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A study on tensor and matrix models for super-resolution fluorescence microscopy

José Henrique de Morais Goulart 1 Laure Blanc-Féraud 1 Eric Debreuve 1 Sébastien Schaub 2
1 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : Super-resolution techniques for fluorescence microscopy areinvaluable tools for studying phenomena that take place atsub-cellular scales, thanks to their capability of overcominglight diffraction. Yet, achieving sufficient temporal resolutionfor imaging live-cell processes remains a challenging prob-lem. Exploiting the temporal fluctuations (blinking) of fluo-rophores is a promising approach that allows employing stan-dard equipment and harmless excitation levels. In this work,we study a novel constrained tensor modeling approach thattakes this temporal diversity into account to estimate the spa-tial distribution of fluorophores and their overall intensities.We compare this approach with an also novel matrix-basedformulation which promotes structured sparsity via a continu-ous approximation of the cardinality function, as well as withother state-of-the-art methods.
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Submitted on : Wednesday, October 9, 2019 - 2:30:46 PM
Last modification on : Wednesday, May 19, 2021 - 3:37:10 AM


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  • HAL Id : hal-02309659, version 1


José Henrique de Morais Goulart, Laure Blanc-Féraud, Eric Debreuve, Sébastien Schaub. A study on tensor and matrix models for super-resolution fluorescence microscopy. CAMSAP 2019 - IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Dec 2019, Le Gosier, Guadeloupe. ⟨hal-02309659⟩



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