Hekrdla Miroslav, Roesel David, Hansen Niklas, Frederick Soumya, Umar Khalilullah, Petráková Vladimíra
J. Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Prague, Czechia.
Department of Physical Chemistry, University of Chemistry and Technology, Prague, Czechia.
Nat Commun. 2025 Jan 11;16(1):601. doi: 10.1038/s41467-025-55952-5.
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.
单分子定位显微镜（SMLM）能够实现超越衍射极限的成像。分子检测是SMLM中至关重要的初始步骤。在当前方法中未得到定量控制的误报检测是影响整个SMLM分析流程的伪影来源。此外，当前方法缺乏标准化，这阻碍了可重复性。在此，我们提出一种优化的分子检测方法，该方法将概率阈值处理与理论上最优的滤波相结合。概率阈值处理能够控制误报检测，而最优滤波则使漏报最小化。使用理论上最优的泊松匹配滤波器作为性能基准来评估现有的滤波方法。总体而言，我们的方法能够以稳健、单参数且用户无偏的方式检测分子。这将使伪影最小化，并在SMLM中实现数据的可重复性。
