Gradual Generalization of Nautical Chart Contours with a Cube B-Spline Snake Model

—B-spline snake methods have been used in cartographic generalization in the past decade, particularly in the generalization of navigational charts where this method yields good results with respect to the shoal-bias rules for generalization of chart contours. However, previous studies only show generalization results at particular generalization (or scale) levels, and the user can only see two conditions: before the generalization and after generalization, but nothing in between. This paper presents an improved method of using B-spline snakes for generalization in the context of nautical charts, where the generalization process is done gradually, and the user can see the complete process of the generalization

An Automatic Level Set Based Liver Segmentation from MRI Data Sets

A fast and accurate liver segmentation method is a challenging work in medical image analysis area. Liver segmentation is an important process for computer-assisted diagnosis, pre-evaluation of liver transplantation and therapy planning of liver tumors. There are several advantages of magnetic resonance imaging such as free form ionizing radiation and good contrast visualization of soft tissue. Also, innovations in recent technology and image acquisition techniques have made magnetic resonance imaging a major tool in modern medicine. However, the use of magnetic resonance images for liver segmentation has been slow when we compare applications with the central nervous systems and musculoskeletal. The reasons are irregular shape, size and position of the liver, contrast agent effects and similarities of the gray values of neighbor organs. Therefore, in this study, we present a fully automatic liver segmentation method by using an approximation of the level set based contour evolution from T2 weighted magnetic resonance data sets. The method avoids solving partial differential equations and applies only integer operations with a two-cycle segmentation algorithm. The efficiency of the proposed approach is achieved by applying the algorithm to all slices with a constant number of iteration and performing the contour evolution without any user defined initial contour. The obtained results are evaluated with four different similarity measures and they show that the automatic segmentation approach gives successful results

Variational segmentation of vector-valued images with gradient vector flow

International audienceIn this paper, we extend the gradient vector flow field for robust variational segmentation of vector-valued images. Rather than using scalar edge information, we define a vectorial edge map derived from a weighted local structure tensor of the image that enables the diffusion of the gradient vectors in accurate directions through the 4DGVF equation. To reduce the contribution of noise in the structure tensor, image channels are weighted according to a blind estimator of contrast. The method is applied to biological volume delineation in dynamic PET imaging, and validated on realistic Monte Carlo simulations of numerical phantoms as well as on real images

Automatic Active Contour Modelling and Its Potential Application for Non-Destructive Testing

Active contouring techniques are very useful in medical imaging, digital mapping, non-destructive ultrasonic evaluation, etc. Therefore, we try to explore and investigate the advanced automatic active contouring methods, which can benefit the aforementioned applications. In this thesis work, we study the automatic active contour models adopted for the object characterization, whose extensions could include the potential defect analysis in the ultrasonic non-destructive testing. The active contouring scheme (also called a snake) or an energy minimizing spline, is an algorithm which is very sensitive to the manually marked initial points, and thereby requires an expertly operation. Therefore, we make new research endeavors to handle this major problem and design a new expert-free snake technique, which can lead to the completely automatic contouring technology for the future applications. Even though this initialization problem has been addressed in the literature for quite a while, to the best of our knowledge, there exists no satisfactory solution so far. In this thesis, we propose a novel initialization algorithm for the automatic snake technique, which can possess a faster convergence than other existing automatic contouring methods and also avoid the human operational error incurred in the conventional snake schemes

Advances in the numerical treatment of grain-boundary migration: Coupling with mass transport and mechanics

This work is based upon a coupled, lattice-based continuum formulation that was previously applied to problems involving strong coupling between mechanics and mass transport; e.g. diffusional creep and electromigration. Here we discuss an enhancement of this formulation to account for migrating grain boundaries. The level set method is used to model grain-boundary migration in an Eulerian framework where a grain boundary is represented as the zero level set of an evolving higher-dimensional function. This approach can easily be generalized to model other problems involving migrating interfaces; e.g. void evolution and free-surface morphology evolution. The level-set equation is recast in a remarkably simple form which obviates the need for spatial stabilization techniques. This simplified level-set formulation makes use of velocity extension and field re-initialization techniques. In addition, a least-squares smoothing technique is used to compute the local curvature of a grain boundary directly from the level-set field without resorting to higher-order interpolation. A notable feature is that the coupling between mass transport, mechanics and grain-boundary migration is fully accounted for. The complexities associated with this coupling are highlighted and the operator-split algorithm used to solve the coupled equations is described.Comment: 28 pages, 9 figures, LaTeX; Accepted for publication in Computer Methods in Applied Mechanics and Engineering. [Style and formatting modifications made, references added.