3 years ago

MIMoSA: An Automated Method for Intermodal Segmentation Analysis of Multiple Sclerosis Brain Lesions

Melissa Lynne Martin, Peter A. Calabresi, Theodore D. Satterthwaite, John Muschelli, Russell T. Shinohara, Dzung L. Pham, Kristin A. Linn, Alessandra M. Valcarcel, Simon N. Vandekar

ABSTRACT

BACKGROUND AND PURPOSE

Magnetic resonance imaging (MRI) is crucial for in vivo detection and characterization of white matter lesions (WMLs) in multiple sclerosis. While WMLs have been studied for over two decades using MRI, automated segmentation remains challenging. Although the majority of statistical techniques for the automated segmentation of WMLs are based on single imaging modalities, recent advances have used multimodal techniques for identifying WMLs. Complementary modalities emphasize different tissue properties, which help identify interrelated features of lesions.

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