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13 March 2024 Resolution-improved self-supervised two-photon voltage imaging denoising
Chang Liu, Jelena Platisa, Xin Ye, Allison M. Ahrens, Ichun Anderson Chen, Ian G. Davison, Vincent A. Pieribone, Jerry L. Chen, Lei Tian
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Proceedings Volume PC12828, Neural Imaging and Sensing 2024; PC1282807 (2024) https://doi.org/10.1117/12.3003148
Event: SPIE BiOS, 2024, San Francisco, California, United States
Abstract
We present DeepVIDv2, a resolution-improved self-supervised voltage imaging denoising approach that achieves higher spatial resolution while preserving fast neuronal dynamics. While existing methods enhance signal-to-noise ratio (SNR), they compromise spatial resolution and result in blurry outputs. By disentangling spatial and temporal performance into two parameters, DeepVIDv2 overcomes the tradeoff faced by its predecessor. This advancement enables more effective analysis of high-speed, large-population voltage imaging data.
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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Chang Liu, Jelena Platisa, Xin Ye, Allison M. Ahrens, Ichun Anderson Chen, Ian G. Davison, Vincent A. Pieribone, Jerry L. Chen, and Lei Tian "Resolution-improved self-supervised two-photon voltage imaging denoising", Proc. SPIE PC12828, Neural Imaging and Sensing 2024, PC1282807 (13 March 2024); https://doi.org/10.1117/12.3003148
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KEYWORDS
Denoising
Two photon imaging
Signal to noise ratio
Spatial resolution
Image quality
Neurons
Temporal resolution
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