Automated image analysis of biomedical microscopy data

Applied Systems Biology, Leibniz Institute for Natural Product Research and Infection Biology, Hans-Knöll-Institute (HKI), Jena, Germany; 2 Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, Jena, Germany

anna.medyukhina@leibniz-hki.de

Abstract

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.

Keywords

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@inproceedings{dgao118-s3, title = {Automated image analysis of biomedical microscopy data}, author = {A. Medyukhina, M-T. Figge}, booktitle = {DGaO-Proceedings, 118. Jahrestagung}, year = {2017}, publisher = {Deutsche Gesellschaft für angewandte Optik e.V.}, issn = {1614-8436}, note = {Talk S3} }
118. Annual Conference of the DGaO · Dresden · 2017