Quantitative Mapping and Minimization of Super-resolution Optical Imaging Artifacts

Overview

Journal Nat Methods

Specialties Biomedical Engineering
Pathology

Date 2018 Feb 20

PMID 29457791

Citations 132

Authors

Sian Culley

David Albrecht

Caron Jacobs

Pedro Matos Pereira

Christophe Leterrier

Jason Mercer

Ricardo Henriques

Affiliations

Soon will be listed here.

Abstract

Super-resolution microscopy depends on steps that can contribute to the formation of image artifacts, leading to misinterpretation of biological information. We present NanoJ-SQUIRREL, an ImageJ-based analytical approach that provides quantitative assessment of super-resolution image quality. By comparing diffraction-limited images and super-resolution equivalents of the same acquisition volume, this approach generates a quantitative map of super-resolution defects and can guide researchers in optimizing imaging parameters.

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