<?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></authors></contributors><titles><title><style face="normal" font="default" size="100%">New variants of a method of MRI scale normalization</style></title><secondary-title><style face="normal" font="default" size="100%">LECTURE NOTES IN COMPUTER SCIENCE</style></secondary-title><short-title><style face="normal" font="default" size="100%">LECT NOTES COMPUT SCI</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year><pub-dates><date><style  face="normal" font="default" size="100%">1999///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">1613</style></volume><pages><style face="normal" font="default" size="100%">490 - 495</style></pages><isbn><style face="normal" font="default" size="100%">0302-9743</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">One of the major drawbacks of Magnetic Resonance Imaging (MRI)has been the lack of a standard and quantifiable interpretation 
of image intensities. This causes many difficulties in image 
display and analysis. We have devised a two-step method wherein 
all images can be transformed in such a way that for the same 
protocol and body region, in the transformed images similar 
intensities will have similar tissue meaning. Normalized images 
can be displayed with fixed windows without the need of per case 
adjustment. More importantly, extraction of quantitative 
information about healthy organs or about abnormities, such as 
tumors, can considerably be simplified. This paper introduces 
and compares new variants of this normalization method that can 
help to overcome some of the problems with the original method.
</style></abstract><notes><style face="normal" font="default" size="100%">UT: 000170515200051doi: 10.1007/3-540-48714-X_51In: Kuba A; Samal M; Todd-Pokropek A (szerk.)Information Processing in Medical Imaging: 16th International 
Conference, IPMI'99, Visegrád, Hungary, June/July 1999. 
Proceedings.
508 p.
Visegrád, Magyarország, 1999.06.28-1999.07.02.
Berlin; Heidelberg: Springer-Verlag, 1999. pp. 490-495.
(Lecture Notes in Computer Science; 1613.)
(ISBN:3-540-66167-0)
http://link.springer.com/book/10.1007/3-540-48714-X/page/1
</style></notes></record></records></xml>