Alshaabi Thayer, Milkie Daniel E, Liu Gaoxiang, Shirazinejad Cyna, Hong Jason L, Achour Kemal, Görlitz Frederik, Milunovic-Jevtic Ana, Simmons Cat, Abuzahriyeh Ibrahim S, Hong Erin, Williams Samara Erin, Harrison Nathanael, Huang Evan, Bae Eun Seok, Killilea Alison N, Drubin David G, Swinburne Ian A, Upadhyayula Srigokul, Betzig Eric
Howard Hughes Medical Institute, Ashburn, VA.
Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA.
ArXiv. 2025 May 23:arXiv:2503.12593v2.
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.
高分辨率组织成像常常受到样本引起的光学像差的影响，这些像差会降低分辨率和对比度。虽然基于波前传感器的自适应光学（AO）可以测量这些像差，但此类硬件解决方案通常很复杂，实施成本高，并且在对大视野内空间变化的像差进行串行映射时速度较慢。在此，我们介绍AOViFT（自适应光学视觉傅里叶变换器）——一种基于机器学习的像差传感框架，它围绕一个在傅里叶域嵌入上运行的3D多级视觉变换器构建。与传统架构或实空间网络相比，AOViFT能够推断像差并恢复点标记样本中的衍射极限性能，同时大幅降低计算成本、训练时间和内存占用。我们在活体基因编辑斑马鱼胚胎上验证了AOViFT，证明了它使用可变形镜或采集后反卷积来校正空间变化像差的能力。通过消除对导星和波前传感硬件的需求并简化实验工作流程，AOViFT降低了对各种生物样本进行高分辨率体积显微镜检查的技术障碍。
