Generalized stepwise optical saturation enables super-resolution fluorescence lifetime imaging microscopy
Abstract
We present a novel super-resolution fluorescence lifetime microscopy technique called generalized stepwise optical saturation (GSOS) that generalizes and extends the concept of the recently demonstrated stepwise optical saturation (SOS) super-resolution microscopy [Biomed. Opt. Express 9, 1613 (2018)]. The theoretical basis of GSOS is developed based on exploring the dynamics of a two-level fluorophore model and using perturbation theory. We show that although both SOS and GSOS utilize the linear combination of M raw images to increase the imaging resolution by a factor of √M, SOS is a special and the simplest case of GSOS. The super-resolution capability is demonstrated with theoretical analysis and numerical simulations for GSOS with sinusoidal and pulse-train modulations. Using GSOS with pulse-train modulation, super-resolution and fluorescence lifetime imaging microscopy (FLIM) images can be obtained simultaneously. The super-resolution FLIM capability is experimentally demonstrated with a cell sample on a custom-built two-photon frequency-domain (FD) FLIM system based on radio frequency analog signal processing. To our knowledge, this is the first implementation of super-resolution imaging in FD-FLIM.
Yide Zhang
Incoming Assistant Professor of ECEE and BME
My long-term research goal is to pioneer optical imaging technologies that surpass current limits in speed, accuracy, and accessibility, advancing translational research. With a foundation in electrical engineering, particularly in biomedical imaging and optics, my PhD work at the University of Notre Dame focused on advancing multiphoton fluorescence lifetime imaging microscopy and super-resolution microscopy, significantly reducing image generation time and cost. I developed an analog signal processing method that enables real-time streaming of fluorescence intensity and lifetime data, and created the first Poisson-Gaussian denoising dataset to benchmark image denoising algorithms for high-quality, real-time applications in biomedical research. As a postdoc at the California Institute of Technology (Caltech), my research expanded to include pioneering photoacoustic imaging techniques, enabling noninvasive and rapid imaging of hemodynamics in humans. In the realm of quantum imaging, I developed innovative techniques utilizing spatial and polarization entangled photon pairs, overcoming challenges such as poor signal-to-noise ratios and low resolvable pixel counts. Additionally, I advanced ultrafast imaging methods for visualizing passive current flows in myelinated axons and electromagnetic pulses in dielectrics. My research is currently funded by the National Institutes of Health (NIH) K99/R00 Pathway to Independence Award. I will join the University of Colorado Boulder (CU Boulder) as an Assistant Professor of Electrical, Computer & Energy Engineering (ECEE) and Biomedical Engineering (BME) in May 2025.