Resolution enhancement of transmission electron microscopy by super-resolution radial fluctuations
Abstract
Super-resolution fluorescence microscopy techniques have enabled dramatic development in modern biology due to their capability to discern features smaller than the diffraction limit of light. Recently, super-resolution radial fluctuations (SRRF), an analytical approach that is capable of generating super-resolution images easily without the need for specialized hardware or photoswitchable fluorophores, has been presented. While SRRF has only been demonstrated on fluorescence microscopes, in principle, this method can be used to generate super-resolution images on any imaging platforms with intrinsic radial symmetric point spread functions. In this work, we show that SRRF can be utilized to enhance the resolution and quality of transmission electron microscopy (TEM) images. By including an image registration algorithm to correct for sample drift, the SRRF-TEM approach substantially enhances the resolution of TEM images of three different samples acquired with a commercial TEM system. We quantify the resolution improvement in SRRF-TEM and evaluate how SRRF parameters affect the resolution and quality of SRRF-TEM results.
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.