3D endogenous visualization and segmentation of brain neural networks in living mice at micron level resolution

Ziv Lautman; Yonatan Winetraub; Eran Blacher; Itamar Terem; Edwin Yuan; Caroline Yu; Adelaida Chibukhchyan; James H. Marshel; Adam de la Zerda

doi:10.1117/12.2583190

5 March 2021 3D endogenous visualization and segmentation of brain neural networks in living mice at micron level resolution

Ziv Lautman, Yonatan Winetraub, Eran Blacher, Itamar Terem, Edwin Yuan, Caroline Yu, Adelaida Chibukhchyan, James H. Marshel, Adam de la Zerda

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Proceedings Volume 11629, Optical Techniques in Neurosurgery, Neurophotonics, and Optogenetics; 1162911 (2021) https://doi.org/10.1117/12.2583190
Event: SPIE BiOS, 2021, Online Only

Abstract

Optical Coherence Tomography (OCT) is a promising research tool for neuroimaging. However, persistent challenges remain in following a large population of neurons and axonal tracts over time and across the entire depth due to system limitations. Here we introduce a label-free highly stable OCT system configuration and a novel segmentation algorithm that enable a longitudinal study of white matter axonal tracts and neuron cell bodies in a mouse brain, across 0.7 mm depth, in vivo. The system configuration enabled the acquisition of high-resolution images, which reveals thousands of neuron cell bodies across the entire volume and their interactions with multiple white matter axon tracts.

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Ziv Lautman, Yonatan Winetraub, Eran Blacher, Itamar Terem, Edwin Yuan, Caroline Yu, Adelaida Chibukhchyan, James H. Marshel, and Adam de la Zerda "3D endogenous visualization and segmentation of brain neural networks in living mice at micron level resolution", Proc. SPIE 11629, Optical Techniques in Neurosurgery, Neurophotonics, and Optogenetics, 1162911 (5 March 2021); https://doi.org/10.1117/12.2583190

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KEYWORDS

Brain

Neural networks

Neurons

3D visualizations

Image segmentation

Optical coherence tomography

Visualization

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