Generalized Tensor-Based Morphometry of HIV/AIDS Using Multivariate Statistics on Deformation Tensors

• Published in: IEEE transactions on medical imaging Vol. 27; no. 1; pp. 129 - 141
• Main Authors: Lepore, Natasha, Brun, Caroline, Chou, Yi-Yu, Chiang, Ming-Chang, Dutton, Rebecca A., Hayashi, Kiralee M., Luders, Eileen, Lopez, Oscar L., Aizenstein, Howard J., Toga, Arthur W., Becker, James T., Thompson, Paul M.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2008; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acquired immune deficiency syndrome; Acquired immunodeficiency syndrome; Acquired Immunodeficiency Syndrome - pathology; Adult; AIDS; Algorithms; Brain; Brain - pathology; Computer Simulation; Data Interpretation, Statistical; Deformation; Determinants; Encephalitis, Viral - pathology; Female; HIV; HIV Infections - pathology; Human immunodeficiency virus; Humans; Image analysis; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Imaging, Three-Dimensional - methods; Information Storage and Retrieval - methods; Jacobian matrices; Jacobians; Lie groups; Magnetic analysis; Magnetic resonance imaging; magnetic resonance imaging (MRI); Magnetic Resonance Imaging - methods; Male; Manifolds; Mathematical analysis; Models, Neurological; Models, Statistical; Multivariate Analysis; Reproducibility of Results; Sensitivity and Specificity; Statistics; Studies; Tensile stress; Tensors; Testing

This paper investigates the performance of a new multivariate method for tensor-based morphometry (TBM). Statistics on Riemannian manifolds are developed that exploit the full information in deformation tensor fields. In TBM, multiple brain images are warped to a common neuroanatomical template via...