Statistical Techniques for the Normalization and Segmentation of Structural MRI

• Activity Number: 474
• Type: Topic Contributed
• Date/Time: Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Section on Nonparametric Statistics
• Author(s): Russell Shinohara*+ and Elizabeth Sweeney and Ciprian M. Crainiceanu and Jeff Goldsmith and Daniel Reich
• Companies: Univ of Pennsylvania and Johns Hopkins University and The Johns Hopkins University and Columbia University and National Institute of Neurological Disorders & Stroke
• Keywords: imaging ; MRI ; segmentation ; normalization

Abstract

While computed tomography and other imaging techniques are measured in absolute units with physical meaning, magnetic resonance images are expressed in arbitrary units that are difficult to interpret and differ between study visits and subjects. Much work in the image processing literature has centered on histogram matching and other histogram mapping techniques, but little focus has been on normalizing images to have biologically interpretable units. We explore this key goal for statistical analysis and the impact of normalization on cross-sectional and longitudinal segmentation of pathology.