Modeling Stroke Lesions in Diffusion Weighted Images Using 2D Random Field Theory

We present a unified statistical framework for quantifying a collection of stroke lesion images that have been segmented in diffusion weighted images. Although Bernoulli models are often used in modeling a collection of binary images, the Bernoulli models actually break down for testing statistical significance of common overlap. To remedy the limitation of the Bernoulli models, we propose to adapt the random field theory often used in whole brain morphometric techniques to stroke lesion images.