Intensity normalization for improved MR images analysis
Florent Lalys 1 , Sushmita Datta 1 , Lorah Freeman 1 , Stacey S. Cofield 2 , Gary R. Cutter 2 , Fred D. Lublin 2 , Jerry S. Wolinsky 1 , and Ponnada A. Narayana 1
University of Texas Health Science Center at
Houston, Houston, Texas, United States,
of Alabama at Birmingham, Birmingham, Alabama, United
Intensity normalization (IN) is a critical step in image
processing, and particularly in MR image segmentation.
The IN technique described by Nyul et al. has been
routinely used in numerous studies, but never critically
evaluated on large cohorts or optimized for specific
applications. In this study we significantly improved
this IN method by identifying an optimal set of
parameters, and verified it on a large cohort of
multiple sclerosis patients. Our findings support
implementing different parameters than those used in the
majority of published studies.
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