Improving fluorescence lifetime imaging microscopy phasor accuracy using convolutional neural networks

Introduction: Although a powerful biological imaging technique, fluorescence lifetime imaging microscopy (FLIM) faces challenges such as a slow acquisition rate, a low signal-to-noise ratio (SNR), and high cost and complexity. To address the fundamental problem of low SNR in FLIM images, we demonstr...

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主要な著者:	Varun Mannam, Jacob P. Brandt, Cody J. Smith, Xiaotong Yuan, Scott Howard
フォーマット:	Artigo
言語:	Inglês
出版事項:	Frontiers Media S.A. 2023-12-01
シリーズ:	Frontiers in Bioinformatics
主題:	phasor lifetime synthesis fluorescence lifetime imaging microscopy (FLIM) lifetime image analysis convolutional neural networks (CNNs) phasor clustering method image segmentation
オンライン･アクセス:	https://www.frontiersin.org/articles/10.3389/fbinf.2023.1335413/full
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