For the simulation of fiber systems, there exist several stochastic models: systems of straight nonoverlapping fibers, systems of overlapping bending fibers, or fiber systems created by sedimentation. However, there i...
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For the simulation of fiber systems, there exist several stochastic models: systems of straight nonoverlapping fibers, systems of overlapping bending fibers, or fiber systems created by sedimentation. However, there is a lack of models providing dense, nonoverlapping fiber systems with a given random orientation distribution and a controllable level of bending. We introduce a new stochastic model in this paper that generalizes the force-biased packing approach to fibers represented as chains of balls. The starting configuration is modeled using random walks, where two parameters in the multivariate von Mises–Fisher orientation distribution control the bending. The points of the random walk are associated with a radius and the current orientation. The resulting chains of balls are interpreted as fibers. The final fiber configuration is obtained as an equilibrium between repulsion forces avoiding crossing fibers and recover forces ensuring the fiber structure. This approach provides high volume fractions up to 72.0075%.
The objective of semantic segmentation in microscopic images is to extract the cellular, nuclear or tissue components. This problem is challenging due to the large variations of these components features (size, shape,...
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The objective of semantic segmentation in microscopic images is to extract the cellular, nuclear or tissue components. This problem is challenging due to the large variations of these components features (size, shape, orientation or texture). In this paper we improve the technique presented in [17] used to identify the epithelial nuclei (crypt) against interstitial nuclei in microscopic images taken from colon tissues. In the proposed enhanced approach, the crypt inner boundary is detected using the closing morphological pyramid instead of morphological hierarchy. The outer crypt border is determined by the epithelial nuclei, overlapped by the maximal isoline of the inner boundary. The use of sampling in building the pyramid offers computational efficiency, reduces the amount of used memory, increase the robustness and preserve the quality results. An analysis of the two approaches is performed considering the number of pixels processed to create each level. Also the relation between the levels of the hierarchical structures is established.
image degradation due to motion is a known problem in Positron Emission Tomography (PET). To reduce motion artifacts in PET, gating based techniques were found applicable. In pure respiratory gated PET, each gate stil...
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image degradation due to motion is a known problem in Positron Emission Tomography (PET). To reduce motion artifacts in PET, gating based techniques were found applicable. In pure respiratory gated PET, each gate still contains cardiac motion. Analogously, pure cardiac gated PET images still contain respiratory motion. Hence, we make use of dual (joint respiratory and cardiac) gating to further reduce the amount of motion contained in the images. The inclusion of non-rigid cardiac motion leads to intensity modulations caused by the Partial Volume Effect (PVE). To overcome the intensity modulations we identified and considered the mass-preserving property of PET images in the Variational Algorithm for Mass-Preserving image REgistration (VAMPIRE). The aim of this paper is the elimination of both cardiac and respiratory motion in thoracic dual gated PET without a loss of statistic. The strategy of our proposed motion correction approach is: 1) Dual gating, 2) Mass-preserving motion estimation (VAMPIRE), and 3) Averaging of the aligned images. In a patient study we showed that the proposed mass-preserving motion correction strategy significantly removes motion artifacts in cardiac PET. VAMPIRE achieved accurate results that resemble cardiac and respiratory motion across all patients.
Part I of this special issue is devoted to the physical layer, MAC layer, and physical-link cross-layer design technologies of vehicular communications and networks. There are 21 papers in this issue.
Part I of this special issue is devoted to the physical layer, MAC layer, and physical-link cross-layer design technologies of vehicular communications and networks. There are 21 papers in this issue.
We prove a general sufficient condition for a noise benefit in the expectation-maximization (EM) algorithm. Additive noise speeds the average convergence of the EM algorithm to a local maximum of the likelihood surfac...
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We prove a general sufficient condition for a noise benefit in the expectation-maximization (EM) algorithm. Additive noise speeds the average convergence of the EM algorithm to a local maximum of the likelihood surface when the noise condition holds. The sufficient condition states when additive noise makes the signal more probable on average. The performance measure is Kullback relative entropy. A Gaussian-mixture problem demonstrates the EM noise benefit. Corollary results give other special cases when noise improves performance in the EM algorithm.
The robust control problem for a class of continuous-time Markov switched linear systems with Wiener process disturbance with linear fractional uncertainties via switched state feedback and switched dynamic output fee...
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In the past decade there has been a great interest in a synthesis-based model for signals, based on sparse and redundant representations. Such a model assumes that the signal of interest can be composed as a linear co...
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In the past decade there has been a great interest in a synthesis-based model for signals, based on sparse and redundant representations. Such a model assumes that the signal of interest can be composed as a linear combination of few columns from a given matrix (the dictionary). An alternative analysis-based model can be envisioned, where an analysis operator multiplies the signal, leading to a cosparse outcome. In this paper, we consider this analysis model, in the context of a generic missing data problem (e.g., compressed sensing, inpainting, source separation, etc.). Our work proposes a uniqueness result for the solution of this problem, based on properties of the analysis operator and the measurement matrix. This paper also considers two pursuit algorithms for solving the missing data problem, an L1-based and a new greedy method. Our simulations demonstrate the appeal of the analysis model, and the success of the pursuit techniques presented.
The popular formulas of evaluating the similarity of digital watermarks have serious drawbacks: when the similarity degree is 1, the watermarks are not unique. This paper firstly analyzes the drawbacks in the popular ...
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We prove that independent fuzzy systems can uniformly approximate Bayesian posterior probability density functions by approximating prior and likelihood probability densities as well as hyperprior probability densitie...
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We prove that independent fuzzy systems can uniformly approximate Bayesian posterior probability density functions by approximating prior and likelihood probability densities as well as hyperprior probability densities that underly priors. This triply fuzzy function approximation extends the recent theorem for uniformly approximating the posterior density by approximating just the prior and likelihood densities. This allows users to state priors and hyper-priors in words or rules as well as to adapt them from sample data. A fuzzy system with just two rules can exactly represent common closed-form probability densities so long as they are bounded. The function approximators can also be neural networks or any other type of uniform function approximator.
In this paper, we investigate the interference mitigation from a cross-layer perspective for a cognitive radio (CR) multiple-input multiple-output (MIMO) network coexisting with a primary time-division-duplexing (TDD)...
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In this paper, we investigate the interference mitigation from a cross-layer perspective for a cognitive radio (CR) multiple-input multiple-output (MIMO) network coexisting with a primary time-division-duplexing (TDD) system. The channel allocation in the media access control (MAC) layer and a subspace-based precoding scheme in the physical layer of the CR network are jointly considered to minimise the interference to the primary user and maximise the CR throughput. Two distributed cross-layer algorithms, namely, joint iterative channel allocation and precoding (JICAP) and non-iterative channel allocation and precoding (NICAP), are proposed for the cases with and without channel information among CR nodes, respectively. Moreover, a channel estimation scheme is also proposed to enable the NICAP. The effectiveness of the proposed algorithms over non-cross-layer counterpart is demonstrated via simulations.
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