@article {69838, title = {Fourier-Based 3D Multistage Transformer for Aberration Correction in Multicellular Specimens}, journal = {Research Square}, year = {2025}, month = {2025 Apr 02}, abstract = {

High-resolution tissue imaging is often compromised by sample-induced optical aberrations that degrade resolution and contrast. While wavefront sensor-based adaptive optics (AO) can measure these aberrations, such hardware solutions are typically complex, expensive to implement, and slow when serially mapping spatially varying aberrations across large fields of view. Here, we introduce AOViFT (Adaptive Optical Vision Fourier Transformer)---a machine learning-based aberration sensing framework built around a 3D multistage Vision Transformer that operates on Fourier domain embeddings. AOViFT infers aberrations and restores diffraction-limited performance in puncta-labeled specimens with substantially reduced computational cost, training time, and memory footprint compared to conventional architectures or real-space networks. We validated AOViFT on live gene-edited zebrafish embryos, demonstrating its ability to correct spatially varying aberrations using either a deformable mirror or post-acquisition deconvolution. By eliminating the need for the guide star and wavefront sensing hardware and simplifying the experimental workflow, AOViFT lowers technical barriers for high-resolution volumetric microscopy across diverse biological samples.

}, doi = {10.21203/rs.3.rs-6273247/v1}, url = {https://doi.org/10.21203/rs.3.rs-6273247/v1}, author = {Thayer Alshaabi and Daniel Milkie and Gaoxiang Liu and Cyna Shirazinejad and Jason Hong and Kemal Achour and Frederik G{\"o}rlitz and Ana Milunovic-Jevtic and Cat Simmons and Ibrahim Abuzahriyeh and Erin Hong and Samara Williams and Nathanael Harrison and Evan Huang and Eun Bae and Alison Killilea and David Drubin and Ian Swinburne and Srigokul Upadhyayula and Eric Betzig} } @article {69142, title = {Image processing tools for petabyte-scale light sheet microscopy data.}, journal = {Nat. Methods}, year = {2024}, month = {2024 Oct 17}, abstract = {

Light sheet microscopy is a powerful technique for high-speed three-dimensional imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations. To address these challenges, we present PetaKit5D, a scalable software solution for efficient petabyte-scale light sheet image processing. This software incorporates a suite of commonly used processing tools that are optimized for memory and performance. Notable advancements include rapid image readers and writers, fast and memory-efficient geometric transformations, high-performance Richardson-Lucy deconvolution and scalable Zarr-based stitching. These features outperform state-of-the-art methods by over one order of magnitude, enabling the processing of petabyte-scale image data at the full teravoxel rates of modern imaging cameras. The software opens new avenues for biological discoveries through large-scale imaging experiments.

}, doi = {10.1038/s41592-024-02475-4}, url = {https://doi.org/10.1038/s41592-024-02475-4}, author = {Xiongtao Ruan and Matthew Mueller and Gaoxiang Liu and Frederik G{\"o}rlitz and Tian-Ming Fu and Daniel E. Milkie and Joshua Lillvis and Alison Killilea and Eric Betzig and Srigokul Upadhyayula} } @article {68257, title = {Characterization, Comparison, and Optimization of Lattice Light Sheets}, journal = {Science Advances}, year = {2023}, month = {2023 Mar 31}, abstract = {

Lattice light sheet microscopy excels at the non-invasive imaging of three-dimensional (3D) dynamic processes at high spatiotemporal resolution within cells and developing embryos. Recently, several papers have called into question the performance of lattice light sheets relative to the Gaussian sheets most common in light sheet microscopy. Here we undertake a comprehensive theoretical and experimental analysis of various forms of light sheet microscopy which both demonstrates and explains why lattice light sheets provide significant improvements in resolution and photobleaching reduction. The analysis provides a procedure to select the correct light sheet for a desired experiment and specifies the processing that maximizes the use of all fluorescence generated within the light sheet excitation envelope for optimal resolution while minimizing image artifacts and photodamage. Development of a new type of {\textquotedblleft}harmonic balanced{\textquotedblright} lattice light sheet is shown to improve performance at all spatial frequencies within its 3D resolution limits and maintains this performance over lengthened propagation distances allowing for expanded fields of view.

}, doi = {10.1126/sciadv.ade6623}, url = {https://doi.org/10.1126/sciadv.ade6623}, author = {Gaoxiang Liu and Xiongtao Ruan and Daniel E. Milkie and Frederik G{\"o}rlitz and Matthew Mueller and Wilmene Hercule and Alison Kililea and Eric Betzig and Srigokul Upadhyayula} } @article {64995, title = {Lamellar junctions in the endolymphatic sac act as a relief valve to regulate inner ear pressure.}, journal = {eLife}, year = {2018}, month = {2018 Jun 19}, doi = {10.7554/eLife.37131}, author = {Ian A. Swinburne and Kishore R. Mosaliganti and Srigokul Upadhyayula and Tsung-Li Liu and David G. C. Hildebrand and Tony Y.-C. Tsai and Anzhi Chen and Ebaa Al-Obeidi and Anna K. Fass and Samir Malhotra and Florian Engert and Jeff W. Lichtman and Tom Kirchhausen and Sean G. Megason and Eric Betzig} } @proceedings {65004, title = {Developing photo activated localization microscopy}, year = {2007}, month = {2007 Apr 15}, abstract = {

In conventional biological imaging, diffraction places a limit on the minimal xy distance at which two marked objects can be discerned. Consequently, resolution of target molecules within cells is typically coarser by two orders of magnitude than the molecular scale at which the proteins are spatially distributed. Photoactivated localization microscopy (PALM) optically resolves selected subsets of protect fluorescent probes within cells at mean separations of \<25 nanometers. It involves serial photoactivation and subsequent photobleaching of numerous sparse subsets of photoactivated fluorescent protein molecules. Individual molecules are localized at near molecular resolution by determining their centers of fluorescent emission via a statistical fit of their point-spread-function. The position information from all subsets is then assembled into a super-resolution image, in which individual fluorescent molecules are isolated at high molecular densities. In this paper, some of the limitations for PALM imaging under current experimental conditions are discussed.

}, doi = {10.1109/isbi.2007.357008}, author = {George H. Patterson and Eric Betzig and Jennifer Lippincott-Schwartz and Harald F. Hess} }