A new model for representing an unorganised 3D data points set is proposed. Based on superquadrics, this model allows to describe the points set with a union of superellipsoids. Two different segmentation and modeling methods are developed in order to determine the whole model: a region growing approach and a split and merge one. This second method leads to a low sensitive model compared to the...

Proposed in this paper is an efficient algorithm to remove self-intersections from the raw offset triangular mesh. The resulting regular mesh can be used in shape inflation, tool path generation, and process planning to name a few. Objective is to find the valid region set of triangles defining the outer boundary of the offset volume from the raw offset triangular mesh. Starting with a seed tri...

A new region growing method for finding the boundaries of blobs is presented. A unique feature of the method is that at each step, at most one pixel exhibits the required properties to join the region. The method uses two novel discontinuity measures, average contrast and peripheral contrast, to control the growing process.

Region growing and edge detection are two popular and common techniques used for image segmentation. Region growing is preferred over edge detection methods because it is more robust against low contrast problems and effectively addresses the connectivity issues faced by edge detectors. Edgebased techniques, on the other hand, can significantly reduce useless information while preserving the im...

In the context of an experimental virtual-reality surgical planning software platform, we propose a fully self-assessed adaptive region growing segmentation algorithm. Our method successfully delineates main tissues relevant to head and neck reconstructive surgery, such as skin, fat, muscle/organs, and bone. We rely on a standardized and selfassessed region-based approach to deal with a great v...

Multi-resolution and region-growing strategies have been successfully used in several fields of image processing. In this paper we investigate how these two strategies can be applied for binary tomography. We included these strategies into a reconstruction method using simulated annealing and tested these new methods on different images.

Though most approaches to protein comparison are based on their structure, several studies produced evidence of a strict correlation between the surface characteristics of proteins and the way they interact. Surface-based techniques for protein comparison typically require applying clustering algorithms to the punctual 3D description of the surface in order to produce a compact surface represen...

A comprehensive phylogenetic framework is indispensable for investigating the evolution of genomic features in mammals as a whole, and particularly in humans. Using the ENCODE sequence data, we estimated mammalian neutral evolutionary rates and selective pressures acting on conserved coding and noncoding elements. We show that neutral evolutionary rates can be explained by the generation time (...

With the amount of multitemporal and multiresolution images growing exponentially, the number of image segmentation applications is recently increasing and, simultaneously, new challenges arise. Hence, there is a need to explore new segmentation concepts and techniques that make use of the temporal dimension. This paper describes a spatio-temporal segmentation that adapts the traditional region...

algorithms or region growing are well-known, but they are In this paper we address the problem of ultrasound volume data segtnentation by means of active contours. The segmentation is performed on an slic~by-slice basis but exploiting the high correlation that exists across nearby slices. We have used active rays to alleviake the computational load of the optimization process. Classical energy ...