<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">László Gábor Nyúl</style></author><author><style face="normal" font="default" size="100%">Jayaram K Udupa</style></author><author><style face="normal" font="default" size="100%">Punam K Saha</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Incorporating a measure of local scale in voxel-based 3-D image registration</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE TRANSACTIONS ON MEDICAL IMAGING</style></secondary-title><short-title><style face="normal" font="default" size="100%">IEEE T MED IMAGING</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2003///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">228 - 237</style></pages><isbn><style face="normal" font="default" size="100%">0278-0062</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a new class of approaches for rigid-body registrationand their evaluation in studying multiple sclerosis (MS) via 
multiprotocol magnetic resonance imaging (MRI). Three pairs of 
rigid-body registration algorithms were implemented, using 
cross-correlation and mutual information (MI), operating on 
original gray-level images, and utilizing the intermediate 
images resulting from our new scale-based method. In the scale 
image, every voxel has the local &quot;scale&quot; value assigned to it, 
defined as the radius of the largest ball centered at the voxel 
with homogeneous intensities. Three-dimensional image data of 
the head were acquired from ten MS patients for each of six MRI 
protocols. Images in some of the protocols were acquired in 
registration. The registered pairs were used as ground truth. 
Accuracy and consistency of the six registration methods were 
measured within and between protocols for known amounts of 
misregistrations. Our analysis indicates that there is no &quot;best&quot; 
method. For medium misregistration, the method using MI, for 
small add large misregistration the method using normalized 
cross-correlation performs best. For high-resolution data the 
correlation method and for low-resolution data the MI method, 
both using the original gray-level images, are the most 
consistent. We have previously demonstrated the use of local 
scale information in fuzzy connectedness segmentation and image 
filtering. Scale may also have potential for image registration 
as suggested by this work.
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><notes><style face="normal" font="default" size="100%">UT: 000182391600009ScopusID: 0038398636doi: 10.1109/TMI.2002.808358</style></notes></record></records></xml>