In this paper, an unsupervised image segmentation technique is presented, which combines pyramidal image segmentation with the fuzzy c-means clustering algorithm. Each layer of the pyramid is split into a number of regions by a root labeling technique, and then fuzzy c-means is used to merge the regions of the layer with the highest image resolution. A cluster validity functional is used to find the optimal number of objects automatically. Segmentation of a number of synthetic as well as clinical images is illustrated and two fully automatic segmentation approaches are evaluated, which determine the left ventricular volume (LV) in 140 cardiovascular magnetic resonance (MR) images. First fuzzy c-means is applied without pyramids. In the second approach the regions generated by pyramidal segmentation are merged by fuzzy c-means. The correlation coefficients of manually and automatically defined LV lumen of all 140 and 20 end-diastolic images were equal to 0.86 and 0.79, respectively, when images were segmented with fuzzy c-means alone. These coefficients increased to 0.90 and 0.93 when the pyramidal segmentation was combined with fuzzy c-means. This method can be applied to any dimensional representation and at any resolution level of an image series. The evaluation study shows good performance in detecting LV lumen in MR images.

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Many segmentation methods for thoracic volume data require manual input in the form of a seed point, initial contour, volume of interest etc. The aim of the work presented here is to further automate this segmentation initialization step. In this paper an anatomical modeling and matching method is proposed to coarsely segment thoracic volume data into anatomically labeled regions. An anatomical model of the thorax is constructed in two steps: 1) individual organs are modeled with blended fuzzy implicit surfaces and 2) the single organ models are grouped into a tree structure with a solid modeling technique named constructive solid geometry (CSG). The combination of CSG with fuzzy implicit surfaces allows a hierarchical scene description by means of a boundary model, which characterizes the scene volume as a boundary potential function. From this boundary potential, an energy function is defined which is minimal when the model is registered to the tissue-air transitions in thoracic magnetic resonance imaging (MRI) data. This allows automatic registration in three steps: feature detection, initial positioning and energy minimization. The model matching has been validated in phantom simulations and on 15 clinical thoracic volume scans from different subjects. In 13 of these sets the matching method accurately partitioned the image volumes into a set of volumes of interest for the heart, lungs, cardiac ventricles, and thorax outlines. The method is applicable to segmentation of various types of thoracic MR-images, provided that a large part of the thorax is contained in the image volume.

Following the linear programming prescription of Ref. \cite{PRA72}, the $d\otimes d$ Bell diagonal entanglement witnesses are provided. By using Jamiolkowski isomorphism, it is shown that the corresponding positive maps are the generalized qudit Choi maps. Also by manipulating particular $d\otimes d$ Bell diagonal separable states and constructing corresponding bound entangled states, it is shown that thus obtained $d\otimes d$ BDEW's (consequently qudit Choi maps) are non-decomposable in certain range of their parameters.Comment: 22 page

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In this paper, considering a more realistic model for the carbon nanotube (CNT) conveying viscous fluid which is embedded in a visco-elastic medium, the effect of viscosity of the medium surrounding the CNT has been investigated. By taking into account the influence of the fluid viscosity and using the Navier-Stokes equations, the governing equation of motion has been derived and a new analytical technique based on the power series is presented for its vibration analysis. The frequency equation of the system is obtained by applying the boundary conditions. The influence of the medium parameters and the fluid viscosity on the natural frequencies of the CNT has been studied. The results show that the medium damping has a marked effect on the natural frequencies and the critical fluid velocity. Furthermore, by increasing the fluid viscosity, the natural frequencies and the critical fluid velocity increase. There is a good agreement between the results obtained through the proposed method and the data reported in the literature. The two main advantages of the proposed method are the applicability of the method to all kinds of the boundary conditions and its rapid convergence.