title: Unified framework for anisotropic interpolation and smoothing of diffusion tensor images.
abstract: To enhance the performance of diffusion tensor imaging (DTI)-based fiber tractography, this study proposes a unified framework for anisotropic interpolation and smoothing of DTI data. The critical component of this framework is an anisotropic sigmoid interpolation kernel which is adaptively modulated by the local image intensity gradient profile. The adaptive modulation of the sigmoid kernel permits image smoothing in homogeneous regions and meanwhile guarantees preservation of structural boundaries. The unified scheme thus allows piece-wise smooth, continuous and boundary preservation interpolation of DTI data, so that smooth fiber tracts can be tracked in a continuous manner and confined within the boundaries of the targeted structure. The new interpolation method is compared with conventional interpolation methods on the basis of fiber tracking from synthetic and in vivo DTI data, which demonstrates the effectiveness of this unified framework.
authors.affiliation: Institute of Imaging Science, Vanderbilt University, Nashville, 1161 21st Avenue South, MCN CCC-1118, TN 37232-2657, USA. arabinda.mishra@vanderbilt.edu
authors.forename: Arabinda
authors.initials: A
authors.lastname: Mishra
authors.forename: Yonggang
authors.initials: Y
authors.lastname: Lu
authors.forename: Jingjing
authors.initials: J
authors.lastname: Meng
authors.forename: Adam W
authors.initials: AW
authors.lastname: Anderson
authors.forename: Zhaohua
authors.initials: Z
authors.lastname: Ding
mesh_terms: D000465:Algorithms; D016880:Anisotropy; D038524:Diffusion Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009412:Nerve Fibers / Q000502:physiology; D015203:Reproducibility of Results