Image Analysis of Cell Function

Image Analysis of Cell Function Unit
© Fraunhofer IZI

Image Analysis of Cell Function Unit

The Image Analysis of Cell Function Unit develops new, bespoke image analysis methods for the non-destructive, microscopy-based quantification of physiological and pathological processes.

By analyzing cells and tissue without modifying or destroying them, the unit aims to support research into fundamental biological relationships as well as the testing of new therapeutic methods. As this requires interdisciplinary cooperation in the fields of electrical engineering, optics, imaging, software development and biology, the specialist group is closely tied in to the Biotronic Systems chair at Leipzig University of Applied Sciences (HTWK).

Light Sheet Microscopy Platform

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.

2D & 3D Image Analysis

  • Quantitative Morphological Analyses
    Morphological analyses can be used, for instance, to grade prostate and cervical cancer. Besides this, they can be drawn upon to investigate the invasion of cervical and basal-cell cancer, to describe follicular lymphomas with a view to toponome structures and to measure the growth of astrocytes. Special attention is given to effective algorithms and their implementation, e.g. through discreet compactness, as well as the integration of explicit pathophysiological knowledge.


  • Machine Learning & Big Data
    Constantly growing data sets and increasingly complex questions place huge demands on both time and personnel in the assessment of diagnostic findings or experimental images. The use of machine learning methods not only significantly alleviates these time and staff demands, it also provides solid approaches when it comes to the partial automation of image analysis.<

 

  • Real-Time Cell Tracking
    Time series imaging, for instance using a confocal microscope, is a state-of-the-art microscopy method. Evaluating these data sets also takes translocation into consideration, enabling cells or cell populations to move over the course of multiple time steps. Tracking algorithms are used to monitor this movement. They run through the time series, recording and highlighting traces of cell movement. This also enables observations to be made on cell motility and vitality.

 

  • Statistical Analyses
    In various scientific constellations, analyzing spatial patterns helps us better understand specific architectural and structural compositions that are made up of individual agents, for instance in botany (plants) and also physiology (cells). This allows concentrations and the probabilities of such concentrations to be depicted and quality parameters for similarities to be determined.

 

  • CT & µCT Analysis
    The nondestructive, efficient analysis of material samples is becoming more and more significant in materials and process testing. The two-dimensional sectional images gained using computed tomography (CT & µCT) are reconstructed as a 3D image data record (GigaVoxel) before then undergoing quantitative and morphological analysis. This microstructure-based assessment is employed in a range of fields, from metal and non-metal materials right over to plastics. The results of the analysis can be used in subsequent processes such as quality management or modeling (finite element method - FEM).

 

Real-Time Cell Tracking
© Fraunhofer IZI

Real-Time Cell Tracking

Statistical Analyses
© Fraunhofer IZI

Statistical Analyses

Fiber structure analysis
© Fraunhofer IZI

Fiber structure analysis

Laboratory and Process Digitalization/Automation

The growing trend towards digitalization is becoming ever more apparent in pretty much every area of life. The demand for innovative applications in the laboratory is also constantly increasing. An intelligent and automated laboratory setup results in optimized workflows and increased process efficiency and safety. Interlinking various aspects of the laboratory in an appropriate, digital and modular manner also simplifies laboratory procedures and the associated documentation.

Control, Regulation and Automation Technology

Effective microscopy platforms require the complex control of all components in order to guarantee not only reproducible outcomes but also software that can easily be operated by the end user. A modular software solution has been created that features a supreme level of automation yet low application complexity for the specially developed light sheet microscope (SPIM). A high level of reproducibility is ensured as the software is able to put together protocols for a specific experiment or study which can then be loaded as presets at a later date. Moreover, every microscopy image can be recorded using parameters created in real time, such as position, temperature, local pH values and partial pressures (smart capillary). This gives way to wide-ranging analyses of the captured images. Due to the software’s modular character, new analysis algorithms can be integrated at any time and the subsequent results can be incorporated into the process operation or exported separately for documentation purposes.