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  • Author(s):
    Yide Zhang, Yinhao Zhu, Evan Nichols, Qingfei Wang, Siyuang Zhang, Cody Smith, Scott Howard
    Abstract:

    Fluorescence microscopy has enabled a dramatic development in modern biology. Due to its inherently weak signal, fluorescence microscopy is not only much noisier than photography, but also presented with Poisson-Gaussian noise where Poisson noise, or shot noise, is the dominating noise source. To get clean fluorescence microscopy images, it is highly desirable to have effective denoising algorithms and datasets that are specifically designed to denoise fluorescence microscopy images. While su…

    Date Created:
    2019-10-15
    Resource Type
    Presentation
  • Author(s):
    Yide Zhang, Scott S. Howard, Cody J. Smith
    Abstract:

    Super-resolution microscopy is broadening our in-depth understanding of cellular structure. However, super-resolution approaches are limited, for numerous reasons, from utilization in longer-term intravital imaging. We devised a combinatorial imaging technique that combines deconvolution with stepwise optical saturation microscopy (DeSOS) to circumvent this issue and image cells in their native physiological environment. Other than a traditional confocal or two-photon microscope, this approac…

    Date Created:
    2019-01-09
    Resource Type
    Software
  • Author(s):
    Yide Zhang, Prakash Nallathamby, Genevieve D. Vigil, Aamir A. Khan, Devon E. Mason, Joel D. Boerckel, Ryan K. Roeder, Scott S. Howard
    Abstract:

    Super-resolution fluorescence microscopy is an important tool in biomedical research for its ability to discern features smaller than the diffraction limit. However, due to its difficult implementation and high cost, the super-resolution microscopy is not feasible in many applications. In this paper, we propose and demonstrate a saturation-based super-resolution fluorescence microscopy technique that can be easily implemented and requires neither additional hardware nor complex post-processin…

    Date Published:
    2018-04