Automated image analysis of biomedical microscopy data

  1. 1Applied Systems Biology, Leibniz-Institut für Naturstoff-Forschung und Infektionsbiologie – Hans-Knöll-Institut
  2. 2Fakultät für Biowissenschaften, Friedrich-Schiller-Universität Jena

anna.medyukhina@leibniz-hki.de

Recent advances in microscopy techniques provide insights into cellular structures and mechanisms that were not accessible a few decades ago. While in the era of light microscopy we could only speculate about certain biological processes, nowadays we can study them at a high level of detail. Unfortunately, the stunning microscopic images are often used for illustrative purposes only, while statistical tests are often omitted or only performed based on a manual image analysis. In order to obtain statistically sound results, large amounts of data need to be analysed, for which automated image analysis is crucial. In this talk, I will address different steps of microscopy image analysis, such as preprocessing, segmentation and object detection, as well as various aspects of quantitative analysis: from simple object counting and size evaluation to characterization of object shape and co-localization analysis. I will demonstrate how automated image analysis routines enable objective and high-throughput evaluation of confocal, multiphoton and light-sheet microscopy data, which – in turns – allows to answer specific questions in the fields of biology and medicine.

Manuskript noch nicht verfügbar. Die Einreichungsphase ist aktuell geschlossen.
@inproceedings{dgao118-s3, title = {Automated image analysis of biomedical microscopy data}, author = {Anna Medyukhina, Marc-Thilo Figge}, booktitle = {DGaO-Proceedings, 118. Jahrestagung}, year = {2017}, publisher = {Deutsche Gesellschaft für angewandte Optik e.V.}, issn = {1614-8436}, note = {Vortrag S3} }
118. Jahrestagung der DGaO · Dresden · 2017