ArticleScientific reports2019
Correcting Artifacts in Single Molecule Localization Microscopy Analysis Arising from Pixel Quantum Efficiency Differences in sCMOS Cameras.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Melanopsin regulates axonal translation underlying retinohypothalamic circuit assembly.bioRxiv : the preprint server for biology · 2026Article
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- Eye-specific differences in active zone addition during synaptic competition in the developing visual system.bioRxiv : the preprint server for biology · 2025Article
- Simple, Economic, and Robust Rail-Based Setup for Super-Resolution Localization Microscopy.The journal of physical chemistry. A · 2023Article
- Quality assessment in light microscopy for routine use through simple tools and robust metrics.The Journal of cell biology · 2022Article
- Cega: a single particle segmentation algorithm to identify moving particles in a noisy system.Molecular biology of the cell · 2021Article
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Authors and funding
3 authors.
Funding
Abstract
Optimal analysis of single molecule localization microscopy (SMLM) data acquired with a scientific Complementary Metal-Oxide-Semiconductor (sCMOS) camera relies on statistical compensation for its pixel-dependent gain, offset and readout noise. In this work we show that it is also necessary to compensate for differences in the relative quantum efficiency (RQE) of each pixel. We found differences in RQE on the order of 4% in our tested sCMOS sensors. These differences were large enough to have a noticeable effect on analysis algorithm results, as seen both in simulations and biological imaging data. We discuss how the RQE differences manifest themselves in the analysis results and present the modifications to the Poisson maximum likelihood estimation (MLE) sCMOS analysis algorithm that are needed to correct for the RQE differences.
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