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Medical image segmentation based on immune clonal optimization

Medical image segmentation based on immune clonal optimizati...

引用

IEEE International Conference on intelligent Computing and intelligent Systems (ICIS)

作者： Wenping Ma Licheng Jiao Ronghua Shang Fujia Zhao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

ISBN: (纸本)9781424447374;9781424447541

Based on the clonal selection theory of artificial immune system, a novel optimal entropy threshold medical image segmentation method is proposed, in which, the affinity function is the optimal entropy threshold, and the medical image segmentation is considered as a optimization problem, clonal operator effectively enlarges searching range, supplies the diversity of solutions and can find the optimal threshold. This paper applies new algorithm to the challenging application: gray matter/white matter segmentation in MRI images, the algorithm is depicted in detail and the convergence is proven, the performance and computational complexity of the algorithm are described by quantitative analysis. Experiment results demonstrate the potential of the algorithm for medical image segmentation.

关键词： Biomedical imaging image segmentation Immune system Entropy Artificial immune systems Optimization methods Magnetic resonance imaging Computational complexity image analysis Performance analysis

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Design RF diplexer by directional immune clonal selection algorithm

Design RF diplexer by directional immune clonal selection al...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Qiuyi Wu Licheng Jiao Yangyang Li Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

Based on the clonal selection theory of the immune system, a novel optimal algorithm, called a directional immune clonal selection algorithm (DICSA), is proposed to design RF diplexer. In DICSA, antibody is proliferated and divided into a set of subpopulation groups. In the antibody's updating, the clonal mutation is applied to avoid premature convergences. The clonal selection realizes the information communication between the subpopulation groups so as to improve the search efficiency. DICSA is applied to a practical problem, designing RF diplexer. The results show that DICSA has stable performance during the optimization process with a satisfactory result.

关键词： Algorithm design and analysis Radio frequency Filters Laboratories Information processing Design optimization Circuits Artificial intelligence Artificial immune systems Least squares methods

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Hybrid Immune Algorithm with intelligent recombination

Hybrid Immune Algorithm with intelligent recombination

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Congress on Evolutionary Computation

作者： Maoguo Gong Licheng Jiao Wenping Ma Ronghua Shang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

In this study, we introduce a hybrid immune algorithm based on the intelligent recombination operator and clonal selection algorithm. The intelligent recombination operator uses orthogonal experimental design for factor analysis which identifies the potential gene segments from two individuals to improve their antigenic affinities. The new algorithm, termed as Hybrid Immune Algorithm with Recombination (HIAR), can avoid the decrease of gene diversity in evolutionary process. It evaluates the hamming distance before recombination and uses the two individuals which have the largest hamming distance between each other to implement intelligent recombination operator. It is shown empirically that HIAR has better performance in solving benchmark functions as compared with intelligent Evolutionary Algorithm and Clonal Selection Algorithm.

关键词： Immune system Competitive intelligence Design for experiments Hamming distance Computational intelligence Approximation algorithms Design optimization Algorithm design and analysis Evolutionary computation Protection

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Human Detection Based on Second Generation Bandelet Transform

Human Detection Based on Second Generation Bandelet Transfor...

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International Conference on Information Science and Engineering (ICISE)

作者： Hong Han Xing Wu Licheng Jiao Lichuan Yue Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

ISBN: (纸本)9781424449095

Base on geometric flow of images and the second generation bandelet transform, a new feature extraction method was proposed, and it was used to detect human in still images. In the paper, bandelet coefficients and their statistical values were extracted as the feature of human images, combined with Adaboost classifier to classify and detect human in images. In the proposed algorithm, some general statistical values of the bandelet coefficients were computed to enhance the classification capacity. The results of human detection experiments indicate that the proposed method can describe human characteristics and improve the performance of classifier effectively. It is very suitable for human detection in still images.

关键词： Humans Feature extraction Discrete wavelet transforms Neural networks Support vector machines Support vector machine classification image analysis Information science Laboratories Information processing

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Quantum-inspired evolutionary multicast algorithm

Quantum-inspired evolutionary multicast algorithm

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IEEE International Conference on Systems, Man and Cybernetics

作者： Yangyang Li Licheng Jiao Jingjing Zhao Qiuyi Wu Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

As a global optimizing algorithm, genetic algorithm (GA) is applied to solve the problem of multicast more and more. GA has more powerful searching ability than traditional algorithm, however its property of ¿prematurity¿ makes it difficult to get a good multicast tree. A quantum-inspired evolutionary algorithm (QEA) to deal with multicast routing problem is presented in this paper, which saliently solves the ¿prematurity¿ problem in genetic based multicast algorithm. Furthermore, in QEA, the individuals in a population are represented by multistate gene quantum bits and this representation has a better characteristic of generating diversity in population than any other representations. In the individual's updating, the quantum rotation gate strategy is applied to accelerate convergence. The algorithm has the property of simple realization and flexible control. The simulation results show that QEA has a better performance than CS and conventional GA.

关键词： Multicast algorithms Competitive intelligence Laboratories Information processing Evolutionary computation Routing Genetic algorithms Quality of service Quantum computing Heuristic algorithms

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Needle segmentation in 3D ultrasound images based on phase-grouping

Needle segmentation in 3D ultrasound images based on phase-g...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhao, Siying Qiu, Wu Ming, Yuchi Ding, Mingyue Institute of Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China Institute of Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Hubei 10086 China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China School of Life Science and Technology Huazhong University of Science and Technology Hubei 10086 China

ISBN: (纸本)9780819478085

Three Dimensional (3D) ultrasound images can provide spatial information to help doctors locate the needle position precisely in ultrasound-guided surgery. In this paper, we present a method called "3D Phase-grouping" to segment the needle inside the patient. The method is an extension from 2D phase-grouping to the 3D case via a new mathematic model-the outer products of adjacent orientation vectors. Firstly, the voxels with the same outer products of the gradient orientation vectors of the adjacent points are divided into Line Support Regions (LSR). Then, the needle is extracted with the 3D Least-Squares line fitting method in the maximal LSR. Synthetic and 3D ultrasound phantom data were tested. The segmentation results were evaluated by the angular deviation, position deviation and computational time. Compared with the 3D Hough transform, 3D Phase-Grouping is more accurate and faster without using pre-information. The computational complexity and robustness of the algorithm remain to be our future research topics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Needles

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Path planning using FMM with direction and curvature constrained

Path planning using FMM with direction and curvature constra...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Li, Shidong Ding, Mingyue Cai, Chao Institute for Pattern Recognition and Artificial Intelligence National Lab. for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China Hubei University for Nationalities Enshi Hubei 445000 China College of Life Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

It is difficult to meet both direction and curvature constraints for traditional Fast Marching (FM) method in path planning. Based on adjusting the cost function in Eiknoal equation-the control equation for FM, a new model for computing the integrated cost function was presented in this paper. A relationship formula about curvature radius was obtained and three kinds of adjusting strategies were given;two of them were used to modify the route to meet with the requires of turning constraint in this paper. Experiments showed that the improved model can be used to plan the path with FMM for agent such as unmanned aerial vehicle (UAV) or robot, which is limited to pass through the scene matching areas. And our preliminary experiments demonstrated that the strategies are feasible and efficient to obtain path with certain curvature radius. The model can also be used to represent the problem such as an aircraft flying in a flow field. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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A novel path planning method based on path network

A novel path planning method based on path network

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

ISBN: (纸本)9780819478085

Traditional path planning methods are too slow to meet the real-time requirement in practical applications. In order to solve this problem, an idea of path net was proposed in this paper. The path planning procedure is divided into two steps: network segment planning and segment assembling. The first step was done with Fast Marching Method, including port selection of segment and network segment planning. Second step, the A* searching method was chosen to select segments for assembling. Experiments demonstrated that our method can obtain an optimal route in a few of seconds after the start and goal are given while several minutes are needed for traditional methods. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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A weakly universal spiking neural P system

A weakly universal spiking neural P system

引用

International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Xiangxiang Zeng Chun Lu Linqiang Pan Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei China

Looking for small universal computing devices is a natural and well investigated topic in computer science. Recently, this topic was also investigated in the framework of spiking neural P systems. One of small universality results is that a small weakly universal extended spiking neural P system with 12 neurons was constructed. In this paper, a new way is introduced for simulating register machines by spiking neural P systems, where only one neuron is used for all instructions of register machine; in this way, we can use less neurons to construct universal spiking neural P system. Specifically, we give a smaller weakly universal spiking neural P system that uses extended rules and has only 9 neurons.

关键词： Neurons Tin Registers Biomembranes Computational modeling Encoding Decoding intelligent control control systems Computer science

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Reconstruction of images from compressive sensing based on the stagewise fast LASSO

Reconstruction of images from compressive sensing based on t...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wu, Jiao Liu, Fang Jiao, Licheng School of Computer Science and Technology Xidian University Xi'an 710071 China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xi'an 710071 China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China College of Sciences China Jiliang University Hangzhou 310018 China

ISBN: (纸本)9780819478092

Compressive sensing (CS) is a theory about that one may achieve a nearly exact signal reconstruction from the fewer samples, if the signal is sparse or compressible under some basis. The reconstruction of signal can be obtained by solving a convex program, which is equivalent to a LASSO problem with l1-formulation. In this paper, we propose a stage-wise fast LASSO (StF-LASSO) algorithm for the image reconstruction from CS. It uses an insensitive Huber loss function to the objective function of LASSO, and iteratively builds the decision function and updates the parameters by introducing a stagewise fast learning strategy. Simulation studies in the CS reconstruction of the natural images and SAR images widely applied in practice demonstrate that the good reconstruction performance both in evaluation indexes and visual effect can be achieved by StF-LASSO with the fast recovered speed among the algorithms which have been implemented in our simulations in most of the cases. Theoretical analysis and experiments show that StF-LASSO is a CS reconstruction algorithm with the low complexity and stability. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Compressed sensing

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