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The level set method offers many advantages over e.g. meshes for modelling and visual effects, but a naïve implementation is both computationally expensive and memory intensive. Narrow band level sets alleviate both issues but are still limited by the ...

The identification of nonlinear systems is a complex task. This article presents a method comparison between the new Fuzzy Adaptive Neurons (FAN), Radial Basis Function Network (RBF), and Adaptive Network-Based Fuzzy Inference System (ANFIS). The ...

We study the connections between spectral clustering and the problems of maximum margin clustering, and estimation of the components of level sets of a density function. Specifically, we obtain bounds on the eigenvectors of graph Laplacian matrices in ...

Swelling media (e.g., gels, tumors) are usually described by mechanical constitutive laws (e.g., Hooke or Darcy laws). However, constitutive relations of real swelling media are not well-known. Here, we take an opposite route and consider a simple packing ...

The revolution of digital imaging has led to an explosion in the information produced. The segmentation framework is composed of three stages. First, we use (BSDM) to extract the region of interest brain; this is a pre-segmentation of brain tissues. In ...

We study the behavior of the first eigenfunction of the Dirichlet Laplacian on a planar convex domain near its maximum. We show that the eccentricity and orientation of the superlevel sets of the eigenfunction stabilize as they approach the maximum, ...

We present a new efficient algorithm for computing signed distance fields by means of the Fast Sweeping Method. Unlike existing algorithms ours is explicitly designed to explore the benefits of sparse (vs dense) grids as well as concurrency, i.e. mutli-...

The signed distance function $d$ to an embedded (hyper-)surface $\Gamma$ is required in the analysis and implementation of some higher-order methods for the numerical treatment of partial differential equations on surfaces. Two algorithms for the ...

In this paper, we first define interval-valued intuitionistic fuzzy parameterized soft sets by combining the interval-valued intuitionistic fuzzy sets and the soft sets from parametrization point of view. By using soft level sets we then construct a ...

In this paper, we present a framework for image segmentation based on parametrized active contours. The evolving contour is parametrized according to a reduced set of control points that form a closed polygon and have a clear visual interpretation. The ...

We present a novel approach to non-rigid objects contour tracking in this paper based on a supervised level set model (SLSM). In contrast to most existing trackers that use bounding box to specify the tracked target, the proposed method extracts the ...

Level sets have been established as highly versatile implicit surface representations, with widespread use in graphics applications including modeling and dynamic simulation. Nevertheless, level sets are often presumed to be limited, compared to ...

Segmenting an image into an arbitrary number of coherent regions is at the core of image understanding. Many formulations of the segmentation problem have been suggested over the past years. These formulations include, among others, axiomatic functionals, ...

BACKGROUND: Breast thermography is a potential imaging method for the early detection of breast cancer. The pathological conditions can be determined by measuring temperature variations in the abnormal breast regions. Accurate delineation of breast ...

This paper presents a fast converging Riemannian steepest descent method for nonparametric statistical active contour models, with application to image segmentation. Unlike other fast algorithms, the proposed method is general and can be applied to any ...

An automatic multi-organ segmentation method using hierarchical-shape-prior guided level sets is proposed. The hierarchical shape priors are organized according to the anatomical hierarchy of the human body, so that major structures with less population ...

In this study, a novel probabilistic, geometric and dynamic shape‐based level sets method is proposed. The shape prior is coupled with the intensity information to enhance the segmentation results. The two‐dimensional principal component analysis method ...

A class of inverse problems for the identification of an unknown geometric object from given measurements is considered. A concept for object imaging based on optimality conditions and level sets is introduced which provides high resolution properties of the ...

We have developed a novel hierarchical data structure for the efficient representation of sparse, time-varying volumetric data discretized on a 3D grid. Our “VDB”, so named because it is a Volumetric, Dynamic grid that shares several characteristics ...