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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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A stability-based multicast routing algorithm for wireless ad hoc networks

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Journal of computers (Taiwan) 2017年第2期28卷 73-85页

作者： Zhang, Fan Yuan, Qi Li, Mingming Xu, Xinyan Xing, Jian Technical Department of Jinan Branch Shandong Cable Interactive Service LTD Jinan250014 China Shandong Province Key Laboratory of Medical Physics and Image Processing Technology School of Physics and Electronics Shandong Normal University Jinan250014 China Department of Substation Maintenance State Grid Weifang Power Supply Company Weifang261021 China Department of Computer Science and Technology Shandong College of Electronic Technology Jinan250200 China

The research on wireless mobile Ad hoc networks has attracted much attention over the past few years, and IP multicast technology supports data transmission from one or several sources to a certain group of receivers. PUMA, as a mesh-based multicast routing algorithm for Ad hoc networks, has been demonstrated to perform better compared with other protocols under high-speed situation. Moreover, node mobility has been one of the dominant factors causing loss of system performance so that the stability is necessary to be taken into account when designing routing protocols. In this paper, a novel stability-based multicast routing algorithm (SMRA) is developed on the basis of PUMA, where the robustness and the congestion are jointly considered. In order to determine the forwarding path and the mesh member status of each node, SMRA utilizes the power information and is implemented across physical layer and network layer. We compare SMRA with PUMA and another well-known tree-based multicast protocol MAODV. Simulation results show that the performance of the proposed algorithm is better than that of PUMA and MAODV in terms of packet delivery ratio and throughput with limited control overhead.

关键词： Network layers

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Semi-automated extraction of retinal blood vessel network with Bifurcation and crossover points 12th

Semi-automated extraction of retinal blood vessel network wi...

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12th International Symposium on Visual Computing, ISVC 2016

作者： Nougrara, Z. Kihal, N. Meunier, J. Faculty of Mathematics and Computer Science Department of Mathematics University of Sciences and Technology of Oran Oran Algeria Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB Algiers Algeria Department of Computer Science and Operations Research University of Montreal Montreal Canada

ISBN: (纸本)9783319508313

Among different retinal analysis tasks, blood vessel extraction plays an important role as it is often the first essential step before any measurement can be made for various applications such as biometric authentication or diagnosis of retinal vascular diseases. In this paper, we present a new method for extraction of blood vessel network with its nodes (bifurcation and crossover points) from retinal images. The first step is to identify pixels with homogeneous vessel elements with a set of four directional filters. Then another step is applied to extract local linear components assuming that a vessel is a set of short linear segments. Through an optimization process this information is combined to extract the vessel network and its nodes. The proposed algorithm was tested on the publicly available DRIVE retinal fundus image database. The experimental results show good precision, recal. The proposed algorithm was tested on the publicly available DRIVE retinal fundus image database. The experimental results show good precision, recall and F-measure compared to ground truth and a state-of-the-art algorithm for the same dataset. © Springer International Publishing AG 2016.

关键词： Blood vessels

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Constructing multi-modality and multi-classifier radiomics predictive models through reliable classifier fusion

arXiv

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arXiv 2017年

作者： Zhou, Zhiguo Zhou, Zhi-Jie Hao, Hongxia Li, Shulong Chen, Xi Zhang, You Folkert, Michael Wang, Jing Department of Radiation Oncology UT Southwestern Medical Center DallasTX United States High-Tech Institute of Xi'an Xi'an China Department of Information and Control Engineering Xi'an University of Technology Xi'an China School of Computer Science and Technology Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China School of Biomedical Engineering Southern Medical Unversity Guangzhou China Institute of Image Processing and Pattern Recognition Xi'an Jiaotong Unversity Xi'an China

Radiomics aims to extract and analyze large numbers of quantitative features from medical images and is highly promising in staging, diagnosing, and predicting outcomes of cancer treatments. Nevertheless, several challenges need to be addressed to construct an optimal radiomics predictive model. First, the predictive performance of the model may be reduced when features extracted from an individual imaging modality (e.g. PET, CT, MRI) are blindly combined into a single predictive model. Second, because many different types of classifiers are available to construct a predictive model, selecting an "optimal" classifier for a particular application is still challenging. In this work, we developed multi-modality and multi-classifier radiomics predictive models that address the aforementioned issues in currently available models. Specifically, a new reliable classifier fusion strategy was proposed to optimally combine output from different modalities and classifiers. In this strategy, modality-specific classifiers were first trained, and an analytic evidential reasoning (ER) rule was developed to fuse the output score from each modality to construct an optimal predictive model. One public datasets and two clinical case studies were performed to validate model performance. The experimental results indicated that the proposed ER rule based radiomics models outperformed the traditional models that rely on a single classifier or simply use combined features from different modalities. Copyright © 2017, The Authors. All rights reserved.

关键词： Diagnosis

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Membrane algorithm with genetic operation and VRPTW-based public optimization system 11th

Membrane algorithm with genetic operation and VRPTW-based pu...

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Duan, Yingying Zhou, Kang Qi, Huaqing Zhang, Zhiqiang School of Math and Computer Wuhan Polytechnic University Wuhan430023 China Department of Economics and Management Wuhan Polytechnic University Wuhan430023 China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789811036101

That combining membrane computing with optimization technology offers a new information interaction model for the research of problems in optimization filed. Based on this, a membrane algorithm owned six basic membranes is proposed to solve the defects of the slow convergence and the small diversity in solving vehicle routing problem with time window. In order to further improve the efficiency and the precision, some new rules are designed: for the former problem, a node classifier is introduced to improve the efficiency by filtering directly a plenty of in-feasible solutions;two methods for the latter problems: an uncertain segment crossover is designed in the corresponding membrane in order to explore directly two feasible segments and segment-node insertion operation is introduced in order to make two individuals inserted synchronously another path. In order to verify the effectiveness of the algorithm, a series of experiments are designed. Known through the results of experiments that these two properties of membranes make the search ability of the algorithm improving quickly for local and global exploration and node classifier improves effectively the running efficiency of this algorithm, which proves that membrane algorithm can accelerate the convergence speed and increase diversity of population. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Membranes

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Improved multi-step iterative algorithms for the fixed points of strongly pseudo-contractive mappings 11th

Improved multi-step iterative algorithms for the fixed point...

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Liu, Jiangrong Zhou, Kang Zeng, Shan Qi, Huaqing Song, Bosheng Wu, Tingfang Department of Math and Computer Wuhan Polytechnic University WuhanHubei430023 China Department of Economics and Management Wuhan Polytechnic University WuhanHubei430023 China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology WuhanHubei430074 China

ISBN: (纸本)9789811036132

In Banach Spaces, we introduce a new improved multi-step iterative algorithm for the fixed points of strongly pseudo-contractive mappings, by proving the convergence for modified Mann iterative sequence, and that the multi-step iterative sequence and Mann iterative scheme are equivalent. We prove the convergence of iterative sequences generalized by the improved multi-step iterative algorithms. The results extend and improve the corresponding related results. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Banach spaces

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An image threshold segmentation algorithm with hybrid evolutionary mechanisms based on membrane computing 11th

An image threshold segmentation algorithm with hybrid evolut...

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Liu, Shuo Zhou, Kang Zeng, Shan Qi, Huaqing Wu, Tingfang Department of Math and Computer Wuhan Polytechnic University WuhanHubei430023 China Department of Economics and Management Wuhan Polytechnic University WuhanHubei430023 China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology WuhanHubei430074 China

ISBN: (纸本)9789811036101

Focused on the contradiction between selective pressure and population diversity in the optimization algorithm using hybrid evolutionary mechanisms, this paper proposes a membrane image threshold segmentation algorithm based on the idea of membrane computing. The proposal uses a hybrid tissue P system of three one-level-membranestructure (OLMS) membranes in which genetic algorithm (GA) and particle swarm optimal algorithm (PSO) are used as evolution operator. The proposed algorithm uses the communication rules and transfer rules to establish the interactions among the membranes, and then enhances the diversity of population in the system and improves the convergence of the algorithm. After comparing with the conventional methods, simulation results and dynamic behavior analysis show that the proposal evidently improve the validity and feasibility of the image segmentation algorithm. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Genetic algorithms

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Consensus algorithms for biased labeling in crowdsourcing

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Information Sciences 2017年 382-383卷 254-273页

作者： Jing Zhang Victor S. Sheng Qianmu Li Jian Wu Xindong Wu School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 P. R. China Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing 210094 P. R. China Department of Computer Science University of Central Arkansas Conway AR 72035 USA Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 P. R. China Institute of Intelligent Information Processing and Application Soochow University Suzhou 215006 P. R. China School of Computing and Informatics University of Louisiana at Lafayette LA 70504 USA

Although it has become an accepted lay view that when labeling objects through crowdsourcing systems, non-expert annotators often exhibit biases, this argument lacks sufficient evidential observation and systematic empirical study. This paper initially analyzes eight real-world datasets from different domains whose class labels were collected from crowdsourcing systems. Our analyses show that biased labeling is a systematic tendency for binary categorization; in other words, for a large number of annotators, their labeling qualities on the negative class (supposed to be the majority) are significantly greater than are those on the positive class (minority). Therefore, the paper empirically studies the performance of four existing EM-based consensus algorithms , DS, GLAD, RY, and ZenCrowd, on these datasets. Our investigation shows that all of these state-of-the-art algorithms ignore the potential bias characteristics of datasets and perform badly although they model the complexity of the systems. To address the issue of handling biased labeling, the paper further proposes a novel consensus algorithm, namely adaptive weighted majority voting (AWMV), based on the statistical difference between the labeling qualities of the two classes. AWMV utilizes the frequency of positive labels in the multiple noisy label set of each example to obtain a bias rate and then assigns weights derived from the bias rate to negative and positive labels. Comparison results among the five consensus algorithms (AWMV and the four existing) show that the proposed AWMV algorithm has the best overall performance. Finally, this paper notes some potential related topics for future study.

关键词：

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Convex cone volume analysis for finding endmembers in hyperspectral imagery

Convex cone volume analysis for finding endmembers in hypers...

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作者： Chang, Chein-I Xiong, Wei Chen, Shih-Yu Information and Technology College Dalian Maritime University Dalian China School of Physics and Optoelectronic Engineering Xidian University Xian China Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County BaltimoreMD21250 United States Department of Computer Science and Information Management Providence University Taichung Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

This paper presents a new approach, called convex cone volume analysis (CCVA), which can be considered as a partially constrained-abundance (abundance non-negativity constraint) technique to find endmembers. It can be shown that finding the maximal volume of a convex cone in the original data space is equivalent to finding the maximal volume of a simplex in a hyperplane. As a result, the CCVA can take advantage of many recently developed fast computational algorithms developed for N-FINDR to derive their counterparts for CCVA. © Copyright 2016 Inderscience Enterprises Ltd.

关键词： Spectroscopy

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Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

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Scientific data 2021年第1期8卷 242页

作者： Julien Cohen-Adad Eva Alonso-Ortiz Mihael Abramovic Carina Arneitz Nicole Atcheson Laura Barlow Robert L Barry Markus Barth Marco Battiston Christian Büchel Matthew Budde Virginie Callot Anna J E Combes Benjamin De Leener Maxime Descoteaux Paulo Loureiro de Sousa Marek Dostál Julien Doyon Adam Dvorak Falk Eippert Karla R Epperson Kevin S Epperson Patrick Freund Jürgen Finsterbusch Alexandru Foias Michela Fratini Issei Fukunaga Claudia A M Gandini Wheeler-Kingshott Giancarlo Germani Guillaume Gilbert Federico Giove Charley Gros Francesco Grussu Akifumi Hagiwara Pierre-Gilles Henry Tomáš Horák Masaaki Hori James Joers Kouhei Kamiya Haleh Karbasforoushan Miloš Keřkovský Ali Khatibi Joo-Won Kim Nawal Kinany Hagen H Kitzler Shannon Kolind Yazhuo Kong Petr Kudlička Paul Kuntke Nyoman D Kurniawan Slawomir Kusmia René Labounek Maria Marcella Laganà Cornelia Laule Christine S Law Christophe Lenglet Tobias Leutritz Yaou Liu Sara Llufriu Sean Mackey Eloy Martinez-Heras Loan Mattera Igor Nestrasil Kristin P O'Grady Nico Papinutto Daniel Papp Deborah Pareto Todd B Parrish Anna Pichiecchio Ferran Prados Àlex Rovira Marc J Ruitenberg Rebecca S Samson Giovanni Savini Maryam Seif Alan C Seifert Alex K Smith Seth A Smith Zachary A Smith Elisabeth Solana Y Suzuki George Tackley Alexandra Tinnermann Jan Valošek Dimitri Van De Ville Marios C Yiannakas Kenneth A Weber Ii Nikolaus Weiskopf Richard G Wise Patrik O Wyss Junqian Xu NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. jcohen@polymtl.ca. Functional Neuroimaging Unit CRIUGM Université de Montréal Montreal QC Canada. jcohen@polymtl.ca. Mila - Quebec AI Institute Montreal QC Canada. jcohen@polymtl.ca. NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. Department of Radiology Swiss Paraplegic Centre Nottwil Switzerland. Centre for Advanced Imaging The University of Queensland Brisbane Australia. Department of Radiology University of British Columbia Vancouver BC Canada. Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown MA USA. Department of Radiology Harvard Medical School Boston MA USA. Harvard-Massachusetts Institute of Technology Health Sciences & Technology Cambridge MA USA. School of Information Technology and Electrical Engineering The University of Queensland Brisbane Australia. NMR Research Unit Queen Square MS Centre UCL Queen Square Institute of Neurology Faculty of Brain Sciences University College London London UK. Department of Systems Neuroscience University Medical Center Hamburg-Eppendorf Hamburg Germany. Department of Neurosurgery Medical College of Wisconsin Milwaukee WI USA. Aix-Marseille Univ CNRS CRMBM Marseille France. APHM Hopital Universitaire Timone CEMEREM Marseille France. Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center Nashville TN USA. Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada. CHU Sainte-Justine Research Centre Montreal QC Canada. Centre de Recherche CHUS CIMS Sherbrooke Canada. Sherbrooke Connectivity Imaging Lab (SCIL) Computer Science department Université de Sherbrooke Sherbrooke Canada. Université de Strasbourg CNRS ICube Strasbourg France. UHB - University Hospital Brno and Masaryk University Department of Radiology and Nuclear

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