Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy

Abstract Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introdu...

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التفاصيل البيبلوغرافية

المؤلفون الرئيسيون:	Min Guo, Yicong Wu, Chad M. Hobson, Yijun Su, Shuhao Qian, Eric Krueger, Ryan Christensen, Grant Kroeschell, Johnny Bui, Matthew Chaw, Lixia Zhang, Jiamin Liu, Xuekai Hou, Xiaofei Han, Zhiye Lu, Xuefei Ma, Alexander Zhovmer, Christian Combs, Mark Moyle, Eviatar Yemini, Huafeng Liu, Zhiyi Liu, Alexandre Benedetto, Patrick La Riviere, Daniel Colón-Ramos, Hari Shroff
التنسيق:	Artigo
اللغة:	Inglês
منشور في:	Nature Portfolio 2025-01-01
سلاسل:	Nature Communications
الوصول للمادة أونلاين:	https://doi.org/10.1038/s41467-024-55267-x
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!