While level sets have demonstrated a great potential for 3D medical image segmentation, their usefulness has been limited by two problems. First, 3D level sets are relatively slow ...
Aaron E. Lefohn, Joshua E. Cates, Ross T. Whitaker
Segmentation is a fundamental problem in medical image analysis. The use of prior knowledge is often considered to address the ill-posedness of the process. Such a process consists...
We propose a new Bayesian, stochastic tracking algorithm for the segmentation of blood vessels from 3D medical image data. Inspired by the recent developments in particle filterin...
David Lesage, Elsa D. Angelini, Isabelle Bloch, Ga...
In this paper we present a system that combines the benefits of 3D deformable models and level set methods for medical volume segmentation. Our 3D deformable model is a very comp...
Derek R. Magee, Andrew J. Bulpitt, Elizabeth Berry
This paper presents the first segmentation operation defined within the 3D topological map framework. Firstly we show how a traditional segmentation algorithm, found in the literat...