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An Effective Retinal Blood Vessel Segmentation by Using Automatic Random Walks Based on Centerline Extraction

BioMed Research International 2020年第0期2020卷 000-000页

作者： Gao, Jianqing Chen, Guannan Lin, Wenru Smart Home Information Collection and Processing on Internet of Things Laboratory of Digital Fujian Fujian Jiangxia University Fuzhou 350108 China School of Electronic Information Science Fujian Jiangxia University Fuzhou 350108 China Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education Fujian Provincial Key Laboratory for Photonics Technology Fujian Normal University Fuzhou 350007 China Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application Fujian Normal University Fuzhou 350117 China College of Computer and Control Engineering Minjiang University Fuzhou 350121 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou 350121 China

The retinal blood vessel analysis has been widely used in the diagnoses of diseases by ophthalmologists. According to the complex morphological characteristics of the blood vessels in normal and abnormal images, an automatic method by using the random walk algorithms based on the centerlines is proposed to segment retinal blood vessels. Hessian-based multiscale vascular enhancement filtering is used to display the vessel structures in maximum intensity projection. Random walk algorithm provides a unique and quality solution, which is robust to weak object boundaries. Seed groups in the random walk segmentation are labeled according to the centerlines, which are extracted by using the divergence of the normalized gradient vector field and the morphological method. Experiments of the proposed method are implemented on the publicly available STARE (the Structured Analysis of the Retina) database. The results are compared to other existing retinal blood vessel segmentation methods with respect to the accuracy, sensitivity, and specificity, and the proposed method is proved to be more sensitive in detecting the retinal blood vessels in both normal and pathological areas. © 2020 Jianqing Gao et al.

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SEBF: A single-chain based extension model of blockchain for fintech 29

SEBF: A single-chain based extension model of blockchain for...

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Ji, Yimu Gu, Weiheng Chen, Fei Xiao, Xiaoying Sun, Jing Liu, Shangdong He, Jing Li, Yunyao Zhang, Kaixiang Mei, Fen Wu, Fei School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing China Institue of High Performance Computing and Bigdata Nanjing University of Posts and Telecommunications Nanjing China Nanjing Center of HPC China Nanjing China Jiangsu HPC and Intelligent Processing Engineer Research Center Nanjing China Institute of Information Technology Nanjing University of Finance and Economics Nanjing China School of Software and Electrical Engineering Swinburne University of Technology Hawthorn Australia WeBank Co. Ltd. Shenzhen China College of Automation Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9780999241165

The traditional blockchain has the shortcoming that a single-chain can only deal with one or a few specific data types. The research question of how to make blockchain be able to deal with various data types has not been well studied. In this paper, we propose a single-chain based extension model of blockchain for fintech (SEBF). In the financial environment, we design a four-layer architecture for this model. By employing the external trusted oracle group and a financial regulator agency, a variety types of data can be effectively stored in the blockchain, such that the data type extension based on a single-chain is realized. The experimental results indicate that the proposed model can improve the efficiency of simplified payment verification. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Blockchain

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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

arXiv

引用

arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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Ligand-rich oxygen evolution electrocatalysts reconstructed from metal-organic frameworks for anion-exchange membrane water electrolysis

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Science Bulletin 2025年

作者： Li, Shiqi Liu, Weiwei Shi, Yi Wang, Tang Liu, Tianyang Xue, Xiang Li, Rui Qiao, Man Wu, Zhen-Yu Zhang, Wang College of Materials Science and Engineering College of Environment Zhejiang University of Technology Hangzhou310014 China Department of Chemistry Institute of Innovative Material Guangdong Provincial Key Laboratory of Sustainable Biomimetic Materials and Green Energy Southern University of Science and Technology Shenzhen518055 China Jiangsu Co-Innovation Centre of Efficient Processing and Utilization of Forest Resources College of Chemical Engineering Nanjing Forestry University Nanjing210037 China Institute of Advanced Materials and Flexible Electronics School of Chemistry and Materials Science Nanjing University of Information Science & Technology Nanjing210044 China

Organic ligands in metal-organic frameworks (MOFs) play an indispensable role in the reconstruction and catalysis during the alkaline oxygen evolution reaction (OER). However, it is still a big challenge to maintain a high content of ligands in MOF-reconstructed OER electrocatalysts and to study the interaction between ligands and derived (oxy)hydroxides. Herein, a ligand-rich trimetallic amorphous electrocatalyst is fabricated through a two-step mechanochemical and electrochemical reconstruction strategy. Experimental and theoretical studies clearly reveal that the d-π interaction between delocalized π-electrons on the benzene ring of ligands and derived (oxy)hydroxides, can trigger the charge transfer from ligands to the active metal centers, thus optimizing the adsorption energy of the oxygen-containing intermediates and enhancing the OER performance. Moreover, an anion-exchange membrane water electrolyzer using such ligand-rich OER electrocatalyst can be operated steadily at 1.69 V and 55 °C under an industrial-level current density of 500 mA cm−2 for over 200 h. This work provides novel insights into the role of organic ligands in alkaline OER electrocatalysis, with the potential to facilitate the production of green hydrogen at industrial-level current densities. © 2025 Science China Press

关键词： Electrolysis

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Privacy-preserving medical treatment system through nondeterministic finite automata

arXiv

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arXiv 2020年

作者： Yang, Yang Deng, Robert H. Liu, Ximeng Wu, Yongdong Weng, Jian Zheng, Xianghan Rong, Chunming School of Information Systems Singapore Management University Singapore College of Mathematics and Computer Science Fuzhou University Fujian China State Key Laboratory of Integrated Services Networks Xidian University Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China School of Information Systems Singapore Management University Singapore Singapore Department of Computer Science Jinan University Guangdong China College of Mathematics and Computer Science Fuzhou University Fujian China Department of Electronic Engineering and Computer Science University of Stavanger Norway MingByte Technology Qingdao China

In this paper, we propose a privacy-preserving medical treatment system using nondeterministic finite automata (NFA), hereafter referred to as P-Med, designed for the remote medical environment. P-Med makes use of the nondeterministic transition characteristic of NFA to flexibly represent the medical model, which includes illness states, treatment methods and state transitions caused by exerting different treatment methods. A medical model is encrypted and outsourced to the cloud to deliver telemedicine services. Using P-Med, patient-centric diagnosis and treatment can be made on-the-fly while protecting the confidentiality of a patient's illness states and treatment recommendation results. Moreover, a new privacy-preserving NFA evaluation method is given in P-Med to get a confidential match result for the evaluation of an encrypted NFA and an encrypted data set, which avoids the cumbersome inner state transition determination. We demonstrate that P-Med realizes treatment procedure recommendation without privacy leakage to unauthorized parties. We conduct extensive experiments and analyses to evaluate efficiency. Copyright © 2020, The Authors. All rights reserved.

关键词： Diseases

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Patch-wise label propagation for MR brain segmentation based on multi-atlas images

Patch-wise label propagation for MR brain segmentation based...

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作者： Wang, Yan Zu, Chen Ma, Zongqing Luo, Yong He, Kun Wu, Xi Zhou, Jiliu College of Computer Science Sichuan University Chengdu China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Department of Head and Neck and Mammary Oncology West China Hospital Sichuan University Chengdu China College of Computer Science Chengdu University of Information Technology Chengdu China

In many neuroscience and clinical studies, accurate and automatic segmentation of subcortical structures is an important and difficult task. Multi-atlas-based segmentation method has been focus of considerable research due to its promising performance. In general, this technique first employs deformable image registration to construct the correspondences between pre-labeled atlas images and the target image. Then, using the acquired deformation field, labels in the atlas are propagated to the target image space. Obviously, anatomical differences between the target image and atlas images possibly affect the image registration accuracy, thus influencing the final segmentation performance. Another limitation is that the label propagation in most conventional multi-atlas based methods is implemented under a voxel-wise strategy, which cannot adequately utilize the local label information to determine the final label of the target sample. In this paper, we propose a patch-wise label propagation method based on multiple atlases for MR brain segmentation. First, each image patch is characterized by patch intensities and abundant texture features, to increase the accuracy of the patch-based similarity measurement. To determine the weights of the training patches for representing the test sample, a patch-based sparse coding procedure is employed. In the label propagation stage, to alleviate possible misalignment from the registration stage, we perform a patch-wise label propagation strategy in a nonlocal manner to predict the final label for each target sample. To evaluate the proposed segmentation method, we comprehensively implement our proposed method by conducting hippocampus segmentation on the ADNI data set. Experimental results demonstrate the effectiveness of the proposed method and show that the proposed method outperforms two conventional multi-atlas-based methods. © 2017, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Image registration

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Unsupervised ensemble learning based on graph embedding for image clustering 25th

Unsupervised ensemble learning based on graph embedding for ...

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25th International Conference on Neural information processing, ICONIP 2018

作者： Luo, Xiaohui Zhang, Li Li, Fanzhang Hu, Chengxiang School of Computer Science and Technology and Joint International Research Laboratory of Machine Learning and Neuromorphic Computing Provincial Key Laboratory for Computer Information Processing Technology Soochow University SuzhouJiangsu215006 China

ISBN: (纸本)9783030041816

Manifold learning has attracted more and more attention in machine learning for past decades. Unsupervised Large Graph Embedding (ULGE), which performs well on the large-scale data, has been proposed for manifold learning. To improve the clustering performance, a novel Unsupervised Ensemble Learning based on Graph Embedding (UEL-GE) is explored, which takes ULGE to get low-dimensional embeddings of the given data and uses the K-means method to obtain the clustering results. Furthermore, the multiple clusterings are corrected by using the bestMap method. Finally, the corrected clusterings are combined to generate the final clustering. Extensive experiments on several data sets are conducted to show the efficiency and effectiveness of the proposed ensemble learning method. © Springer Nature Switzerland AG 2018.

关键词： K-means clustering

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Target vehicle detection and tracking in surveillance videos based on exponential forgetting and perceptual hash algorithm

Advances in Transportation Studies

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Advances in Transportation Studies 2018年第Special issue期2卷 97-106页

作者： Fan, H.H. Zhu, H.J. School of Computer Engineering Jiangsu University of Technology Changzhou213001 China Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Changzhou213001 China

In order to obtain the stable background of a traffic surveillance video, the application scenarios, computational complexity, and results of the Gaussian background model were analyzed. In the background modeling process, many artifacts were generated, making it difficult to reconstruct a highly stable background image. In order to solve this problem, we proposed a background model based on exponential forgetting algorithm. This method satisfies the background reconstruction of complex environment, the computation is small and the background result is pure. To further improve the accuracy of the test, shadows of the vehicle were detected to reduce the error caused on vehicle detection. The perceptual hash algorithm was used to track the target vehicle. The proposed algorithm is verified by different video data. The experimental results show that a good vehicle tracking effect is achieved in a variety of weather conditions. © 2018, Gioacchino Onorati Editore. All rights reserved.

关键词： Vehicles

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An Integrated and Intelligent Dental Healthcare System with Mobile Services 15th

An Integrated and Intelligent Dental Healthcare System with ...

引用

15th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Xu, Yueshen Lu, Yi Li, Rui Niu, Lin Du, Wenzhi An, Ni Liu, Yaning Liu, Xinyi Jiang, Yan Li, Zhenhua Guo, Jin Wang, Xiangdong School of Computer Science and Technology Xidian University Xi’an710071 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University SuzhouJiangsu215006 China Stomatological Hospital Xi’an Jiaotong University Xi’an710004 China Clinical Research Center of Shaanxi Province for Dental and Maxillofacial Diseases College of Stomatology Xi’an Jiaotong University Xi’an China Shaanxi Lishengruihui Technology Co. Ltd. Xi’an710075 China

ISBN: (纸本)9783030301453

Medical informatization takes a key role in medical and healthcare industries, which is a necessary way of improving service quality and treatment experience in a hospital. In this paper, we design and implement an integrated and intelligent healthcare system with mobile services, specific to dental healthcare. The developed system contains four components, including WeChat official account, intelligent question and answering (Q&A) system, mobile follow-up care mini program and AI speech assistant. The developed WeChat official account and intelligent Q&A system provide a large amount of professional knowledge on dental health, which can help narrow the knowledge gap between doctors and patients. The two components facilitate patients to follow up our applications without downloading any extra softwares, as the developed functions (e.g., voice service) are provided through mobile services. These two components also facilitate follow-up management, decreasing manpower and resource usage in hospital. Our system is developed to serve patients as well as dentists, and provides a group of interactive healthcare services in a low cost. In this paper, we elaborate the whole system architecture and implementation detail of each component. We also report the performance test result and training process of the classifier. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Hospitals

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Efficiently Retrieving Differences between Remote Sets using Counting Bloom Filter

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International Journal of Performability Engineering 2019年第7期15卷 1947-1954页

作者： Tian, Xiaomei Zhao, Huihuang Sun, Yaqi Liang, Xiaoman College of Computer Science and Technology Hengyang Normal University Hengyang421002 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

Retrieving differences between remote sets is widely used in set reconciliation and data deduplication. Set reconciliation and data deduplication between two nodes are widely used in various network applications. The basic idea of the difference retrieving problem is that each member of a node pair has an object set and seeks to find all differences between the two remote sets. There are many methods for retrieving difference sets, such as the standard Bloom filter (SBF), counting Bloom filter (CBF), and invertible Bloom filter (IBF). In these methods, based on the standard Bloom filter or its variants, each node represents its objects using a standard Bloom filter or other Bloom filter, which is then exchanged. A receiving node retrieves different objects between the two sets according to the received SBF, CBF, or IBF. We propose a new algorithm for retrieving differences that finds differences between remote sets using counting Bloom filters' deletion operation. The theoretical analyses and experimental results show that the differences can be retrieved efficiently. Only a very small number of differences are missing in the retrieving process, and this false negative rate can be decreased to 0% by adjusting the counting Bloom filter's parameters. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Data structures

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