Posted By: NITRC ADMIN - Sep 2, 2012
Tool/Resource: Neuroinformatics - The Journal
 

Abstract  
Mapping brain structure in relation to neurological development, function, plasticity, and disease is widely considered to be one of the most essential challenges for opening new lines of neuro-scientific inquiry. Recent developments with MRI analysis of structural connectivity, anatomical brain segmentation, cortical surface parcellation, and functional imaging have yielded fantastic advances in our ability to probe the neurological structure-function relationship in vivo. To date, the image analysis efforts in each of these areas have typically focused on a single modality. Here, we extend the cortical reconstruction using implicit surface evolution (CRUISE) methodology to perform efficient, consistent, and topologically correct analyses in a natively multi-parametric manner. This effort combines and extends state-of-the-art techniques to simultaneously consider and analyze structural and diffusion information alongside quantitative and functional imaging data. Robust and consistent estimates of the cortical surface extraction, cortical labeling, diffusion-inferred contrasts, diffusion tractography, and subcortical parcellation are demonstrated in a scan-rescan paradigm. Accompanying this demonstration, we present a fully automated software system complete with validation data.

  • Content Type Journal Article
  • Category Original Article
  • Pages 1-13
  • DOI 10.1007/s12021-012-9159-9
  • Authors
    • Bennett A. Landman, Department of Electrical Engineering, Vanderbilt University, 2301 Vanderbilt Pl., Station B, PO Box 351679, Nashville, TN 37235-1679, USA
    • John A. Bogovic, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
    • Aaron Carass, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
    • Min Chen, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
    • Snehashis Roy, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
    • Navid Shiee, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
    • Zhen Yang, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
    • Bhaskar Kishore, The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
    • Dzung Pham, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
    • Pierre-Louis Bazin, Department of Neurophysics, Max Plank Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
    • Susan M. Resnick, Laboratory of Personality and Cognition, National Institute on Aging, Baltimore, MD, USA
    • Jerry L. Prince, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA


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