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Reconstruction of the human cerebral cortex robust to white matter lesions: Method and validation
Authors:Navid Shiee  Pierre‐Louis Bazin  Jennifer L. Cuzzocreo  Chuyang Ye  Bhaskar Kishore  Aaron Carass  Peter A. Calabresi  Daniel S. Reich  Jerry L. Prince  Dzung L. Pham
Affiliation:1. Image Analysis and Communication Laboratory, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland;2. Center for Neuroscience and Regenerative Medicine, Henry M. Jackson Foundation for Advancement of Military Medicine, Bethesda, Maryland;3. Department of Neurophysics, Max Planck Institutes for Human Cognitive and Brain Sciences, Leipzig, Germany;4. Department of Neurology, Johns Hopkins University, Baltimore, Maryland;5. Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland
Abstract:Cortical atrophy has been reported in a number of diseases, such as multiple sclerosis and Alzheimer's disease, that are also associated with white matter (WM) lesions. However, most cortical reconstruction techniques do not account for these pathologies, thereby requiring additional processing to correct for the effect of WM lesions. In this work, we introduce CRUISE+, an automated process for cortical reconstruction from magnetic resonance brain images with WM lesions. The process extends previously well validated methods to allow for multichannel input images and to accommodate for the presence of WM lesions. We provide new validation data and tools for measuring the accuracy of cortical reconstruction methods on healthy brains as well as brains with multiple sclerosis lesions. Using this data, we validate the accuracy of CRUISE+ and compare it to another state‐of‐the‐art cortical reconstruction tool. Our results demonstrate that CRUISE+ has superior performance in the cortical regions near WM lesions, and similar performance in other regions. Hum Brain Mapp 35:3385–3401, 2014. © 2013 Wiley Periodicals, Inc .
Keywords:cortical reconstruction  WM lesions  multiple sclerosis  lesion segmentation  cortical thickness
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