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Optimized molecule detection in localization microscopy with selected false positive probability.

Authors :
Hekrdla, Miroslav
Roesel, David
Hansen, Niklas
Frederick, Soumya
Umar, Khalilullah
Petráková, Vladimíra
Source :
Nature Communications; 1/11/2025, Vol. 16 Issue 1, p1-13, 13p
Publication Year :
2025

Abstract

Single-molecule localization microscopy (SMLM) allows imaging beyond the diffraction limit. Detection of molecules is a crucial initial step in SMLM. False positive detections, which are not quantitatively controlled in current methods, are a source of artifacts that affect the entire SMLM analysis pipeline. Furthermore, current methods lack standardization, which hinders reproducibility. Here, we present an optimized molecule detection method which combines probabilistic thresholding with theoretically optimal filtering. The probabilistic thresholding enables control over false positive detections while optimal filtering minimizes false negatives. A theoretically optimal Poisson matched filter is used as a performance benchmark to evaluate existing filtering methods. Overall, our approach allows the detection of molecules in a robust, single-parameter and user-unbiased manner. This will minimize artifacts and enable data reproducibility in SMLM. The work presents a molecule detection method for single-molecule localization microscopy. By means of probabilistic thresholding with control over false positive detections, the method improves robustness and enhances reproducibility. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20411723
Volume :
16
Issue :
1
Database :
Complementary Index
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
182189964
Full Text :
https://doi.org/10.1038/s41467-025-55952-5