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arXiv 2017年

作者： Fan, Zhun Lu, Jiewei Li, Wenji Wei, Caimin Huang, Han Cai, Xinye Chen, Xinjian Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shan'tou515063 China Department of Mathematics Shantou University Shan'tou515063 China School of Software Engineering South China University of Technology Guang'zhou510006 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Jiang'su210016 China Medical Image Processing and Analysis Lab School of Electronics and Information Engineering Soochow University Su'zhou215006 China

In this paper, a hierarchical image matting model is proposed to extract blood vessels from fundus images. More specifically, a hierarchical strategy utilizing the continuity and extendibility of retinal blood vessels is integrated into the image matting model for blood vessel segmentation. Normally the matting models require the user specified trimap, which separates the input image into three regions manually: the foreground, background and unknown regions. However, since creating a user specified trimap is a tedious and time-consuming task, region features of blood vessels are used to generate the trimap automatically in this paper. The proposed model has low computational complexity and outperforms many other state-of-art supervised and unsupervised methods in terms of accuracy, which achieves a vessel segmentation accuracy of 96.0%, 95.7% and 95.1% in an average time of 10.72s, 15.74s and 50.71s on images from three publicly available fundus image datasets DRIVE, STARE, and CHASE_DB1, respectively. Copyright © 2017, The Authors. All rights reserved.

关键词： Blood vessels

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Topology analysis system for vehicular Ad Hoc network 17

Topology analysis system for vehicular Ad Hoc network

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17th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2016

作者： Dong, Baihong Deng, Jian Wu, Weigang Meng, Tianyu 1. School of Data and Computer Science Sun Yat-Sen Univ. China Guangdong Province Key Lab. of Big Data Analysis and Processing China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou China

ISBN: (纸本)9781509050819

With the development of the technology, Vehicular Ad-hoc Network is developing rapidly and continuously. And many new algorithms in VANET were put forward. For example, many people apply the Named Data Networks or Software Defined Networking6 to the VANET. However, few researches are looking into the analysis of the topology of the VANET, among most of which are based on simple situations and calculation of the track of vehicles. And therefore, these analysis are inadequate for analyzing the topology under complex situations. This paper is going to put forward a new method for analyzing the change of the topology of VANET, which is capable to quantitatively analyze the change under different and complex situations. In the real experiment, when compared with traditional analysis methods, this new method can analyze more precisely the impact of some possible wireless communication problem on the change of the topology, for example, the impact of hidden node on the vehicular wireless communication and whether the number or the density of vehicles makes the topology of VANET more stable. And this new method can provide a numerical result instead of purely qualitative analysis. © 2016 IEEE.

关键词： Topology

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Software Defined Networking Based On-Demand Routing Protocol in Vehicle Ad Hoc Networks

Software Defined Networking Based On-Demand Routing Protocol...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Baihong Dong Weigang Wu Zhiwei Yang Junjie Li School of Data and Computer Science Sun Yat-Sen University Guangdong Key Lab. of Big Data Analysis and Processing Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou

ISBN: (纸本)9781509056972

This paper comes up with a SDN based On-Demand Routing Protocol, SVAO, which separates data forwarding layer and network control layer, as in SDN, to enhance the data transmission efficiency within VANETs. The Roadside Service Unit plays the role of Local Controller and is in charge of selecting vehicles to forward packet within a road segment. All the vehicles state in the road. Correspondingly, a two-level design is used. Global Level is distributed and adopts a ranked query scheme to collect vehicle information and determine the road segments along which a message should be forwarded. And the Local Level is in charge of selecting forwarding vehicles in each road segment determined by the global level. We compare SVAO with popular ad-hoc network routing protocols, including OLSR, DSR, DSDV, and DB via simulations. We consider the impact of vehicle density, speed on data transmission rate and average packet delay. The simulation results show that in case of large network scales or high vehicle speed, SVAO performs better than the others.

关键词： Routing protocols Roads Routing Ad hoc networks Topology Vehicle dynamics

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Person re-identification with density-distance unsupervised salience learning 8th

Person re-identification with density-distance unsupervised ...

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8th International Conference on image and Graphics, ICIG 2015

作者： Zhou, Baoliang Zheng, Aihua Jiang, Bo Li, Chenglong Tang, Jin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology AnHui University Hefei China Key Laboratory of Industry Image Processing and Analysis in Anhui Province Hefei China

ISBN: (纸本)9783319219684

Human salience of pedestrians images is distinctive and has been shown importantly in person re-identification (or pedestrians identification) problem. Thus, how to obtain the salient area of pedestrian images is important for this salience based pedestrians identification problem. In this paper, we first show that this kind of salient area detection can be formulated as a kind of outlier detection problem, and then propose a novel unsupervised salience learning method using a local outlier-detection technique for person re-identification task. The main feature of the proposed salience computation method is that it exploits both distance and density information simultaneously. Experimental results on several datasets show the effectiveness of the proposed salience based person re-identification method. © Springer International Publishing Switzerland 2015.

关键词： Statistics

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Small universal simple spiking neural P systems with weights

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Science China(Information Sciences) 2014年第9期57卷 19-29页

作者： ZENG XiangXiang PAN LinQiang PREZ-JIMNEZ Mario J. Key Laboratory of Image Processing and Intelligent Control School of AutomationHuazhong University of Science and Technology Department of Computer Science and Artificial Intelligence University of SevillaAvda. Reina Mercedes s/nSevilla 41012Spain

Spiking neural P systems with weights(WSN P systems,for short)are a new variant of spiking neural P systems,where the rules of a neuron are enabled when the potential of that neuron equals a given *** is known that WSN P systems are universal by simulating register ***,in these universal systems,no bound is considered on the number of neurons and *** this work,a restricted variant of WSN P systems is considered,called simple WSN P systems,where each neuron has only one *** complexity parameter,the number of neurons,to construct a universal simple WSN P system is *** is proved that there is a universal simple WSN P system with 48 neurons for computing functions;as generator of sets of numbers,there is an almost simple(that is,each neuron has only one rule except that one neuron has two rules)and universal WSN P system with 45 neurons.

关键词： bio-inspired computing membrane computing P system spiking neural P system universal computing device

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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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A joint strength based genetic algorithm for network clustering

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Journal of Computational Information Systems 2014年第14期10卷 5915-5922页

作者： Zhang, Xingyi Ding, Zhuanlian Tang, Jin Luo, Bin Key Laboratory of Industrial Image Processing and Analysis of Anhui Province School of Computer Science and Technology Anhui University Hefei China

The quality of network clustering is partially determined by its evaluation criterion. In this paper, a joint strength based genetic algorithm (JSGA) for network clustering is proposed, where the joint strength which can effectively distinguish density and network topology is introduced as the evaluation criterion. An efficient joint strength based local search strategy is presented in JSGA, which can improve the local search ability of existing genetic algorithms for network clustering. A joint strength based population initialization method is also proposed, by which an initial population with a good clustering precision and diversity can be generated. Experimental results on both computer-generated networks and realworld network data sets illustrate that JSGA outperforms traditional methods in terms of detecting communities. © 2014 by Binary Information Press

关键词： Genetic algorithms

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Computational efficiency and universality of timed P systems with membrane creation

Computational efficiency and universality of timed P systems...

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9th International Conference on Bio-Inspired Computing - Theories and Applications, BIC-TA 2014

作者： Song, Bosheng P É Rez-Jim É Nez, Mario J. Pan, Linqiang Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China Department of Computer Science and Artificial Intelligence University of Sevilla Avda. Reina Mercedes s/n Sevilla41012 Spain

ISBN: (纸本)9783662450482

In this work, inspired from this biological motivation that in living cells, the execution time of different biological processes is difficult to know precisely and very sensitive to environmental factors that might be hard to control, the computational efficiency and universality of timed P systems with membrane creation are investigated. Specifically, we give a time-free solution to SAT problem by a family of P systems with membrane creation in the sense that the correctness of the solution is irrelevant to the times associated with the involved rules. We further show that time-free P systems with membrane creation are computationally universal. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Membranes

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A novel hybrid intelligence algorithm for solving combinatorial optimization problems

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Journal of Computing Science and Engineering 2014年第4期8卷 199-206页

作者： Deng, Wu Chen, Han Li, He Software Institute Dalian Jiaotong University Dalian China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China The Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science and Engineering Zigong China Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis Guangxi University for Nationalities Nanning China

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity. © 2014. The Korean Institute of Information Scientists and Engineers.

关键词： Genetic algorithms

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