Single-shot volumetric fluorescence imaging with neural fields
Abstract
Single-shot volumetric fluorescence (SVF) imaging offers a significant advantage over traditional imaging methods that require scanning across multiple axial planes, as it can capture biological processes with high temporal resolution. The key challenges in SVF imaging include requiring sparsity constraints, eliminating depth ambiguity in the reconstruction, and maintaining high resolution across a large field of view. We introduce the QuadraPol point spread function (PSF) combined with neural fields, an approach for SVF imaging. This method utilizes a custom polarizer at the back focal plane and a polarization camera to detect fluorescence, effectively encoding the three-dimensional scene within a compact PSF without depth ambiguity. In addition, we propose a reconstruction algorithm based on the neural field technique that provides improved reconstruction quality compared with classical deconvolution methods. QuadraPol PSF, combined with neural fields, significantly reduces the acquisition time of a conventional fluorescence microscope by ∼20 times and captures a 100-mm³ cubic volume in one shot. We validate the effectiveness of both our hardware and algorithm through all-in-focus imaging of bacterial colonies on sand surfaces and visualization of plant root morphology. Our approach offers a powerful tool for advancing biological research and ecological studies.
Copyright and License
© The Authors. Published by SPIE and CLP under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Acknowledgement
The work reported in this paper is supported by the Resnick Sustainability Institute and the Heritage Medical Research Institute (Grant No. HMRI-15-09-01) at Caltech. We thank Tara Chari for constructing the E. coli strain harboring mScarlet-I. We also thank Daniel Wagenaar from the Caltech Neurotechnology Lab for the assistance in fabricating the custom polarizer and Panlang Lyu for the helpful discussions.
Data Availability
The data underlying this study are openly available from OSF ( https://osf.io/4a5ws/) and by request, the code is available at GitHub ( https://github.com/hwzhou2020/SVF/).
Supplemental Material
Supplemental document : AP_7_2_026001_ds001.pdf
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Additional details
- Resnick Sustainability Institute
- California Institute of Technology
- Heritage Medical Research Institute HMRI-15-09-01
- Available
-
2025-02-25Published online
- Caltech groups
- Division of Engineering and Applied Science (EAS), Division of Biology and Biological Engineering (BBE)
- Publication Status
- Published