Type of presentation: Poster

ID-9-P-2980 Microscopy Image Browser is a new open-source tool for segmentation and analysis of microscopy datasets

Belevich I.¹, Joensuu M.¹, Vihinen H.¹, Jokitalo E.¹

¹Electron Microscopy Unit, Institute of Biotechnology, PO Box 56 (Viikinkaari 9), University of Helsinki, 00014, Finland

ilya.belevich@helsinki.fi

Rapid development of multidimensional microscopy imaging techniques during recent years has raised number of questions about effective image processing, visualization and analysis of the obtained datasets. Most universities worldwide provide access to the modern imaging techniques so that descriptive multidimensional datasets of the desired specimen can be fairly easily obtained by any researcher. After acquisition the datasets have to be analyzed and quite often the detailed analysis is impossible without segmentation (creating of a model) of objects of interest out of the multidimensional data. It seems that the segmentation is the most time consuming part of the image analysis routine. For example, it may take up to a month to properly segment a single electron tomogram. The slowness of the process is caused by two main factors: limited variety of good segmentation algorithms and software tools (even commercial ones) that can be used to facilitate the modelling. As a result, amount of collected and not properly processed data is much higher than the amount of produced results.

In my talk I would like to address this problem and present a free, open-source software package, Microscopy Image Browser (MIB), which can be used for image processing, analysis, segmentation and visualization of multidimensional datasets. MIB seems to be quite effective and we already utilized it in few projects [1-4]. The program is written under Matlab environment which opens large variety of options for its extension with different tools and filters available thought the Matlab community. Even though the focus of the program is 3D segmentation of electron microscopy datasets, MIB is rather universal and can be used to perform analysis and visualization of multidimensional datasets obtained by light microscopy.

1. Puhka et al. Mol. Biol.Cell 23, (2012) 2424-.
2. Anttonen et al., Sci. Rep. 2, (2012) 978-.
3. Joensuu M et al. Mol. Biol.Cell (2014) Epub ahead of print.
4. Majaneva M et al. J Euk Microbiol (2014) accepted.

Mervi Lindman and Antti Salminen are acknowledged for excellent technical assistance. This work was supported by Academy of Finland (project 131650, E.J.) and Biocenter of Finland.

Fig. 1: The user interface window of Microscopy Image Browser	Fig. 2: Serial Block Face Scanning Electron Microscopy dataset of Tripanosoma brucei with one tripanosome segmented from the 3D volume using MIB. Dimensions: 11.3 x 15.4 x 6.8 µm, voxel size: 14 x 14 x 30 nm. The lower part of the figure shows visualization of individual organelles from the same model. The models were visualized using Amira.
Fig. 3: A model of Golgi apparatus and endoplasmic reticulum exit sites from a dataset obtained by Electron Tomography. The segmentation was done using MIB and the rendering done with Amira.