Paper Info
Title
Learning-based multi-modal rigid image registration by using Bhattacharyya distances.
Abstract
Multi-modal image registration is a momentous technology in medical image processing and analysis. In order to improve the robustness and accuracy of multi-modal rigid image registration, a novel learning-based dissimilarity function is proposed in this paper. This novel dissimilarity function is based on measuring the dissimilarity between the joint intensity distribution of the testing image pair and the expected intensity distributions, which is learned from a registered image pair, with Bhattacharyya distances. Then, the aim of the registration process is to minimize the dissimilarity function. Eight hundred randomized CT - T1 registrations were performed and evaluated by the Retrospective Image Registration Evaluation (RIRE) project. The experimental results demonstrate that the proposed method can achieve higher robustness and accuracy, as compared with a closely related approach and a state-of-the-art method.
Year
DOI
Venue
2011
10.1109/IEMBS.2011.6090514
EMBC
Keywords
Field
DocType
robustness,rire project,dissimilarity function,image processing,learning (artificial intelligence),accuracy,learning based multimodal rigid image registration,joint intensity distribution,retrospective image registration evaluation project,image registration,bhattacharyya distances,medical image processing,image resolution,testing,learning artificial intelligence
Computer vision,Bhattacharyya distance,Pattern recognition,Image texture,Computer science,Image processing,Robustness (computer science),Artificial intelligence,Image resolution,Modal,Image registration
Conference
Volume
ISSN
ISBN
2011
1557-170X
978-1-4244-4122-8
Citations 
PageRank 
References 
3
0.38
6
Authors
2
Name
Order
Citations
PageRank
Ronald W. K. So1483.70
Albert C. S. Chung296472.07