The hypergraph partitioning problem has many applications in scientific computing and provides a more accurate inter-processor communication model for distributed systems than the equivalent graph problem. In this paper, we propose a sequential multi-level hypergraph partitioning algorithm. The algorithm makes novel use of the technique of rough set clustering in categorising the vertices of th...

This paper addresses the issue of accurate lesion segmentation in retinal imagery, using level set methods and a novel stopping mechanism an elementary features scheme. Specifically, the curve propagation is guided by a gradient map built using a combination of histogram equalization and robust statistics. The stopping mechanism uses elementary features gathered as the curve deforms over time, ...

In this paper, we first draw a connection between a level set algorithm and k-Means plus nonlinear diffusion preprocessing. Then, we exploit this link to develop a new hybrid numerical technique for segmentation that draws on the speed and simplicity of k-Means procedures, and the robustness of level set algorithms. The proposed method retains spatial coherence on initial data characteristic of...

We show that electrical impedance tomography (EIT) image reconstruction algorithms based on the Level Set (LS) method are suitable for real data, which is breathing data in our application. The LS based reconstruction method (LSRM) helps track fast topologically changing interfaces, which are typically smoothed by traditional voxel based reconstruction method (VBRM), during the monitoring proce...

The level set method may be used as a strongest pawn for segmentation of a tumor to achieve an accurate estimation of its volume. The level set method is a numeric technique for tracking interfaces and shapes. In this method, equation parameters are being set or speed function is being set. A threshold based method is introduced for tumor segmentation. In this paper, tumor segmentation and its ...

The level set method [1] is a popular technique for tracking moving interfaces in several disciplines including computer vision and fluid dynamics. However, despite its high flexibility, the original level set method is limited by two important numerical issues. Firstly, the level set method does not implicitly preserve the level set function as a distance function, which is necessary to estima...

The ambiguity and complexity of medical cerebrovascular image makes the skeleton gained by conventional skeleton algorithm discontinuous, which is sensitive at the weak edges, with poor robustness and too many burrs. This paper proposes a cerebrovascular image skeleton extraction algorithm based on Level Set model, using Euclidean distance field and improved gradient vector flow to obtain two d...

Introduction Brain region extraction is to segment brain region from nonbrain regions in magnetic resonance (MR) images. The segmented brain is usually used for measuring individual cortex thickness and brain volume, monitoring the development of the brain, and surface-based analysis. Brain region extraction is, therefore, an important step for various applications above mentioned. We present a...

Level set methods are the numerical techniques for tracking interfaces and shapes. They have been successfully used in image segmentation. A new variational level set evolving algorithm without re-initialization is presented in this paper. It consists of an internal energy term that penalizes deviations of the level set function from a signed distance function, and an external energy term that ...