@article {69719, title = {Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopyAbstract}, journal = {Nature Communications}, volume = {16}, year = {2025}, month = {Jan-12-2025}, abstract = {

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations. We use simulations and experiments to show that applying the trained {\textquoteleft}de-aberration{\textquoteright} networks outperforms alternative methods, providing restoration on par with adaptive optics techniques; and subsequently apply the networks to diverse datasets captured with confocal, light-sheet, multi-photon, and super-resolution microscopy. In all cases, the improved quality of the restored data facilitates qualitative image inspection and improves downstream image quantitation, including orientational analysis of blood vessels in mouse tissue and improved membrane and nuclear segmentation in\ C. elegans\ embryos.

}, doi = {10.1038/s41467-024-55267-x}, url = {https://www.nature.com/articles/s41467-024-55267-xhttps://www.nature.com/articles/s41467-024-55267-x.pdfhttps://www.nature.com/articles/s41467-024-55267-x.pdfhttps://www.nature.com/articles/s41467-024-55267-x}, author = {Guo, Min and Wu, Yicong and Hobson, Chad M. and Su, Yijun and Qian, Shuhao and Krueger, Eric and Christensen, Ryan and Kroeschell, Grant and Bui, Johnny and Chaw, Matthew and Zhang, Lixia and Liu, Jiamin and Hou, Xuekai and Han, Xiaofei and Lu, Zhiye and Ma, Xuefei and Zhovmer, Alexander and Combs, Christian and Moyle, Mark and Yemini, Eviatar and Liu, Huafeng and Liu, Zhiyi and Benedetto, Alexandre and La Riviere, Patrick and Col{\'o}n-Ramos, Daniel and Shroff, Hari} } @article {69792, title = {Volumetric imaging of the 3D orientation of cellular structures with a polarized fluorescence light-sheet microscope.}, journal = {Proc Natl Acad Sci }, volume = {122}, year = {2025}, month = {2025 Feb 25}, pages = {e2406679122}, abstract = {

Polarized fluorescence microscopy is a valuable tool for measuring molecular orientations in biological samples, but techniques for recovering three-dimensional orientations and positions of fluorescent ensembles are limited. We report a polarized dual-view light-sheet system for determining the diffraction-limited three-dimensional distribution of the orientations and positions of ensembles of fluorescent dipoles that label biological structures. We share a set of visualization, histogram, and profiling tools for interpreting these positions and orientations. We model the distributions based on the polarization-dependent efficiency of excitation and detection of emitted fluorescence, using coarse-grained representations we call orientation distribution functions (ODFs). We apply ODFs to create physics-informed models of image formation with spatio-angular point-spread and transfer functions. We use theory and experiment to conclude that light-sheet tilting is a necessary part of our design for recovering all three-dimensional orientations. We use our system to extend known two-dimensional results to three dimensions in FM1-43-labeled giant unilamellar vesicles, fast-scarlet-labeled cellulose in xylem cells, and phalloidin-labeled actin in U2OS cells. Additionally, we observe phalloidin-labeled actin in mouse fibroblasts grown on grids of labeled nanowires and identify correlations between local actin alignment and global cell-scale orientation, indicating cellular coordination across length scales.

}, keywords = {Actins, Animals, Humans, Imaging, Three-Dimensional, Mice, Microscopy, Fluorescence, Microscopy, Polarization, Xylem}, issn = {1091-6490}, doi = {10.1073/pnas.2406679122}, author = {Chandler, Talon and Guo, Min and Su, Yijun and Chen, Jiji and Wu, Yicong and Liu, Junyu and Agashe, Atharva and Fischer, Robert S and Mehta, Shalin B and Kumar, Abhishek and Baskin, Tobias I and Jaumouill{\'e}, Valentin and Liu, Huafeng and Swaminathan, Vinay and Nain, Amrinder S and Oldenbourg, Rudolf and La Riviere, Patrick J and Shroff, Hari} } @article {69128, title = {Phase diversity-based wavefront sensing for fluorescence microscopy.}, journal = {Optica}, volume = {11}, year = {2024}, month = {2024 Jun 10}, pages = {806-820}, abstract = {

Fluorescence microscopy is an invaluable tool in biology, yet its performance is compromised when the wavefront of light is distorted due to optical imperfections or the refractile nature of the sample. Such optical aberrations can dramatically lower the information content of images by degrading image contrast, resolution, and signal. Adaptive optics (AO) methods can sense and subsequently cancel the aberrated wavefront, but are too complex, inefficient, slow, or expensive for routine adoption by most labs. Here we introduce a rapid, sensitive, and robust wavefront sensing scheme based on phase diversity, a method successfully deployed in astronomy but underused in microscopy. Our method enables accurate wavefront sensing to less than λ/35 root mean square (RMS) error with few measurements, and AO with no additional hardware besides a corrective element. After validating the method with simulations, we demonstrate calibration of a deformable mirror \> 100-fold faster than comparable methods (corresponding to wavefront sensing on the ~100 ms scale), and sensing and subsequent correction of severe aberrations (RMS wavefront distortion exceeding λ/2), restoring diffraction-limited imaging on extended biological samples.

}, doi = {10.1364/OPTICA.518559}, url = {https://doi.org/10.1364/OPTICA.518559}, author = {Johnson, Courtney and Guo, Min and Schneider, Magdalena C and Su, Yijun and Khuon, Satya and Reiser, Nikolaj and Wu, Yicong and Riviere, Patrick La and Shroff, Hari} } @article {68409, title = {Practical considerations for quantitative light sheet fluorescence microscopy.}, journal = {Nature Methods}, volume = {19}, year = {2022}, month = {2022 Dec 01}, pages = {1538-49}, abstract = {

Fluorescence microscopy has evolved from a purely observational tool to a platform for quantitative, hypothesis-driven research. As such, the demand for faster and less phototoxic imaging modalities has spurred a rapid growth in light sheet fluorescence microscopy (LSFM). By restricting the excitation to a thin plane, LSFM reduces the overall light dose to a specimen while simultaneously improving image contrast. However, the defining characteristics of light sheet microscopes subsequently warrant unique considerations in their use for quantitative experiments. In this Perspective, we outline many of the pitfalls in LSFM that can compromise analysis and confound interpretation. Moreover, we offer guidance in addressing these caveats when possible. In doing so, we hope to provide a useful resource for life scientists seeking to adopt LSFM to quantitatively address complex biological hypotheses.

}, issn = {1548-7105}, doi = {10.1038/s41592-022-01632-x}, author = {Hobson, Chad M and Guo, Min and Vishwasrao, Harshad D and Wu, Yicong and Shroff, Hari and Chew, Teng-Leong} }