Work

Maximum Likelihood Localization Maps

Year: 2026

Type: preprint

Abstract: Single-molecule localization microscopy commonly reconstructs images from estimated emitter coordinates. We calculate maximum-likelihood localization maps (MLLM), a non-iterative approach that evaluates positional likelihood from measured data and a supplied point-spread function. The MLLM of each detected single molecule image is added into a final upsampled image representing the overall molecular probability map, preserving the positional likelihood structure and obviating separate coordinate-based rendering. MLLM calculation is noniterative, fast, supports any calibrated point-spread function, accounts for local background variation, supports two- and three-dimensional reconstruction, and can be calculated in parallel.

Source: bioRxiv (Cold Spring Harbor Laboratory)

DOI: 10.64898/2026.11.05.764521

Authors: Hossein Zarei Oshtolagh, Ronny Foerster, Jonas Ries, Rainer Heintzmann

Institutions: Leibniz Institute of Photonic Technology, Friedrich Schiller University Jena, University of Vienna

Language: English

Topic: Advanced Fluorescence Microscopy Techniques

Subfield: Biophysics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funder: Deutsche Forschungsgemeinschaft

Awards: G2967549892, SFB 1278: Polymerbasierte NanopartikelBibliotheken für die Entwicklung zielgerichteter antiinflammatorischer Strategien