English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/96610
logo share SHARE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:


Robust elastic 2D/3D geometric graph matching

AuthorsSerradell, Eduard ; Kybic, Jan; Moreno-Noguer, Francesc ; Fua, Pascal
KeywordsGraph matching
Image registration
Issue Date2012
PublisherThe International Society for Optics and Photonics
CitationMedical Imaging 2012: Image Processing: 831408 (2012)
SeriesProceedings of SPIE 8314
AbstractWe present an algorithm for geometric matching of graphs embedded in 2D or 3D space. It is applicable for registering any graph-like structures appearing in biomedical images, such as blood vessels, pulmonary bronchi, nerve fibers, or dendritic arbors. Our approach does not rely on the similarity of local appearance features, so it is suitable for multimodal registration with a large difference in appearance. Unlike earlier methods, the algorithm uses edge shape, does not require an initial pose estimate, can handle partial matches, and can cope with nonlinear deformations and topological differences. The matching consists of two steps. First, we find an affine transform that roughly aligns the graphs by exploring the set of all consistent correspondences between the nodes. This can be done at an acceptably low computational expense by using parameter uncertainties for pruning, backtracking as needed. Parameter uncertainties are updated in a Kalman-like scheme with each match. In the second step we allow for a nonlinear part of the deformation, modeled as a Gaussian Process. Short sequences of edges are grouped into superedges, which are then matched between graphs. This allows for topological differences. A maximum consistent set of superedge matches is found using a dedicated branch-and-bound solver, which is over 100 times faster than a standard linear programming approach. Geometrical and topological consistency of candidate matches is determined in a fast hierarchical manner. We demonstrate the effectiveness of our technique at registering angiography and retinal fundus images, as well as neural image stacks.
DescriptionTrabajo presentado a la Medical Imaging celebrada en San Diego el 4 de febrero de 2012.
Publisher version (URL)http://dx.doi.org/10.1117/12.910573
Identifiersdoi: 10.1117/12.910573
isbn: 9780819489630
Appears in Collections:(IRII) Libros y partes de libros
Files in This Item:
File Description SizeFormat 
Robust elastic 2D 3D.pdf3,51 MBUnknownView/Open
Show full item record
Review this work

Related articles:

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.