Open-source image reconstruction of super-resolution structured illumination microscopy data in ImageJ.
Nat Commun 2016;
7:10980. [PMID:
26996201 PMCID:
PMC4802170 DOI:
10.1038/ncomms10980]
[Citation(s) in RCA: 121] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 02/08/2016] [Indexed: 12/19/2022] Open
Abstract
Super-resolved structured illumination microscopy (SR-SIM) is an important tool for fluorescence microscopy. SR-SIM microscopes perform multiple image acquisitions with varying illumination patterns, and reconstruct them to a super-resolved image. In its most frequent, linear implementation, SR-SIM doubles the spatial resolution. The reconstruction is performed numerically on the acquired wide-field image data, and thus relies on a software implementation of specific SR-SIM image reconstruction algorithms. We present fairSIM, an easy-to-use plugin that provides SR-SIM reconstructions for a wide range of SR-SIM platforms directly within ImageJ. For research groups developing their own implementations of super-resolution structured illumination microscopy, fairSIM takes away the hurdle of generating yet another implementation of the reconstruction algorithm. For users of commercial microscopes, it offers an additional, in-depth analysis option for their data independent of specific operating systems. As a modular, open-source solution, fairSIM can easily be adapted, automated and extended as the field of SR-SIM progresses.
Reconstruction of super resolution structured illumination microscopy (SR-SIM) datasets typically relies upon commercial software. Here Müller et al. present an open-source ImageJ plugin to facilitate reconstruction of SR-SIM data from a broad range of microscopy platforms.
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