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Analysis of Brain Images with Pathological Changes

We present a new method for computing surface-based and voxel-based imaging biomarkers using 4D modeling of longitudinal MRI. We analyze the potential for clinical use of these biomarkers by correlating them with TBI-specific patient scores. Our preliminary results indicate that the proposed voxel-based biomarkers are correlated with clinical outcomes. Related publications: Analyzing imaging biomarkers for traumatic brain injury using 4D modeling of longitudinal MRI (IEEE ISBI 2013)

Longitudinal images with TBI present topological changes over time due to the effect of the impact force on tissue, skull, and blood vessels and the recovery process. We address this issue by defining a novel atlas construction scheme that explicitly models the effect of topological changes. Our method automatically estimates the probability of topological changes jointly with the personalized atlas. Related publications: Segmentation of Serial MRI of TBI patients using Personalized Atlas Construction and Topological Change Estimation [PDF] (IEEE ISBI 2012)

For quantitatively analyzing the recovery and treatment efficacy of MR images with Traumatic brain injury (TBI). We introduce a multimodal image segmentation framework for longitudinal TBI images. The framework is initialized through manual input of primary lesion sites at each time point, which are then refined by a joint approach composed of Bayesian segmentation and construction of a personalized atlas. Related publications: A Patient-Specific Segmentation Framework for Longitudinal MR Images of Traumatic Brain Injury [PDF] (SPIE Medical Imaging 2012)