Browsing by Author "Gao, Hao-Cheng"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Deep learning-driven adaptive optics for single-molecule localization microscopy
    (Springer Nature, 2023) Zhang, Peiyi; Ma, Donghan; Cheng, Xi; Tsai, Andy P.; Tang, Yu; Gao, Hao-Cheng; Fang, Li; Bi, Cheng; Landreth, Gary E.; Chubykin, Alexander A.; Huang, Fang; Anatomy, Cell Biology and Physiology, School of Medicine
    The inhomogeneous refractive indices of biological tissues blur and distort single-molecule emission patterns generating image artifacts and decreasing the achievable resolution of single-molecule localization microscopy (SMLM). Conventional sensorless adaptive optics methods rely on iterative mirror changes and image-quality metrics. However, these metrics result in inconsistent metric responses and thus fundamentally limit their efficacy for aberration correction in tissues. To bypass iterative trial-then-evaluate processes, we developed deep learning-driven adaptive optics for SMLM to allow direct inference of wavefront distortion and near real-time compensation. Our trained deep neural network monitors the individual emission patterns from single-molecule experiments, infers their shared wavefront distortion, feeds the estimates through a dynamic filter and drives a deformable mirror to compensate sample-induced aberrations. We demonstrated that our method simultaneously estimates and compensates 28 wavefront deformation shapes and improves the resolution and fidelity of three-dimensional SMLM through >130-µm-thick brain tissue specimens.