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Summary: COMPARISON OF RECONSTRUCTION ALGORITHMS IN COMPRESSED SENSING
APPLIED TO BIOLOGICAL IMAGING
Yoann Le Montagner1,2
, Elsa Angelini2
, Jean-Christophe Olivo-Marin1
1
Institut Pasteur, Unité d'Analyse d'Images Quantitative, France
2
Institut Telecom, Telecom ParisTech, CNRS LTCI, France
ABSTRACT
In this paper, we propose a short presentation of the compressed
sensing imaging framework, along with a review of recent appli-
cations in the biomedical imaging field. One of the critical issue that
used to hinder the application of compressed sensing in a bioimag-
ing context is the computational cost of the underlying image re-
construction process. However, some recently published algorithms
manage to overcome this difficulty, leading to acceptable reconstruc-
tion computational times. We illustrate with simulations on biolog-
ical images of fluorescence microscopy a comparison of three re-
construction algorithms, evaluating data fidelity and computational
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