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Excursions in Harmonic Analysis, Volume 2

Part of the series Applied and Numerical Harmonic Analysis pp 423-450

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A Harmonic Analysis View on Neuroscience Imaging

  • Paul Hernandez—HerreraAffiliated withComputational Biomedicine Lab, Department of Computer Science, University of Houston Email author 
  • , David JiménezAffiliated withDepartment of Mathematics, University of Houston
  • , Ioannis A. KakadiarisAffiliated withComputational Biomedicine Lab, Department of Computer Science, University of Houston
  • , Andreas KoutsogiannisAffiliated withDepartment of Mathematics, University of Athens, Greece
  • , Demetrio LabateAffiliated withDepartment of Mathematics, University of Houston
  • , Fernanda LaezzaAffiliated withDepartment of Pharmacology and Toxicology, University of Texas Medical Branch
  • , Manos PapadakisAffiliated withDepartment of Mathematics, University of Houston

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Abstract

After highlighting some of the current trends in neuroscience imaging, this work studies the approximation errors due to varying directional aliasing, arising when 2D or 3D images are subjected to the action of orthogonal transformations. Such errors are common in 3D images of neurons acquired by confocal microscopes. We also present an algorithm for the construction of synthetic data (computational phantoms) for the validation of algorithms for the morphological reconstruction of neurons. Our approach delivers synthetic data that have a very high degree of fidelity with respect to their ground-truth specifications.

Keywords

Synthetic tubular data Synthetic dendrites Directional aliasing Approximation error Dendritic arbor segmentation Confocal microscopy