2016, Walde, Marie, Jost, Aurélie, Wicker, Kai, Heintzmann, Rainer

Bessel illumination is an established method in optical imaging and manipulation to achieve an extended depth of field without compromising the lateral resolution. When broadband or multicolour imaging is required, wavelength-dependent changes in the radial profile of the Bessel illumination can complicate further image processing and analysis. We present a solution for engineering a multicolour Bessel beam that is easy to implement and promises to be particularly useful for broadband imaging applications. A phase-only spatial light modulator (SLM) in the image plane and an iterative Fourier Transformation algorithm (IFTA) are used to create an annular light distribution in the back focal plane of a lens. The 2D Fourier transformation of such a light ring yields a Bessel beam with a constant radial profile for different wavelength.

2015, Jost, Aurélie, Tolstik, Elen, Feldmann, Polina, Wicker, Kai, Sentenac, Anne, Heintzmann, Rainer, Degtyar, Vadim E.

The microscope image of a thick fluorescent sample taken at a given focal plane is plagued by out-of-focus fluorescence and diffraction limited resolution. In this work, we show that a single slice of Structured Illumination Microscopy (two or three beam SIM) data can be processed to provide an image exhibiting tight sectioning and high transverse resolution. Our reconstruction algorithm is adapted from the blind-SIM technique which requires very little knowledge of the illumination patterns. It is thus able to deal with illumination distortions induced by the sample or illumination optics. We named this new algorithm thick slice blind-SIM because it models a three-dimensional sample even though only a single two-dimensional plane of focus was measured.

2016, Förster, Ronny, Wicker, Kai, Müller, Walter, Jost, Aurélie, Heintzmann, Rainer

The reconstruction process of structured illumination microscopy (SIM) creates substantial artefacts if the specimen has moved during the acquisition. This reduces the applicability of SIM for live cell imaging, because these artefacts cannot always be recognized as such in the final image. A movement is not necessarily visible in the raw data, due to the varying excitation patterns and the photon noise. We present a method to detect motion by extracting and comparing two independent 3D wide-field images out of the standard SIM raw data without needing additional images. Their difference reveals moving objects overlaid with noise, which are distinguished by a probability theory-based analysis. Our algorithm tags motion-artefacts in the final high-resolution image for the first time, preventing the end-user from misinterpreting the data. We show and explain different types of artefacts and demonstrate our algorithm on a living cell.