Title
An adaptive fuzzy-inference-rule-based flexible model for automatic elastic image registration
Abstract
In this study, a fuzzy-inference-rule-based flexible model (FIR-FM) for automatic elastic image registration is proposed. First, according to the characteristics of elastic image registration, an FIR-FM is proposed to model the complex geometric transformation and feature variation in elastic image registration. Then, by introducing the concept of motion estimation and the corresponding sum-of-squared-difference (SSD) objective function, the parameter learning rules of the proposed model are derived for general image registration. Based on the likelihood objective function, particular attention is also paid to the derivation of parameter learning rules for the case of partial image registration. Thus, an FIR-FM-based automatic elastic image registration algorithm is presented here. It is distinguished by its 1) strong ability in approximating complex nonlinear transformation inherited from fuzzy inference; 2) efficiency and adaptability in obtaining precise model parameters through effective parameter learning rules; and 3) completely automatic registration process that avoids the requirement of manual control, as in many traditional landmark-based algorithms. Our experiments show that the proposed method has an obvious advantage in speed and is comparable in registration accuracy as compared with a state-of-the-art algorithm.
Year
DOI
Venue
2009
10.1109/TFUZZ.2009.2020154
IEEE T. Fuzzy Systems
Keywords
Field
DocType
solid modeling,learning artificial intelligence,fuzzy control,objective function,human factors,information technology,adaptive learning,approximation theory,image registration,rule based,motion estimation,medical diagnosis
Rule-based system,Pattern recognition,Computer science,Approximation theory,Geometric transformation,Solid modeling,Artificial intelligence,Motion estimation,Fuzzy control system,Adaptive learning,Machine learning,Image registration
Journal
Volume
Issue
ISSN
17
5
1063-6706
Citations 
PageRank 
References 
4
0.39
32
Authors
3
Name
Order
Citations
PageRank
Fu-lai Chung124434.50
Zhaohong Deng264735.34
Shitong Wang31485109.13