Super-resolution in confocal microscopy using generative adversarial networks with paired and unpaired data

S. Patra; C. Trujillo; A. Doblas

doi:10.1117/12.2652629

16 May 2023 Super-resolution in confocal microscopy using generative adversarial networks with paired and unpaired data

S. Patra, C. Trujillo, A. Doblas

Author Affiliations +

Proceedings Volume 12385, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXX; 123850A (2023) https://doi.org/10.1117/12.2652629
Event: SPIE BiOS, 2023, San Francisco, California, United States

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

Citation Download Citation

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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