Paper Info
Title
Fast medical image segmentation through an approximation of narrow-band B-spline level-set and multiresolution
Abstract
We have recently proposed a new level-set formulation, where the level-set is modelled as a continuous parametric function expressed in a B-spline basis. We propose in this paper to adapt this formalism to the class of narrow-band level-set methods, where the implicit function evolves only around its zero-level. For this purpose, we propose to model the interface by two lists of boundary points and we express the level-set evolution into the B-spline framework. We show that the flexibility of the method makes the algorithm well suited to the segmentation of 2-D and 3-D medical images. In particular, we introduce a multiresolution implementation of the method, yielding an efficient algorithm in term of computational time. The behavior of this approach is illustrated on medical images from various fields.
Year
DOI
Venue
2009
10.1109/ISBI.2009.5192979
Boston, MA
Keywords
Field
DocType
computerised tomography,image segmentation,medical image processing,splines (mathematics),2D medical image segmentation,3D medical image segmentation,continuous parametric function,fast medical image segmentation,implicit function evolution,level set formulation,multiresolution implementation,narrow band B spline level set approximation,B-spline,Level-set,Multiresolution
B-spline,Spline (mathematics),Computer vision,Parametric equation,Pattern recognition,Segmentation,Computer science,Level set,Implicit function,Image segmentation,Artificial intelligence,Image resolution
Conference
ISSN
ISBN
Citations 
1945-7928 E-ISBN : 978-1-4244-3932-4
978-1-4244-3932-4
1
PageRank 
References 
Authors
0.35
5
2
Name
Order
Citations
PageRank
Olivier Bernard169063.59
Denis Friboulet240332.65