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Harnessing artificial intelligence to reduce phototoxicity in live imaging.
Gómez-de-Mariscal, Estibaliz; Del Rosario, Mario; Pylvänäinen, Joanna W; Jacquemet, Guillaume; Henriques, Ricardo.
Afiliación
  • Gómez-de-Mariscal E; Instituto Gulbenkian de Ciência, Oeiras 2780-156, Portugal.
  • Del Rosario M; Instituto Gulbenkian de Ciência, Oeiras 2780-156, Portugal.
  • Pylvänäinen JW; Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku 20500, Finland.
  • Jacquemet G; Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku 20500, Finland.
  • Henriques R; Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku 20520, Finland.
J Cell Sci ; 137(3)2024 02 01.
Article en En | MEDLINE | ID: mdl-38324353
ABSTRACT
Fluorescence microscopy is essential for studying living cells, tissues and organisms. However, the fluorescent light that switches on fluorescent molecules also harms the samples, jeopardizing the validity of results - particularly in techniques such as super-resolution microscopy, which demands extended illumination. Artificial intelligence (AI)-enabled software capable of denoising, image restoration, temporal interpolation or cross-modal style transfer has great potential to rescue live imaging data and limit photodamage. Yet we believe the focus should be on maintaining light-induced damage at levels that preserve natural cell behaviour. In this Opinion piece, we argue that a shift in role for AIs is needed - AI should be used to extract rich insights from gentle imaging rather than recover compromised data from harsh illumination. Although AI can enhance imaging, our ultimate goal should be to uncover biological truths, not just retrieve data. It is essential to prioritize minimizing photodamage over merely pushing technical limits. Our approach is aimed towards gentle acquisition and observation of undisturbed living systems, aligning with the essence of live-cell fluorescence microscopy.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / Inteligencia Artificial Idioma: En Revista: J Cell Sci Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / Inteligencia Artificial Idioma: En Revista: J Cell Sci Año: 2024 Tipo del documento: Article