Paper Info
Title
Medical image registration based on fast and adaptive bidimensional empirical mode decomposition
Abstract
Image registration plays a crucial role in several areas, yet iconic registration methods are more efficient than those in geometrical registration, but they require great execution time. Regarding reduction in the execution time of iconic registration, the authors have proposed a new method based on mutual information while exploiting adaptive multiresolution decomposition, bidimensional empirical mode decomposition (BEMD) in its fast and adaptive version fast and adaptive BEMD (FABEMD). The idea is that instead of registering two images, the authors proceed to registration of the bidimensional intrinsic mode functions (BIMFs) that results from the FABEMD decomposition. The BIMF selected by the authors' algorithm is characterised by preservation of the general form of the image, and it contains a tone of grey levels lower than that of the original image, thus the number of combinations of the grey levels, used while calculating entropy is reduced, which in turn reduces execution time of the registration.
Year
DOI
Venue
2013
10.1049/iet-ipr.2012.0034
Image Processing, IET
Keywords
Field
DocType
entropy,image registration,image resolution,medical image processing,BIMF,FABEMD decomposition,adaptive multiresolution decomposition,bidimensional intrinsic mode functions,entropy,fast-and-adaptive bidimensional empirical mode decomposition,geometrical registration,grey levels,iconic registration,medical image registration
Computer vision,Pattern recognition,Computer science,Execution time,Artificial intelligence,Mutual information,Image resolution,Image registration,Hilbert–Huang transform
Journal
Volume
Issue
ISSN
7
6
1751-9659
Citations 
PageRank 
References 
9
0.68
6
Authors
3
Name
Order
Citations
PageRank
Jamal Riffi1203.97
Mohamed Adnane Mahraz290.68
Hamid Tairi35717.49