Premium
New methods of MR image intensity standardization via generalized scale
Author(s) -
Madabhushi Anant,
Udupa Jayaram K.
Publication year - 2006
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2335487
Subject(s) - standardization , intensity (physics) , scale (ratio) , medical imaging , medical physics , computer science , artificial intelligence , computer vision , optics , physics , quantum mechanics , operating system
Image intensity standardization is a post‐acquisition processing operation designed for correcting acquisition‐to‐acquisition signal intensity variations (non‐standardness) inherent in Magnetic Resonance (MR) images. While existing standardization methods based on histogram landmarks have been shown to produce a significant gain in the similarity of resulting image intensities, their weakness is that in some instances the same histogram‐based landmark may represent one tissue, while in other cases it may represent different tissues. This is often true for diseased or abnormal patient studies in which significant changes in image intensity characteristics may occur. In an attempt to overcome this problem, in this paper, we present two new intensity standardization methods based on two scale concepts developed in Madabhushi et al. [Computer Vision Image Understanding 101, 100–121 (2006)] for image processing applications. These scale concepts are utilized in this paper to accurately determine principal tissue regions within MR images. Landmarks derived from these regions are used to perform intensity standardization. The new methods were qualitatively and quantitatively evaluated on a total of 67 clinical three dimensional (3D) MR images corresponding to four different protocols and to normal, Multiple Sclerosis (MS), and brain tumor patient studies. The new scale‐based methods were found to be better than the existing methods, with a significant improvement observed for severely diseased and abnormal patient studies.