Quantitative mapping and minimization of super-resolution optical imaging artifacts

TY - JOUR

T1 - Quantitative mapping and minimization of super-resolution optical imaging artifacts

AU - Culley, Siân

AU - Albrecht, David

AU - Jacobs, Caron

AU - Pereira, Pedro Matos

AU - Leterrier, Christophe

AU - Mercer, Jason

AU - Henriques, Ricardo

N1 - Publisher Copyright: © 2018 Nature Publishing Group. All rights reserved.

PY - 2018/4/3

Y1 - 2018/4/3

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85044957001&partnerID=8YFLogxK

U2 - 10.1038/nmeth.4605

DO - 10.1038/nmeth.4605

M3 - Article

C2 - 29457791

AN - SCOPUS:85044957001

SN - 1548-7091

VL - 15

SP - 263

EP - 266

JO - NATURE METHODS

JF - NATURE METHODS

IS - 4

ER -