@inbook{9a420da903ec43d1bed728864398be20,
title = "A harmonic analysis view on neuroscience imaging",
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 = "Approximation error, Confocal microscopy, Dendritic arbor segmentation, Directional aliasing, Synthetic dendrites, Synthetic tubular data",
author = "Paul Hernandez-Herrera and David Jim{\'e}nez and Kakadiaris, {Ioannis A.} and Andreas Koutsogiannis and Demetrio Labate and Fernanda Laezza and Manos Papadakis",
note = "Funding Information: Acknowledgements This work was supported in part by NSF grants DMS 0915242, DMS 1005799, and DMS 1008900 and by NHARP grant 003652-0136-2009. Publisher Copyright: {\textcopyright} Springer Science+Business Media New York 2013.",
year = "2013",
doi = "10.1007/978-0-8176-8379-5_21",
language = "English (US)",
series = "Applied and Numerical Harmonic Analysis",
publisher = "Springer International Publishing",
number = "9780817683788",
pages = "423--450",
booktitle = "Applied and Numerical Harmonic Analysis",
edition = "9780817683788",
}