Implicit neural representations in light microscopy

Hauser SL, Brosig J, Murthy B, Attardo A, Kist A (2024)

Publication Type: Journal article

Publication year: 2024


Book Volume: 15

Pages Range: 2175-2186

Journal Issue: 4

DOI: 10.1364/BOE.515517


Three-dimensional stacks acquired with confocal or two-photon microscopy are crucial for studying neuroanatomy. However, high-resolution image stacks acquired at multiple depths are time-consuming and susceptible to photobleaching. In vivo microscopy is further prone to motion artifacts. In this work, we suggest that deep neural networks with sine activation functions encoding implicit neural representations (SIRENs) are suitable for predicting intermediate planes and correcting motion artifacts, addressing the aforementioned shortcomings. We show that we can accurately estimate intermediate planes across multiple micrometers and fully automatically and unsupervised estimate a motion-corrected denoised picture. We show that noise statistics can be affected by SIRENs, however, rescued by a downstream denoising neural network, shown exemplarily with the recovery of dendritic spines. We believe that the application of these technologies will facilitate more efficient acquisition and superior post-processing in the future.

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Hauser, S.L., Brosig, J., Murthy, B., Attardo, A., & Kist, A. (2024). Implicit neural representations in light microscopy. Biomedical Optics Express, 15(4), 2175-2186.


Hauser, Sophie Louise, et al. "Implicit neural representations in light microscopy." Biomedical Optics Express 15.4 (2024): 2175-2186.

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