ABSTRACT
Acute ischemic stroke is described as the sudden interruption of blood flow to the brain that results in the deprivation of oxygen and nutrients to the cells; and stroke duration directly increases the risk of permanent brain damage. Physicians are now looking at Magnetic Resonance Images (MRI) to identify precursors to strokes. There is a strong relationship between white matter lesions (WML) and risk of stroke, as well as correlations with Alzheimer's disease, and multiple sclerosis. ML are best seen in Fluid Attenuation Inversion Recovery (FLAIR). This chapter presents an efficient approach to WML segmentation. The algorithm focuses on the correction of PVA, yielding lesions which are segmented at subvoxel precision to produce boundaries that are ideal for reliable shape analysis. It examines the fundamentals of MRI and the FLAIR modality, and presents a framework for exploratory noise analysis, as well as methods for PVA-based WML segmentation and shape metric calculations.
