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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Xin Yang Wanji He Jiaoying Jin Xuming Zhang Ming Yuchi Mingyue Ding State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence (IPRAI) Huazhong University of Science and Technology Wuhan Hubei China Image Processing and Intelligence Control Key Laboratory of Education Ministry of China S School of Life Science and Technology Huazhong University of Science and Technology Wuhan Hubei China

A hybrid method is used to evaluate atherosclerosis through a mathematical morphology approach and GVF-Snake method. Common carotid artery (CCA) segmentation requires outlining the intima and adventitia contours on the transverse view of B-mode ultrasound (US) images. The lumen and adventitia contours are segmented using a morphology and GVF-Snake methods, respectively. Upon analyzing ten separate patient data sets demonstrate that a comparison between the proposed method and the traditional approach (manual contouring) on 110 transverse images of the CCA showed a mean absolute distance (MAD) of 0.67±0.17mm for lumen and 0.64 ± 0.19mm for adventitia. Their Dice Similarity Coefficient (DSC) values are 92.7%±2.3% and 90.3%±3.5% for lumen and adventitia segmentation, respectively. These values are in good agreement with clinical standards.

关键词： image segmentation Three dimensional displays Measurement Biomedical imaging Ultrasonic imaging Sun

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Ultrasound Carotid Artery Intima-Media Thickness (IMT) Segmentation Review

Ultrasound Carotid Artery Intima-Media Thickness (IMT) Segme...

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International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Xin Yang Jiaoying Jin Ming Yuchi Mingyue Ding State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence (IPRAI) Huazhong University of Science and Technology HUST Wuhan Hubei China Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology HUST Wuhan Hubei China

Stroke and heart attack, which could be led by a kind of cerebrovascular and cardiovascular disease named asatherosclerosis, would seriously cause human morbidity and mortality. And the carotid artery of intima-media thickness (IMT) is a key indicator to the disease. With the development of computer assisted diagnosis (CAD) technology, Ultrasound imaging, being real-time, economic, reliable, safe, and now seems to become a standard in vascular assessment methodology especially for the measurement of IMT. This review is an attempt to discuss the clinical relevance of measurements in clinical practice at first, and then followed by the challenges that one has to face when approaching the segmentation of ultrasound images. Secondly, the paper is presentation of common used methods for the IMT segmentation and measurement. An overview of summary and future perspectives is given in conclusion finally.

关键词： Ultrasonic imaging image segmentation Carotid arteries Ultrasonic variables measurement Biomedical imaging

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Large, Complex, and Realistic Safety Clothing and Helmet Detection: Dataset and Method

arXiv

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arXiv 2023年

作者： Yu, Fusheng Li, Jiang Wang, Xiaoping Wu, Shaojin Zhang, Junjie Zeng, Zhigang The School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Institute of Artificial Intelligence Huazhong University of Science and Technology Wuhan430074 China The Hubei Key Laboratory of Brain-Inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China The Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

Detecting safety clothing and helmets is paramount for ensuring the safety of construction workers. However, the development of deep learning models in this domain has been impeded by the scarcity of high-quality datasets. In this study, we construct a large, complex, and realistic safety clothing and helmet detection (SFCHD) dataset. SFCHD is derived from two authentic chemical plants, comprising 12,373 images, 7 categories, and 50,552 annotations. We partition the SFCHD dataset into training and testing sets with a ratio of 4:1 and validate its utility by applying several classic object detection algorithms. Furthermore, drawing inspiration from spatial and channel attention mechanisms, we design a spatial and channel attention-based low-light enhancement (SCALE) module. SCALE is a plug-and-play component with a high degree of flexibility. Extensive evaluations of the SCALE module on both the ExDark and SFCHD datasets have empirically demonstrated its efficacy in enhancing the performance of detectors under low-light conditions. The dataset and code are publicly available at https://***/lijfrankopen/SFCHD-SCALE. Copyright © 2023, The Authors. All rights reserved.

关键词： Chemical plants

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New Criteria of Passivity Analysis for Fuzzy Time-Delay Systems With Parameter Uncertainties

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IEEE Transactions on Fuzzy Systems 2015年第6期23卷 2284-2301页

作者： Wen, Shiping Zeng, Zhigang Huang, Tingwen Yu, Xinghuo Xiao, Mingqing School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Texas A and M University at Qatar Doha23874 Qatar Platform Technologies Research Institute RMIT University MelbourneVIC3001 Australia Department of Mathematics Southern Illinois University CarbondaleIL62901 United States

This paper investigates the passivity problem for a class of uncertain stochastic fuzzy nonlinear systems with mixed delays and nonlinear noise disturbances by employing an improved free-weighting matrix approach. The fuzzy system is based on the Takagi-Sugeno model that is often used to represent the complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning. To reflect more realistic dynamical behaviors of the system, the parameter uncertainties, the stochastic disturbances, and nonlinearities are considered, where the parameter uncertainties enter into all the system matrices, the stochastic disturbances are given in the form of a Brownian motion. The mixed delays comprise both discrete and distributed time-varying delays. By taking the relationship among the time delays, their lower and upper bounds into account, some less conservative linear-matrix-inequality-based delay-dependent passivity criteria are obtained without ignoring any useful terms in the derivative of Lyapunov functional. Finally, numerical examples are given to demonstrate the effectiveness and merits of the proposed methods. © 1993-2012 IEEE.

关键词： Time delay

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NMF: an Efficient Method for Detecting the Fallen Leaves Using Cleaning Robots on the Road

NMF: an Efficient Method for Detecting the Fallen Leaves Usi...

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IEEE International Conference on Robotics and Biomimetics

作者： Yanzi Miao Zongwei Zhang Hesheng Wang Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China China University of Mining and Technology Xuzhou China Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665405362

The improvement of urban greening level makes sanitary work more complicated and difficult, especially, for the seasonal leaf cleaning on roads in the park, campus etc.. With the rapid development of computer vision, it is a feasible and innovative way to detect and clean the fallen leaves effectively with intelligent robot. However, since the irregular shape and size, uneven distribution of fallen leaves and complex outdoor conditions, especially the densely stacked leaves, even current advanced object detection algorithm has no satisfactory effect on detection of fallen leaves. To deal with the dense leaves detection problem and improve navigation efficiency, we propose a Non-Maximum Fusion(NMF) algorithm. NMF scales the high-confidence box with the pre-defined δ to fuse intersecting and adjacent boxes instead of supressing these boxes. The experiments on the fallen leaves data set shows that NMF improves the fallen leaves detection coverage significantly and the coverage reaches to 95%. Also, NMF greatly reduces the number of goal nodes for path planning. Since NMF functions at the back end of detector to process detection boxes without training, it can be intergrated into any fallen leaves detection pipeline easily.

关键词： Training Navigation Shape Roads Pipelines Green products Object detection

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Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion Recognition

arXiv

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arXiv 2024年

作者： Li, Jiang Wang, Xiaoping Zeng, Zhigang The School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Institute of Artificial Intelligence Huazhong University of Science and Technology Wuhan430074 China The Hubei Key Laboratory of Brain-Inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China The Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

Multimodal emotion recognition in conversation (MERC) has garnered substantial research attention recently. Existing MERC methods face several challenges: (1) they fail to fully harness direct inter-modal cues, possibly leading to less-than-thorough cross-modal modeling;(2) they concurrently extract information from the same and different modalities at each network layer, potentially triggering conflicts from the fusion of multi-source data;(3) they lack the agility required to detect dynamic sentimental changes, perhaps resulting in inaccurate classification of utterances with abrupt sentiment shifts. To address these issues, a novel approach named GraphSmile is proposed for tracking intricate emotional cues in multimodal dialogues. GraphSmile comprises two key components, i.e., GSF and SDP modules. GSF ingeniously leverages graph structures to alternately assimilate inter-modal and intra-modal emotional dependencies layer by layer, adequately capturing cross-modal cues while effectively circumventing fusion conflicts. SDP is an auxiliary task to explicitly delineate the sentiment dynamics between utterances, promoting the model’s ability to distinguish sentimental discrepancies. Furthermore, GraphSmile is effortlessly applied to multimodal sentiment analysis in conversation (MSAC), forging a unified multimodal affective model capable of executing MERC and MSAC tasks. Empirical results on multiple benchmarks demonstrate that GraphSmile can handle complex emotional and sentimental patterns, significantly outperforming baseline models. Copyright © 2024, The Authors. All rights reserved.

关键词： Emotion Recognition

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Automatic Detection of the Intima-Media Layer in Ultrasound Common Carotid Artery image Based on Active Contour Model

Automatic Detection of the Intima-Media Layer in Ultrasound ...

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International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Jiaoying Jin Mingyue Ding Xin Yang Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Life School of Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI) Life School of Science and Technology Huazhong University of Science and Technology Wuhan China

The analysis of the carotid artery wall is of paramount importance in clinical practice. Especially, the intima-media thickness is a risk index for some of the most severe acute cerebrovascular pathologies, hence, an accurate segmentation of the different layers of the carotid artery is needed. IMT is usually manually measured on longitudinal B-mode ultrasound images. In the past ten years, many computer-based techniques for intima-media thickness measurement have been proposed to overcome the limits of manual segmentation, but almost all of them require a certain degree of user interaction. In this paper we proposed a novel approach for the completely user-independent segmentation of the common carotid artery wall. Our algorithm is designed for the extraction of the intima and media layers of the distal carotid wall in ultrasound images. It is based on integrated approach consisting of common carotid artery region identification, contour initialization with threshold segmentation, intima-lumen segmentation with Snake, and media-adventitia segmentation with GVF-Snake that enables the automated tracing of the carotid walls. The acoustic impedance's difference is employed to locate common carotid artery region. Finally, the characterization of the algorithm in terms of segmentation error was evaluated with a set of 40 common carotid artery ultrasound images and compared to the segmentation traced by a trained operator. Experiments showed that a mean error lower than 1.3 pixel both on the intima and media layers was obtained, which is comparable to that obtained by means of operator dependent techniques.

关键词： image segmentation Carotid arteries Ultrasonic imaging Media Algorithm design and analysis Ultrasonic variables measurement

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Ultrasound image Denoising with Multi-shape Patches Aggregation Based Non-local Means

Ultrasound Image Denoising with Multi-shape Patches Aggregat...

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International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Wanjun Chen Mingyue Ding Yalin Miao Lei Luo Department of Information Science Xi'an University of Technology Xi'an Shaanxi China College of Life Science and Technology lmage processing and Intelligent Control key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China

The Non-Local Means (NLM) filter uses the redundancy of information in the image to remove noise, this scheme gives some of the best results among other powerful methods such as wavelet based approaches or diffusion techniques. Though simple to implement and efficient in practice, the classical NLM suffers from ringing artifacts around edges when using square patches, due to an abrupt lack of redundancy of the image. This paper presents an extended NLM based on Multi-Shape Patches Aggregation (NLM-MSPA) to overcome this problem, and uses it to remove medical ultrasound images corrupted by multiplicative speckle noise. We have incorporated a preprocessing step to make the speckle noise much closer to the real additive white Gaussian noise, hence more amenable to a denoising algorithm such as NLM-MSPA. Results on real images and artificially speckled images show that the proposed scheme outperforms several classical methods chosen for comparison in its ability to reduce speckle and preserve edge details.

关键词： Speckle Ultrasonic imaging Noise reduction Shape Biomedical imaging Signal to noise ratio

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Application of Case Teaching Method in Artificial Intelligence Teaching

Application of Case Teaching Method in Artificial Intelligen...

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作者： Li Huang Wei Hu Chong Tan College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology

Aiming at the current situation of poor quality of artificial intelligence teaching and weak students' interest in learning, a case teaching method is proposed. This paper analyzes the teaching status of artificial intelligence firstly, and then systematically describes the case teaching method. Finally, the necessity of introducing case teaching method into artificial intelligence teaching is studied. Practice shows that the case teaching method can effectively enhance students' self-learning ability, improve students' comprehensive innovation ability, and promote the development of artificial intelligence teaching.

关键词： Case teaching method Artificial intelligence Teaching case Course

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An OpenPLC-based Active Real-time Anomaly Detection Framework for Industrial control Systems

An OpenPLC-based Active Real-time Anomaly Detection Framewor...

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Chinese Automation Congress (CAC)

作者： Chengxu Zheng Xiaopeng Wang Xiaoyu Luo Chongrong Fang Jianping He The Dept. of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China NSFOCUS Technologies Group Co. Ltd Beijing China

In recent years, the design of anomaly detectors has attracted a tremendous surge of interest due to security issues in industrial control systems (ICS). Restricted by hardware resources, most anomaly detectors can only be deployed at the remote monitoring ends, far away from the control sites, which brings potential threats to anomaly detection. In this paper, we propose an active real-time anomaly detection framework deployed in the controller of OpenPLC, which is a standardized open-source PLC and has high scalability. Specifically, we add adaptive active noises to control signals, and then identify a linear dynamic system model of the plant offline and implement it in the controller. Finally, we design two filters to process the estimated residuals based on the obtained model and use χ 2 detector for anomaly detection. Extensive experiments are conducted on an industrial control virtual platform to show the effectiveness of the proposed detection framework.

关键词： Adaptation models Industrial control Detectors Real-time systems Software Security Task analysis

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