Motivation: In fluorescence microscopy, single-molecule localization microscopy (SMLM) techniques aim at localizing with high-precision high-density fluorescent molecules by stochastically activating and imaging small subsets of blinking emitters. Super resolution plays an important role in this field since it allows to go beyond the intrinsic light diffraction limit. Results: In this work, we propose a deep learning-based algorithm for precise molecule localization of high-density frames acquired by SMLM techniques whose 2-based loss function is regularized by non-negative and 0-based constraints. The 0 is relaxed through its continuous exact 0 (CEL0) counterpart. The arising approach, named DeepCEL0, is parameter-free, more flexible, faster and provides more precise molecule localization maps if compared to the other state-of-the-art methods. We validate our approach on both simulated and real fluorescence microscopy data.

Cascarano, P., Comes, M.c., Sebastiani, A., Mencattini, A., Loli Piccolomini, E., Martinelli, E. (2022). DeepCEL0 for 2D single-molecule localization in fluorescence microscopy. BIOINFORMATICS, 38(5), 1411-1419 [10.1093/bioinformatics/btab808].

DeepCEL0 for 2D single-molecule localization in fluorescence microscopy

Mencattini A.;Martinelli E.
2022-01-01

Abstract

Motivation: In fluorescence microscopy, single-molecule localization microscopy (SMLM) techniques aim at localizing with high-precision high-density fluorescent molecules by stochastically activating and imaging small subsets of blinking emitters. Super resolution plays an important role in this field since it allows to go beyond the intrinsic light diffraction limit. Results: In this work, we propose a deep learning-based algorithm for precise molecule localization of high-density frames acquired by SMLM techniques whose 2-based loss function is regularized by non-negative and 0-based constraints. The 0 is relaxed through its continuous exact 0 (CEL0) counterpart. The arising approach, named DeepCEL0, is parameter-free, more flexible, faster and provides more precise molecule localization maps if compared to the other state-of-the-art methods. We validate our approach on both simulated and real fluorescence microscopy data.
2022
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/07 - MISURE ELETTRICHE ED ELETTRONICHE
Settore ING-INF/01 - ELETTRONICA
English
Cascarano, P., Comes, M.c., Sebastiani, A., Mencattini, A., Loli Piccolomini, E., Martinelli, E. (2022). DeepCEL0 for 2D single-molecule localization in fluorescence microscopy. BIOINFORMATICS, 38(5), 1411-1419 [10.1093/bioinformatics/btab808].
Cascarano, P; Comes, Mc; Sebastiani, A; Mencattini, A; Loli Piccolomini, E; Martinelli, E
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/307778
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