Paper Info
Title
Improving MMI with enhanced-FCM for the fusion of brain MR and SPECT images
Abstract
Recently, maximization mutual information (MMI) of image intensities has been proposed as a new matching criterion for automated multimodality image registration. However, the success of the MMI relies on the similarity of the histogram distribution between the images to be fused. This condition is usually hard to be achieved in practical application. Besides, MMI is time consuming because it needs to find an optimal solution about six parameters (three for shifts and three for rotations) during the registration process. To overcome these drawbacks of using the traditional MMI, a novel scheme, named improved MMI, which is based on fuzzy c-means (FCM) and MMI, is proposed. The experimental results, using MR and SPECT images, to confirm the superior performance of the proposed method in comparison with the traditional MMI method are also included.
Year
DOI
Venue
2004
10.1109/ICPR.2004.1334591
Biomedical Engineering: Applications, Basis and Communications
Field
DocType
ISSN
Computer vision,Histogram,Image fusion,Pattern recognition,Computer science,Fuzzy logic,Fusion,Fuzzy set,Artificial intelligence,Mutual information,Image registration,Maximization
Conference
1051-4651
Citations 
PageRank 
References 
2
0.45
5
Authors
2
Name
Order
Citations
PageRank
Chung-Hsien Huang1397.92
Jiann-Der Lee221134.02