Selective Plane Illumination Microscopy (SPIM) is a fluorescence microscopy method which illuminates just a thin layer being in the sample (usually only a couple of micrometers). Compared with other fluorescence microscopy procedures such as confocal microscopy, light sheet microscopy is thus able to keep damage caused by light-induced stress or bleaching at a minimum. By carrying out multi-directional SPIM (mSPIM), the sample can be illuminated alternately from different directions and in real time, thus enabling further artifacts to be eliminated and increasing image quality accordingly.
Since 2017, the light sheet microscope and related services have been available not only to in-house units but also to customers and partners. The 3D fluorescence microscopy platform is especially gentle on samples and therefore well suited, among other things, to observing and analyzing the growth of organoids, the study of model organisms, and the histological architecture of organotypic cultures as a long-term process over the course of days or even weeks based on 3D imaging.
Micro-arrays as molecular biological screening systems contain thousands of tightly packed tests (spots) on an object slide. Fluorescence microscopy images of these slides can be automatically analyzed with commercially available software solutions. However, this requires a great number of spots that should have a high signal intensity whereas no interfering artifacts are present in the image. If these conditions are not met, the hitherto existing software does not automatically detect the spots, which increases the need for time-consuming manual analysis.
During the development phase of a particularly sensitive micro-array-screening-system, the prototypes may exhibit only a small count of high intensity spots, on top of that with a low signal to noise ratio (SNR). To enable high throughput testing for these images, the Image Analysis of Cell Function Unit and the Ligand Development Unit develop robust algorithms for the detection and segmentation of spots. Using a prototypical software implementation, and by introducing the new option of exporting some statistical parameters, the processing time per sample could be remarkably reduced compared to manual analysis.
Going beyond the current project EpiCoV2020, the algorithms could be tested successfully for images of peptide micro arrays obtained from allergy research. The main goal is now to evaluate more cases of application and to implement the algorithms in a distributable software