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Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 299-327页

作者： A.Robert Singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of Computational intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of artificial intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of Information Convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

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Event-Triggered Robust Parallel Optimal Consensus Control for Multiagent Systems

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IEEE/CAA Journal of Automatica Sinica 2025年第1期 40-53页

作者： Qinglai Wei Shanshan Jiao Qi Dong Fei-Yue Wang IEEE the institute of Systems Engineering Macau University of Science and Technology the State Key Laboratory of Multimodal artificial intelligence Systems Institute of Automation Chinese Academy of Sciences the School of artificial intelligence University of Chinese Academy of Sciences China Academy of Electronics and Information Technology the State Key Laboratory of Multimodal artificial intelligence Systems the School of artificial intelligence University of Chinese Academy of Sciences

This paper highlights the utilization of parallel control and adaptive dynamic programming(ADP) for event-triggered robust parallel optimal consensus control(ETRPOC) of uncertain nonlinear continuous-time multiagent systems(MASs).First, the parallel control system, which consists of a virtual control variable and a specific auxiliary variable obtained from the coupled Hamiltonian, allows general systems to be transformed into affine systems. Of interest is the fact that the parallel control technique's introduction provides an unprecedented perspective on eliminating the negative effects of disturbance. Then, an eventtriggered mechanism is adopted to save communication resources while ensuring the system's stability. The coupled HamiltonJacobi(HJ) equation's solution is approximated using a critic neural network(NN), whose weights are updated in response to events. Furthermore, theoretical analysis reveals that the weight estimation error is uniformly ultimately bounded(UUB). Finally,numerical simulations demonstrate the effectiveness of the developed ETRPOC method.

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Mechanism of inflammatory response and therapeutic effects of stem cells in ischemic stroke:current evidence and future perspectives

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Neural Regeneration research 2025年第1期20卷 67-81页

作者： Yubo Wang Tingli Yuan Tianjie Lyu Ling Zhang Meng Wang Zhiying He Yongjun Wang Zixiao Li Vascular Neurology Department of NeurologyBeijing Tiantan HospitalCapital Medical UniversityBeijingChina China National Clinical research Center for Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina Shanghai Engineering research Center of Stem Cells Translational Medicine ShanghaiChina National Center for Healthcare Quality Management in Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina institute for Regenerative Medicine Shanghai East HospitalSchool of Life Sciences and TechnologyTongji UniversityShanghaiChina Chinese institute for Brain research BeijingChina research Unit of artificial intelligence in Cerebrovascular Disease Chinese Academy of Medical SciencesBeijingChina Beijing Engineering research Center of Digital Healthcare for Neurological Diseases BeijingChina

Ischemic stroke is a leading cause of death and disability worldwide,with an increasing trend and tendency for onset at a younger ***,in particular,bears a high burden of stroke *** recent years,the inflammatory response after stroke has become a research hotspot:understanding the role of inflammatory response in tissue damage and repair following ischemic stroke is an important direction for its *** review summarizes several major cells involved in the inflammatory response following ischemic stroke,including microglia,neutrophils,monocytes,lymphocytes,and ***,we have also highlighted the recent progress in various treatments for ischemic stroke,particularly in the field of stem cell ***,understanding the complex interactions between inflammation and ischemic stroke can provide valuable insights for developing treatment strategies and improving patient *** cell therapy may potentially become an important component of ischemic stroke treatment.

关键词： cell therapy immune cell inflammatory ischemic stroke stem cell

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Science China Technological Sciences 2025年第1期 6-53页

作者： Zhe SUN Xuelong LI School of artificial intelligence Optics and Electronics (iOPEN)Northwestern Polytechnical University Key Laboratory of Intelligent Interaction and Applications (Northwestern Polytechnical University) Ministry of Industry and Information Technology The institute of artificial intelligence (TeleAI) China Telecom

Water-related optical imaging constitutes a pivotal domain within the field of water-related optics and vision,furnishing essential tools for comprehending the water-related environment, harnessing water resources, and safeguarding water ecology. Its merits encompass facile target detection, elevated imaging resolution, and copious information ***, the formidable challenge of attaining clear images in water-related environments is challenging due to the water's absorption and scattering properties. Substantial strides have been achieved in recent years through advancements in software and hardware optical imaging and processing techniques. This review offers a comprehensive exploration of the present state of water-related optical imaging, spanning historical, theoretical, and methodological dimensions. A retrospective analysis of the historical evolution of water-related optical imaging is presented, accompanied by a detailed exposition of the operational principles and the latest noteworthy advancements in various categories of water-related optical imaging. Furthermore, a meticulous comparative analysis of these methodologies is undertaken. These approaches not only enhance water-related optical imaging efficacy but also furnish robust support for scientific inquiry and resource exploitation in water-related environments. This review enhances the comprehension of advancements in water-related optical imaging research, acting as a crucial touchpoint for future explorations and innovations. Water-related optical imaging is critical for comprehending marine ecosystems, supporting environmental conservation, and improving industry efficiency.

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Flexible Graphene Field‑Effect Transistors and Their Application in Flexible Biomedical Sensing

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Nano-Micro Letters 2025年第2期17卷 252-313页

作者： Mingyuan Sun Shuai Wang Yanbo Liang Chao Wang Yunhong Zhang Hong Liu Yu Zhang Lin Han institute of Marine Science and Technology Shandong UniversityQingdao 266237ShandongPeople’s Republic of China State Key Laboratory of Crystal Materials Shandong UniversityJinan 250100ShandongPeople’s Republic of China School of Integrated Circuits Shandong UniversityJinan 250100ShandongPeople’s Republic of China Shandong Engineering research Center of Biomarker and artificial intelligence Application Jinan250100ShandongPeople’s Republic of China

Flexible electronics are transforming our lives by making daily activities more *** to this innovation are field-effect transistors(FETs),valued for their efficient signal processing,nanoscale fabrication,low-power consumption,fast response times,and ***,known for its exceptional mechanical properties,high electron mobility,and biocompatibility,is an ideal material for FET channels and *** combination of graphene and FETs has given rise to flexible graphene field-effect transistors(FGFETs),driving significant advances in flexible electronics and sparked a strong interest in flexible biomedical ***,we first provide a brief overview of the basic structure,operating mechanism,and evaluation parameters of FGFETs,and delve into their material selection and patterning *** ability of FGFETs to sense strains and biomolecular charges opens up diverse application *** specifically analyze the latest strategies for integrating FGFETs into wearable and implantable flexible biomedical sensors,focusing on the key aspects of constructing high-quality flexible biomedical ***,we discuss the current challenges and prospects of FGFETs and their applications in biomedical *** review will provide valuable insights and inspiration for ongoing research to improve the quality of FGFETs and broaden their application prospects in flexible biomedical sensing.

关键词： Flexible Graphene Field-effect transistor Wearable Implantable Biosensor

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Hierarchical Approximate Matching for Retrieval of Chinese Historical Calligraphy Character

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Journal of Computer Science & Technology 2007年第4期22卷 633-640页

作者：章夏芬庄越挺吴江琴吴飞 institute of artificial intelligence Zhejiang University

As historical Chinese calligraphy works are being digitized, the problem of retrieval becomes a new challenge. But, currently no OCR technique can convert calligraphy character images into text, nor can the existing Handwriting Character Recognition approach does not work for it. This paper proposes a novel approach to efficiently retrieving Chinese calligraphy characters on the basis of similarity： calligraphy character image is represented by a collection of discriminative features, and high retrieval speed with reasonable effectiveness is achieved. First, calligraphy characters that have no possibility similar to the query are filtered out step by step by comparing the character complexity, stroke density and stroke protrusion. Then, similar calligraphy characters axe retrieved and ranked according to their matching cost produced by approximate shape match. In order to speed up the retrieval, we employed high dimensional data structure - PK-tree. Finally, the efficiency of the algorithm is demonstrated by a preliminary experiment with 3012 calligraphy character images.

关键词： Chinese calligraphy approximate matching character retrieval

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Toward the third generation artificial intelligence

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Science China(Information Sciences) 2023年第2期66卷 5-23页

作者： Bo ZHANG Jun ZHU Hang SU institute for artificial intelligence Tsinghua University

There have been two competing paradigms in artificial intelligence(AI) development ever since its birth in 1956, i.e., symbolism and connectionism(or sub-symbolism). While symbolism dominated AI research by the end of 1980s, connectionism gained momentum in the 1990s and is gradually displacing symbolism. This paper considers symbolism as the first generation of AI and connectionism as the second generation. However, each of these two paradigms simulates the human mind from only one *** cannot achieve true human behaviors by relying on only one paradigm. In order to develop novel AI technologies that are safe, reliable, and extensible, it is necessary to establish a new explainable and robust AI theory. To this end, this paper looks toward developing a third generation artificial intelligence by combining the current paradigms.

关键词： artificial intelligence symbolism connectionism dual-space model single-space model triple-space model

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research on Key Technologies of Network Security Situational Awareness for Attack Tracking Prediction

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Chinese Journal of Electronics 2019年第1期28卷 162-171页

作者： KOU Guang WANG Shuo TANG Guangming artificial intelligence research Center National Innovation Institute of Defense Technology Information Engineering University

This paper analyzed the existing network security situation evaluation methods and discovered that they cannot accurately reflect the features of large-scale,synergetic, multi-stage gradually shown by network attack behaviors. For this purpose, the association between attack intention and network configuration information was deep analyzed. Then a network security situation evaluation method based on attack intention recognition was proposed. Unlike traditional method, the evaluation method was based on intruder. This method firstly made causal analysis of attack event and discovered and simplified intrusion path to recognize every attack phases, then realized situation evaluation based on the attack phases. Lastly attack intention was recognized and next attack phase was forecasted based on achieved attack phases, combined with vulnerability and network connectivity. A simulation experiments for the proposed network security situation evaluation model is performed by network examples. The experimental results show that this method is more accurate on reflecting the truth of attack. And the method does not need training on the historical sequence, so the method is more effective on situation forecasting.

关键词： Multi-stage attack Situation evaluation Network security Intention recognition Causal analysis

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A novel spiking neural network of receptive field encoding with groups of neurons decision

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Frontiers of Information Technology & Electronic Engineering 2018年第1期19卷 139-150页

作者： Yong-qiang MA Zi-ru WANG Si-yu YU Ba-dong CHEN Nan-ning ZHENG Peng-ju REN institute of artificial intelligence and Robotics Xi'an Jiaotong University

Human information processing depends mainly on billions of neurons which constitute a complex neural network,and the information is transmitted in the form of neural *** this paper,we propose a spiking neural network(SNN),named MD-SNN,with three key features:(1) using receptive field to encode spike trains from images;(2) randomly selecting partial spikes as inputs for each neuron to approach the absolute refractory period of the neuron;(3) using groups of neurons to make *** test MD-SNN on the MNIST data set of handwritten digits,and results demonstrate that:(1) Different sizes of receptive fields influence classification results significantly.(2) Considering the neuronal refractory period in the SNN model,increasing the number of neurons in the learning layer could greatly reduce the training time,effectively reduce the probability of over-fitting,and improve the accuracy by 8.77%.(3) Compared with other SNN methods,MD-SNN achieves a better classification;compared with the convolution neural network,MD-SNN maintains flip and rotation invariance(the accuracy can remain at 90.44% on the test set),and it is more suitable for small sample learning(the accuracy can reach 80.15%for 1000 training samples,which is 7.8 times that of CNN).

关键词： Tempotron Receptive field Difference of Gaussian(DoG) Flip invariance Rotation invariance

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Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 37-57页

作者： Zhiqiang Pu Yi Pan Shijie Wang Boyin Liu Min Chen Hao Ma Yixiong Cui the School of artificial intelligence University of Chinese Academy of Sciences the institute of Automation Chinese Academy of Sciences the Nanjing artificial intelligence research of IA the School of Sports Engineering Beijing Sport University

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) *** addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

关键词： artificial intelligence(AI) decision-making football review soccer sports analytics

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