Tech Briefs Magazine - January 2024 - PIT-21

Sharper Images: A Breakthrough in Microscopy Resolution
An innovative algorithm successfully addresses the challenge of microscopy resolution through pixel reassignment.
SPIE, Bellingham, WA
O
btaining high-resolution images
in the world of microscopy has
long been a challenge. Deconvolution, a
method to enhance image clarity, often
amplifies noise between the sample
and the image. Researchers at Boston
University recently developed a novel
deblurring algorithm that avoids these
issues, improving the resolution of images
with photon intensity conservation
and local linearity.
As reported in the Gold Open Access
journal Advanced Photonics, the innovative
deblurring algorithm is adaptable
to various fluorescence microscopes, requiring
minimal assumptions about the
emission point spread function (PSF). It
works on a sequence of raw images and
even a single image, enabling temporal
analysis of fluctuating fluorophore
statistics. Furthermore, the researchers
have made this algorithm available as
a MATLAB function, making it widely
accessible.
The fundamental concept behind this
breakthrough is pixel reassignment. By
reassigning pixel intensities based on
local gradients, images are sharpened
without the risk of introducing noise artifacts.
The technique standardizes raw
images before applying this process, ensuring
consistent results.
The resolution of a microscope is traditionally
defined by its ability to distinguish
two closely spaced point sources.
The new method, called " deblurring by
pixel reassignment " (DPR), significantly
reduces the required separation distance,
allowing for enhanced resolution.
To demonstrate the effectiveness of
DPR, the researchers applied it to a variety
of imaging conditions: single-molecule
localization, structural imaging of
engineered cardiac tissue, and volumetric
zebrafish imaging. These real-world
applications showcased DPR's potential
in improving the clarity of microscopic
images.
DPR's unique ability to sharpen images,
while preserving larger structures,
opens doors to broader applications. It
can be used in scenarios where samples
contain both small and large structures,
making it a versatile tool for researchers.
While no deblurring strategy is
entirely immune to noise, DPR's advantage
lies in the fact that it does not amplify
noise. This sets it apart from other
deconvolution methods, simplifying its
implementation and making it suitable
for a wide range of samples with extended
features.
A new approach to enhancing the spatial
resolution of microscopy images, the
DPR technique provides a versatile and
user-friendly solution that significantly
improves image clarity while avoiding
common noise-related issues, making it
an invaluable tool for a wide range of
scientific applications. Professor Jerome
Mertz, Director of the Biomicroscopy
Laboratory at Boston University and senior
author of the study said, " Because
of its ease of use, speed, and versatility,
we believe DPR can be of general utility
to the bio-imaging community. "
For more information, see B. Zhao
and J. Mertz, " Resolution enhancement
with deblurring by pixel reassignment, "
Advanced Photonics 5(6), 066004 (2023),
doi 10.1117/1.AP.5.6.066004
Principle of DPR. (a) From left to right: simulations of Gaussian PSF intensity and gradient maps (amplitude and direction), pixel reassignments, deblurred PSF
image after application of DPR. (b) DPR workflow. (Image: B. Zhao and J. Mertz, doi 10.1117/1.AP.5.6.066004)
Photonics & Imaging Technology, January 2024
21

Tech Briefs Magazine - January 2024

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