A harmonic analysis view on neuroscience imaging

Paul Hernandez-Herrera, David Jiménez, Ioannis A. Kakadiaris, Andreas Koutsogiannis, Demetrio Labate, Fernanda Laezza, Manos Papadakis

Research output: Chapter in Book/Report/Conference proceedingChapter


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.

Original languageEnglish (US)
Title of host publicationApplied and Numerical Harmonic Analysis
PublisherSpringer International Publishing
Number of pages28
StatePublished - 2013

Publication series

NameApplied and Numerical Harmonic Analysis
ISSN (Print)2296-5009
ISSN (Electronic)2296-5017


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

ASJC Scopus subject areas

  • Applied Mathematics


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