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bioRxiv · 10.1101/587485

Single-shot autofocus microscopy using deep learning

Pinkard, H.·Phillips, Z.·Babakhani, A.·Fletcher, D. A.·Waller, L.
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Abstract

Maintaining an in-focus image over long time scales is an essential and non-trivial task for a variety of microscopic imaging applications. Here, we present an autofocusing method that is inexpensive, fast, and robust. It requires only the addition of one or a few off-axis LEDs to a conventional transmitted light microscope. Defocus distance can be estimated and corrected based on a single image under this LED illumination using a neural network that is small enough to be trained on a desktop CPU in a few hours. In this work, we detail the procedure for generating data and training such a network, explore practical limits, and describe relevant design principles governing the illumination source and network architecture.

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Pinkard, H., Phillips, Z., Babakhani, A., Fletcher, D. A., Waller, L.. 2019-03-23. Single-shot autofocus microscopy using deep learning. https://doi.org/10.1101/587485

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