Biological Nanoimaging

Prof. Dr. Rainer HEINTZMANN

Email: rainer.heintzmann@uni-jena.de
Phone: +49 3641-9-48350

Prof. Rainer Heintzmann is Professor of Nanobiophotonics at Friedrich Schiller University Jena and heads the Microscopy Department at the Leibniz Institute of Photonic Technology (Leibniz IPHT).

His research focuses on computational optical microscopy and the development of imaging methods beyond the classical diffraction limit. A particular emphasis lies on structured illumination microscopy, quantitative modelling of image formation, computational reconstruction, point-spread-function engineering, and the combination of advanced optical instrumentation with data-driven image analysis.

Research Areas

Prof. Heintzmann's research focuses on advanced optical microscopy and computational image formation, with particular emphasis on methods that extend spatial resolution, information content and imaging speed beyond conventional microscopy. Research interests include:

Structured illumination microscopy (SIM) and optical super-resolution
Computational microscopy and inverse image reconstruction
Quantitative modelling and engineering of optical point-spread functions
Fluorescence and label-free optical microscopy
Light-sheet and spectroscopic imaging
Adaptive, automated and open-source microscopy
Optical imaging under challenging conditions, including cryogenic microscopy
Extension of structured illumination concepts towards shorter wavelengths

Teaching Fields

Prof. Heintzmann teaches undergraduate courses in physical chemistry, as well as specialized courses on optics and image processing. These currently include:

Optical microscopy
Computational imaging and image reconstruction
Super-resolution microscopy
Fourier optics and image formation
Biomedical and quantitative imaging

Research Methods

The group combines advanced optical microscopy with computational modelling and image reconstruction. Methods include:

Structured illumination microscopy (SIM)
Fluorescence super-resolution microscopy
Light-sheet microscopy
Raman and spectroscopic microscopy
Point-spread-function measurement, modelling and engineering
Fourier-optical and wave-optical modelling
Inverse problems and computational image reconstruction
Machine-learning-assisted microscopy and image analysis
Automated and open-source microscope platforms
Quantitative validation of spatial resolution and imaging performance

Recent Research Results

CellSTORM - affordable localisation microscopy on a smartphone.
Image: Heintzmann research group

Structured illumination microscopy (SIM) remains a central research direction of the group. Recent developments extend SIM towards improved robustness, automation and new optical configurations. Selective-plane-activation SIM has enabled super-resolution imaging with improved optical sectioning, while automated multicolour SIM modules demonstrate how advanced super-resolution methods can be implemented in compact and accessible microscope systems [1,2].

A second focus is the quantitative modelling of optical image formation. Accurate knowledge of the microscope point-spread function is essential for super-resolution reconstruction and quantitative imaging. Recent work has developed and experimentally validated numerical methods for calculating point-spread functions, including realistic aberrations and complex optical configurations [3].

The group also investigates new regimes of optical microscopy. Time-deterministic cryo-optical microscopy enables dynamic biological processes to be followed in live samples and then rapidly frozen at selected moments for high-signal fluorescence and Raman imaging [4]. Structured illumination concepts have additionally been extended into the extreme-ultraviolet spectral region, demonstrating a route towards super-resolution imaging at substantially shorter wavelengths [5].

More broadly, current work combines optical instrument development with computational reconstruction and automated microscopy. This integration aims to increase resolution, reproducibility and accessibility while extracting the maximum information content from measured optical data.

[1] Temma et al., Nat. Methods 21, 889 (2024).
[2] Wang et al., Commun. Eng. 4, 42 (2025).
[3] Miora et al., Opt. Express 32, 27278 (2024).
[4] Tsuji et al., Light Sci. Appl. 14, 275 (2025).
[5] Mincigrucci et al., Opt. Express 32, 30813 (2024).

link to the Biological Nanoimaging GroupExternal link