Paper Info
Title
Distance-Intensity for image registration
Abstract
In this paper, a novel one-element voxel attribute, namely distance-intensity (DI), is defined for associating spatial information with image intensity for registration tasks. For each voxel in an image, the DI feature encodes spatial information at a global level, and is about the distance of the voxel to its closest object boundary, together with the original intensity information. Without the help of image segmentations, the computation of the DI map is carried out by applying a Poisson process on a vector field that combines both gradient and distance-gradient. Mutual information (MI) is adopted as a similarity measure on the DI feature space. A multi-resolution registration method is then used for aligning multi-modal images. Experimental results show that, as compared with the conventional MI-based method, the proposed method has longer capture ranges at different image resolutions. This leads to more robust registrations. Randomized registration experiments on clinical 3D CT, MR-T1 and MR-T2 datasets demonstrate that the new method gives higher success rates than the traditional MI-based method.
Year
DOI
Venue
2005
10.1007/11569541_29
CVBIA
Keywords
Field
DocType
di feature space,image registration,di map,conventional mi-based method,spatial information,new method,multi-resolution registration method,different image resolution,di feature,traditional mi-based method,image resolution,vector field,image segmentation,mutual information,feature space
Voxel,Computer vision,Feature vector,Similarity measure,Feature detection (computer vision),Pattern recognition,Computer science,Artificial intelligence,Mutual information,Kanade–Lucas–Tomasi feature tracker,Image resolution,Image registration
Conference
Volume
ISSN
ISBN
3765
0302-9743
3-540-29411-2
Citations 
PageRank 
References 
4
0.43
8
Authors
2
Name
Order
Citations
PageRank
Rui Gan118313.62
Albert C. S. Chung296472.07