Title
Voxel Similarity Measures for 3D Serial MR Brain Image Registration
Abstract
We investigated 7 different similarity measures for rigid body registration of serial MR brain scans. To assess their accuracy we used a set of 33 clinical 3D serial MR images, manually segmented by a radiologist to remove deformable extra-dural tissue, and also simulated brain model data. For each measure we determined the consistency of registration transformations for both sets of segmented and unsegmented data. The difference images produced by registration with and without segmentation were visually inspected by two radiologists in a blinded study. We have shown that of the measures tested, those based on joint entropy produced the best consistency and seemed least sensitive to the presence of extra-dural tissue. For this data the difference in accuracy of these joint entropy measures, with or without brain segmentation, was within the threshold of visually detectable change in the difference images.
Year
DOI
Venue
1999
10.1007/3-540-48714-X_48
IPMI
Keywords
Field
DocType
difference image,brain segmentation,registration transformation,rigid body registration,serial MR brain,simulated brain model data,unsegmented data,best consistency,deformable extra-dural tissue,extra-dural tissue,Serial MR Brain Image,Voxel Similarity Measures
Brain segmentation,Voxel,Blinded study,Computer vision,Pattern recognition,Computer science,Segmentation,Joint entropy,Artificial intelligence,Neuroimaging,Brain model,Image registration
Conference
Volume
Issue
ISSN
19
2
0278-0062
ISBN
Citations 
PageRank 
3-540-66167-0
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Mark Holden11386.75
Derek L G Hill22823441.79
Erika R. E. Denton329026.66
Jo M. Jarosz400.34
Tim C. S. Cox5857.82
David J. Hawkes64262470.26