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Abstract #1586

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

1 University of Texas Health Science Center at Houston, Houston, Texas, United States, 2 University of Alabama at Birmingham, Birmingham, Alabama, United States

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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