A harmonic analysis view on neuroscience imaging

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

doi:10.1007/978-0-8176-8379-5_21

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 proceeding › Chapter

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.

Original language	English (US)
Title of host publication	Excursions in Harmonic Analysis
Subtitle of host publication	The February Fourier Talks at the Norbert Wiener Center
Publisher	Birkhauser Boston
Pages	423-450
Number of pages	28
Volume	2
ISBN (Electronic)	9780817683795
ISBN (Print)	9780817683788
DOIs	https://doi.org/10.1007/978-0-8176-8379-5_21
State	Published - Jan 1 2013

Keywords

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

ASJC Scopus subject areas

Mathematics(all)

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10.1007/978-0-8176-8379-5_21

Cite this

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AU - Hernandez-Herrera, Paul

AU - Jiménez, David

AU - Kakadiaris, Ioannis A.

AU - Koutsogiannis, Andreas

AU - Labate, Demetrio

AU - Laezza, Fernanda

AU - Papadakis, Manos

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Y1 - 2013/1/1

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AB - 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.

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KW - Confocal microscopy

KW - Dendritic arbor segmentation

KW - Directional aliasing

KW - Synthetic dendrites

KW - Synthetic tubular data

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A harmonic analysis view on neuroscience imaging

Abstract

Keywords

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