Computational microscopy for fast widefield deep-tissue fluorescence imaging using a commercial dual-cannula probe
Ekata Mitra1, Ruipeng Guo1, Soren Nelson2
1Department of Electrical & Computer Engineering, University of Utah, Salt Lake City, UT 84112, USA.
Abstract:
A solid-glass cannula serves as a micro-endoscope that can deliver excitation light deep inside tissue while also collecting emitted fluorescence. Then, we utilize deep neural networks to reconstruct images from the collected intensity distributions. By using a commercially available dual-cannula probe, and training a separate deep neural network for each cannula, we effectively double the field of view compared to prior work. We demonstrated ex vivo imaging of fluorescent beads and brain slices and in vivo imaging from whole brains. We clearly resolved 4 μm beads, with FOV from each cannula of 0.2 mm (diameter), and produced images from a depth of ~1.2 mm in the whole brain, currently limited primarily by the labeling. Since no scanning is required, fast widefield fluorescence imaging limited primarily by the brightness of the fluorophores, collection efficiency of our system, and the frame rate of the camera becomes possible.
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