The maximum clique problem has diverse applications in the field of pattern recognition, computer vision, information processing etc. The connection between self-assembly and computation has implied that the tile asse...
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Randí;et al. proposed a famous spectral graphical representation of DNA sequences, and claimed that it avoids loss of information. In this paper we build two mathematical models for this graphical representation ...
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In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple sc...
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The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquir...
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The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearest-neighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.
Aimed at the deficiency of the resampling algorithm in PF, diversity measures ESS (effective sample size) and PDF (population diversity factor) are evaluated respectively. Combined with the estimation result, diversit...
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Aimed at the deficiency of the resampling algorithm in PF, diversity measures ESS (effective sample size) and PDF (population diversity factor) are evaluated respectively. Combined with the estimation result, diversity measures PDF is used for adaptively tuning the resampling threshold. By integrating the operation of particle mutation after resampling into PF and using the above mechanism of diversity guidance, the AMPF algorithm (Adaptive Mutation PF) is presented so as to assure the diversity of particle sets. With the simulation program using matlab 7.0 to track a single target motion from a fixed visual observation points, the performance of diversity measures and AMPF are evaluated and the validity of the proposed method is verified.
Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this work, a discrete structure representation ...
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Active contours have been one of the most successful methods for image segmentation during the last two decades, but one of the shortcomings of being unable to converge to concavity is a handicap to its effectiveness....
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Active contours have been one of the most successful methods for image segmentation during the last two decades, but one of the shortcomings of being unable to converge to concavity is a handicap to its effectiveness. In order to address this issue, the gradient vector flow (GVF) was put forth. Although there have been a great number of works on GVF, the image structure has seldom been incorporated into GVF algorithm. In this work, the image structure characterized by the Hessian matrix is incorporated into the GVF algorithm by reformulating the smoothness constraint of GVF into matrix form. In this way, the associated diffusion PDEs are anisotropic and the modified GVF snake can converge to very long concavity and preserve weak edge simultaneously. Experiments and comparisons are presented to demonstrate the properties of the proposed strategies.
This paper develops a volume-based technique, called Volume Sphering Analysis (VSA) which can process all acquired Magnetic Resonance (MR) image slices-formed image cube using only one set of training samples obtained...
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Designing and developing automatic techniques for magnetic resonance images (MR) for data analysis is very challenging. One popular and public available method, FAST (FMRIB Automatic Segmentation Tool) has been widely...
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Randić et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with ti...
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Randić et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with time complexity O(n 2 ), and find another important advantage in the representation: no degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the representation. The approach adopts four elements of covariance matrix as a descriptor, and is illustrated on the first exon of beta-globin genes from 11 different species.
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