Optimized molecule detection in localization microscopy with selected false positive probability

Miroslav Hekrdla (), David Roesel, Niklas Hansen, Soumya Frederick, Khalilullah Umar and Vladimíra Petráková ()
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Miroslav Hekrdla: Czech Academy of Sciences
David Roesel: Czech Academy of Sciences
Niklas Hansen: Czech Academy of Sciences
Soumya Frederick: Czech Academy of Sciences
Khalilullah Umar: Czech Academy of Sciences
Vladimíra Petráková: Czech Academy of Sciences

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: 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.

Date: 2025
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DOI: 10.1038/s41467-025-55952-5

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