U. Matti

Assessment of 3D MINFLUX data for quantitative structural biology in cells revisited

The paper re-analyzes MINFLUX 3D imaging data to confirm its high localization precision and discuss its implications for structural biology.

Maximum-likelihood model fitting for quantitative analysis of SMLM data

LocMoFit is an open-source framework that fits models to SMLM data using maximum likelihood estimation to extract biological insights from single-molecule localization coordinates.

Photon-free (s)CMOS camera characterization for artifact reduction in high- and super-resolution microscopy

This paper develops an automated pipeline for sCMOS camera characterization using thermal signals, enabling artifact reduction in high- and super-resolution microscopy without additional hardware or user intervention.

Deep learning enables fast and dense single-molecule localization with high accuracy

This paper introduces DECODE, a deep learning tool that improves single-molecule localization speed and density in SMLM with high accuracy across various imaging conditions.

Direct Supercritical Angle Localization Microscopy for Nanometer 3D Superresolution

This paper introduces SALM, a 3D superresolution technique that improves z-resolution by four times using direct splitting of supercritical and undercritical emission.

A cost-efficient open source laser engine for microscopy

The paper presents an open-source, cost-efficient laser engine for microscopy using affordable diodes and fiber delivery to reduce speckles.

Nuclear pores as versatile reference standards for quantitative superresolution microscopy

The paper uses genome-edited cell lines with labeled nuclear pore complexes to serve as reference standards for quantitative superresolution microscopy.

Fast, robust and precise 3D localization for arbitrary point spread functions

The paper introduces a fast and precise 3D localization method for arbitrary PSFs, achieving high resolution and speed on standard microscopes.