate points for the target one by comparing local patch embeddings. Subsequently, geometric constraints constructed from labeled template point sets enable the selection of geometrically consistent matching point sets. Ultimately, the framework utilizes the global mutual information of images to perform landmark localization through iterative optimization. Adhering to the AFID data annotation protocol, we evaluated our method on two public MRI head datasets, OASIS and HCP, for detecting 32 anatomical landmarks. The results convincingly demonstrate the superiority of our method over current state-of-the-art approaches in terms of both accuracy and computational efficiency.

关键词： Location awareness Three-dimensional displays Protocols Navigation Memory management Surgery Feature extraction Robustness Optimization Mutual information

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FireMatch: A Semi-Supervised Video Fire Detection Network Based on Consistency and Distribution Alignment

arXiv

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arXiv 2023年

作者： Lin, Qinghua Li, Zuoyong Zeng, Kun Fan, Haoyi Li, Wei Zhou, Xiaoguang School of Computer Science and Mathematics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China School of Automation Beijing University of Post and Telecommunications Beijing100876 China School of Economics and Management Minjiang University Fuzhou350121 China

Deep learning techniques have greatly enhanced the performance of fire detection in videos. However, video-based fire detection models heavily rely on labeled data, and the process of data labeling is particularly costly and time-consuming, especially when dealing with videos. Considering the limited quantity of labeled video data, we propose a semi-supervised fire detection model called FireMatch, which is based on consistency regularization and adversarial distribution alignment. Specifically, we first combine consistency regularization with pseudo-label. For unlabeled data, we design video data augmentation to obtain corresponding weakly augmented and strongly augmented samples. The proposed model predicts weakly augmented samples and retains pseudo-label above a threshold, while training on strongly augmented samples to predict these pseudo-labels for learning more robust feature representations. Secondly, we generate video cross-set augmented samples by adversarial distribution alignment to expand the training data and alleviate the decline in classification performance caused by insufficient labeled data. Finally, we introduce a fairness loss to help the model produce diverse predictions for input samples, thereby addressing the issue of high confidence with the non-fire class in fire classification scenarios. The FireMatch achieved an accuracy of 76.92% and 91.81% on two real-world fire datasets, respectively. The experimental results demonstrate that the proposed method outperforms the current state-of-the-art semi-supervised classification methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Fires

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Design and Visual Servoing control of a Hybrid Dual-Segment Flexible Neurosurgical Robot for Intraventricular Biopsy

Design and Visual Servoing Control of a Hybrid Dual-Segment ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jian Chen Mingcong Chen Qingxiang Zhao Shuai Wang Yihe Wang Ying Xiao Jian Hu Danny Tat Ming Chan Kam Tong Leo Yeung David Yuen Chung Chan Hongbin Liu School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences (CASIA) Beijing China Centre of AI and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences (CAIR-HKISI-CAS) HKSAR Department of Biomedical Engineering City University of Hong Kong HKSAR CAIR-HKISI-CAS HKSAR State Key Laboratory of Multimodal Artificial Intelligence Systems CASIA Beijing China Department of Surgery The Chinese University of Hong Kong HKSAR State Key Laboratory of Management and Control for Complex Systems CASIA Beijing China School of Biomedical Engineering and Imaging Sciences King’s College London London UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Traditional rigid endoscopes have challenges in flexibly treating tumors located deep in the brain, and low operability and fixed viewing angles limit its development. This study introduces a novel dual-segment flexible robotic endoscope MicroNeuro, designed to perform biopsies with dexterous surgical manipulation deep in the brain. Taking into account the uncertainty of the control model, an image-based visual servoing with online robot Jacobian estimation has been implemented to enhance motion accuracy. Furthermore, the application of model predictive control with constraints significantly bolsters the flexible robot’s ability to adaptively track mobile objects and resist external interference. Experimental results underscore that the proposed control system enhances motion stability and precision. Phantom testing substantiates its considerable potential for deployment in neurosurgery.

关键词： Jacobian matrices Visualization Endoscopes Estimation Interference Predictive models control systems

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A nonlinear impulsive control system with impulse time windows and un-fixed coefficient of impulsive intensity

A nonlinear impulsive control system with impulse time windo...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Yuming Feng Zitao Wang Xiaoyu Liu Wei Zhang Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology Chongqing Three Gorges University Wanzhou Chongqing China School of Computer Science and Engineering Chongqing Three Gorges University Wanzhou Chongqing China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing China School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China

ISBN: (数字)9781728158570

ISBN: (纸本)9781728158587

Based on the fact that there always exists error in the impulsive intensity, which leads to the fact that the coefficient is un-fixed, and in the occurrence of the impulses, we propose a new model, which is called nonlinear impulsive control system with impulse time windows and un-fixed coefficient of impulsive intensity. We find sufficient conditions for ensuring its stability by using Lypunov's method. We choose chaotic Lorenz system and Chua's system as numerical examples to show the effectiveness of the results, by employing such method, the systems are controlled.

关键词： Impulsive control system impulse time windows impulsive intensity stability control systems Impulsiveness Pulses Time windows

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Optimal Fault Detection Observer Design using Excluding Degree

Optimal Fault Detection Observer Design using Excluding Degr...

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IEEE Conference on Decision and control

作者： Feng Xu Yiming Wan Ye Wang Division of Information Science and Technology Shenzhen International Graduate School Tsinghua University Shenzhen P.R. China School of Artificial Intelligence and Automation Huazhong University of Science and Technology and Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan P.R. China Department of Electrical and Electronic Engineering The University of Melbourne Parkville VIC Australia

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper proposes a novel optimal gain design method for robust fault detection using set-valued observers. First, a new fault detection performance specification is proposed for set-valued observers based on a new notion named the excluding degree of the origin from a zonotope. Second, a fractional programming problem is formulated to describe fault detection optimality of set-valued observers. Third, optimal fault detection gains are obtained by solving the fractional programming problem. Finally, numerical examples are used to illustrate the effectiveness of the proposed method.

关键词： Fault detection Design methodology Observers Programming Computational complexity Optimization Numerical stability

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Determination of Pattern Recognition Problems based on a Pythagorean Fuzzy Correlation Measure from Statistical Viewpoint

Determination of Pattern Recognition Problems based on a Pyt...

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International Workshop on Advanced Computational intelligence (IWACI)

作者： Paul Augustine Ejegwa Yuming Feng Shiping Wen Wei Zhang Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing China School of Computer Science and Engineering Chongqing Three Gorges University Wanzhou Chongqing China Australian AI Institute University of Technology Sydney Ultimo Australia School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China

By considering all the three parameters describing Pythagorean fuzzy set, we introduce a new technique of computing correlation coefficient between Pythagorean fuzzy sets from statistical perspective. The correlation coefficient value obtain via this technique shows strength of correlation between the Pythagorean fuzzy sets and indicates whether the Pythagorean fuzzy sets under consideration are related negatively or positively in contrast to other existing correlation coefficient approaches in Pythagorean fuzzy context, which only assess the strength of relationship. Certain numerical examples are considered to ascertain the authenticity of this method over similar techniques studied in intuitionistic/Pythagorean fuzzy contexts. Some pattern recognition problems are resolved with the aid of the new technique. For higher productivity sake, this technique could be approached from an object-oriented perspective.

关键词： Correlation coefficient Productivity Fuzzy sets Correlation Uncertainty Pattern recognition Performance analysis

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control Selection Based on State Change of Chaotic System

Control Selection Based on State Change of Chaotic System

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International Conference on Computer and Communications (ICCC)

作者： Jiaxi Zhou Wei Zhang Yuming Feng B. O. Onasanya School of Electronics and Information Engineering Chongqing Three Gorges University Wanzhou Chongqing China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing China School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China Department of Mathematics University of Ibadan Ibadan Oyo State Nigeria

Considering that the system may need to meet more needs in the control process, that is, to accelerate or slow down the control intensity according to the system state, the control mode that combines the control cycle and the control method has a wider range of applications. In this paper, the model for state detection and judgment in the second half of the control cycle is studied, and appropriate measures are taken to achieve various control effects of the system. The simulation of the application example illustrates the effectiveness of the controller.

关键词： Analytical models Chaotic communication Process control control systems Numerical models Optimization

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Automated Detection of Epileptic Spikes and Seizures Incorporating a Novel Spatial Clustering Prior

Automated Detection of Epileptic Spikes and Seizures Incorpo...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Hanyang Dong Shurong Sheng Xiongfei Wang Jia-Hong Gao Yi Sun Wanli Yang Kuntao Xiao Pengfei Teng Guoming Luan Zhao Lv School of Artificial Intelligence Anhui University Hefei China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Department of Neurosurgery Beijing Key Laboratory of Epilepsy Sanbo Brain Hospital Capital Medical University Beijing China McGovern Institute for Brain Research Peking University Beijing China Center for MRI Research Academy for Advanced Interdisciplinary Studies Peking University Beijing China Beijing City Key Lab for Medical Physics and Engineering Institute of Heavy Ion Physics School of Physics Peking University Beijing China Anhui Province Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

A Magnetoencephalography (MEG) time-series recording consists of multi-channel signals collected by superconducting sensors, with each signal’s intensity reflecting magnetic field changes over time at the sensor location. Automating epileptic MEG spike detection significantly reduces manual assessment time and effort, yielding substantial clinical benefits. Existing research addresses MEG spike detection by encoding neural network inputs with signals from all channel within a time segment, followed by classification. However, these methods overlook simultaneous spiking occurred from nearby sensors. We introduce a simple yet effective paradigm that first clusters MEG channels based on their sensor’s spatial position. Next, a novel convolutional input module is designed to integrate the spatial clustering and temporal changes of the signals. This module is fed into a custom MEEG-ResNet3D developed by the authors, which learns to extract relevant features and classify the input as a spike clip or not. Our method achieves an F1 score of 94.73% on a large real-world MEG dataset Sanbo-CMR collected from two centers, outperforming state-of-the-art approaches by 1.85%. Moreover, it demonstrates efficacy and stability in the Electroencephalographic (EEG) seizure detection task, yielding an improved weighted F1 score of 1.4% compared to current state-of-the-art techniques evaluated on TUSZ, whch is the largest EEG seizure dataset.

关键词： Convolution Magnetic sensors Neural networks Magnetoencephalography Manuals Feature extraction Electroencephalography Encoding Recording Magnetic fields

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Micro Channel for Analyzing Mechanical Adaption of Cancer Cell

Micro Channel for Analyzing Mechanical Adaption of Cancer Ce...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Pengyun Li Xiaoming Liu Xiaoqing Tang Masaru Kojima Jian Huang Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and the Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Osaka University 1-3 Machikaneyama Toyonaka Osaka Japan Key Laboratory of Ministry of Education for Image Processing and Intelligent Control the School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781728150734

ISBN: (纸本)9781728150741

It was reported that cancer cells could biologically respond and adapt to the confined environment during migration in extracellular matrix (ECM). But it is not clearly studied that how cancer cells respond and adapt to confined environment in mechanical way. Thus, in this study, we designed and fabricated a kind of one-layer micro channel to mimic confined environment for analyzing mechanical adaption of cell. This micro channel could apply sequential mechanical stresses on a number of cells with high throughput, and the time of cells passing through five rows of micro channels were used to evaluate their adaptability to the sequential and confined space. In experiments, each cell suffered 20 times of mechanical stresses after passing through 20 squeezing channels arranged in 5 rows. We observed the sequential squeezing processes under microscope and investigated the passing time using a high-speed camera. The preliminary results indicated that cancer cells could pass through and adapt to the confined environment faster than normal cells.

关键词：

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猕猴脑网络组图谱:包含分区、连接和组织学的多层面全新大脑地图

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Science Bulletin 2024年第14期69卷 2241-2259页

作者：陆玉恒崔玥曹龙董振伟程禄祺吴雯王昌硕刘新异刘有通张宝贵李德莹赵舶凯王海艳李开心马亮时维阳李雯马亚伟杜宗昌张佳琪熊辉罗娜刘妍妍侯肖逍韩景路孙洪吉蔡涛彭强冯琳清王骄健 George Paxinos 杨正宜樊令仲蒋田仔 Brainnetome Center Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China Henan Key Laboratory of Imaging and Intelligent Processing PLA Strategic Support Force Information Engineering UniversityZhengzhou 450001China Neuroscience Research Australia and The University of New South Wales Sydney NSW 2031Australia Key Laboratory for NeuroInformation of the Ministry of Education School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengdu 610054China State Key Laboratory of Primate Biomedical Research Institute of Primate Translational MedicineKunming University of Science and TechnologyKunming 650500China School of Mechanical and Power Engineering Harbin University of Science and TechnologyHarbin 150080China School of Life and Environmental Sciences Guilin University of Electronic TechnologyGuilin 541004China Sino-Danish College University of Chinese Academy of ScienceBeijing 100049China Research Center for Augmented Intelligence Zhejiang LabHangzhou 311100China Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital Yongzhou 425000China

The rhesus macaque(Macaca mulatta)is a crucial experimental animal that shares many genetic,brain organizational,and behavioral characteristics with humans.A macaque brain atlas is fundamental to biomedical and evolutionary ***,even though connectivity is vital for understanding brain functions,a connectivity-based whole-brain atlas of the macaque has not previously been *** this study,we created a new whole-brain map,the Macaque Brainnetome Atlas(MacBNA),based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI *** new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional *** parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained *** a demonstrative application,the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain *** resulting resource includes:(1)the thoroughly delineated Macaque Brainnetome Atlas(MacBNA),(2)regional connectivity profiles,(3)the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset(Brainnetome-8),and(4)multi-contrast MRI,neuronal-tracing,and histological images collected from a single *** can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and ***,it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

关键词： Macaca mulatta Brain atlas Connectivity-based parcellation Diffusion MRI Cytoarchitecture Cross-species comparison

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