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Numerical tissue characterization in MS via standardization of the MR image intensity scale
Author(s) -
Ge Yulin,
Udupa Jayaram K.,
Nyúl Lázló G.,
Wei Luogang,
Grossman Robert I.
Publication year - 2000
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/1522-2586(200011)12:5<715::aid-jmri8>3.0.co;2-d
Subject(s) - histogram , intensity (physics) , segmentation , standardization , white matter , computer science , artificial intelligence , nuclear medicine , magnetic resonance imaging , biomedical engineering , image (mathematics) , computer vision , medicine , radiology , physics , optics , operating system
Abstract Image intensity standardization is a recently developed postprocessing method that is capable of correcting the signal intensity variations in MR images. We evaluated signal intensity of healthy and diseased tissues in 10 multiple sclerosis (MS) patients based on standardized dual fast spin‐echo MR images using a numerical postprocessing technique. The main idea of this technique is to deform the volume image histogram of each study to match a standard histogram and to utilize the resulting transformation to map the image intensities into standard scale. Upon standardization, the coefficients of variation of signal intensities for each segmented tissue (gray matter, white matter, lesion plaques, and diffuse abnormal white matter) in all patients were significantly smaller (2.3–9.2 times) than in the original images, and the same tissues from different patients looked alike, with similar intensity characteristics. Numerical tissue characterizability of different tissues in MS achieved by standardization offers a fixed tissue‐specific meaning for the numerical values and can significantly facilitate image segmentation and analysis. J. Magn. Reson. Imaging 2000;12:715–721. © 2000 Wiley‐Liss, Inc.