Presentation + Paper
16 May 2023 Super-resolution in confocal microscopy using generative adversarial networks with paired and unpaired data
Author Affiliations +
Abstract
The advantages of confocal microscopy over widefield microscopy are their ability to produce optically sectioned images and their ability to produce multi-color imaging in which different organelles within the biological specimen are stained using multiple dyes, enabling colocalization studies. These features make confocal microscopy a widely used tool to provide valuable morphological and functional information within cells and tissues. One of the major drawbacks of confocal microscopy is its limited spatial resolution. Here, we train two generative adversarial networks using paired and unpaired data of low- and high-resolution images to improve the spatial resolution in confocal microscopy.
Conference Presentation
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. Patra, C. Trujillo, and A. Doblas "Super-resolution in confocal microscopy using generative adversarial networks with paired and unpaired data", Proc. SPIE 12385, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXX, 123850A (16 May 2023); https://doi.org/10.1117/12.2652629
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KEYWORDS
Confocal microscopy

Data modeling

Signal to noise ratio

Point spread functions

Education and training

Microscopes

Performance modeling

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