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Microscopy Image Browser: an open-source platform for segmentation and analysis of multidimensional datasets

Abstract number:

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Meeting: The 16th European Microscopy Congress 2016

Session: Instrumentation and Methods

Topic: Quantitative imaging and image processing

Presentation Form: Poster

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Ilya Belevich (1), Merja Joensuu (1), Darshan Kumar (1), Helena Vihinen (1), Eija Jokitalo (1)

1. Institute of Biotechnology, University of Helsinki, Helsinki, Finlande

Keywords: image processing, matlab, models, multidimensional, Segmentation

Understanding the structure – function relationship of cells and cell organelles in their natural context requires multidimensional imaging. Recent technical advances especially in multimodal 3D-5D imaging techniques have enabled a new insight into the morphology of tissues, cells and organelles. As the performance and access to such techniques are improving, the amounts of collected data are growing exponentially posing a question about effective processing, visualization, and analysis of these large datasets. Quite often the detailed analysis of multidimensional data is impossible without segmentation of objects of interest out of the volume (creating of a model). Usually the segmentation is the most time consuming and challenging 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 number of good software tools (even commercial ones) and segmentation algorithms that can be applied to facilitate the modeling. As a result, the real potential of the collected data is not completely realized.

Here, we present a free user-friendly software package (Microscopy Image Browser, MIB) for effective segmentation and image processing of multidimensional datasets that improves and facilitates the full utilization of acquired data and enables quantitative analysis of morphological features. MIB is written in Matlab language which is familiar to many researchers and available for main common operating systems (Windows, Mac and Linux); alternatively MIB is also distributed as a standalone package for both Windows and Mac OS. The access to the code and the open-source environment enables fine tuning and possibility of adding new plug-ins to customize MIB for specific needs of any research project.

Even though the focus of the program is 3D segmentation of electron microscopy datasets, MIB is rather universal and can be used to perform segmentation, analysis and visualization of 2D-4D datasets obtained by light microscopy.

We already utilized MIB in more than 10 scientific research projects, where it allowed us to facilitating the segmentation part of the image processing workflow significantly. Here we demonstrate its successful application by presenting results of segmentation and quantification of cells and different cellular organelles imaged using various electron and light microscopy techniques.

Figures:

MIB is written in Matlab and distributed as free-ware open-source software. Matlab itself is mostly a collection of functions that may be difficult to use by novices. To improve the usability, MIB includes an intuitive graphical user interface. The detailed installation instructions and tutorials can be found on the MIB website.

A collage image of a graphical user interface of Microscopy Image Browser (MIB) and a 3D model of Trypanosoma brucei. The dataset was obtained with Serial Block Face Scanning Electron Microscopy and processed and segmented using MIB. The resulting model was rendered using Amira (FEI) and the final collage assembled using Adobe Photoshop.

To cite this abstract:

Ilya Belevich, Merja Joensuu, Darshan Kumar, Helena Vihinen, Eija Jokitalo; Microscopy Image Browser: an open-source platform for segmentation and analysis of multidimensional datasets. The 16th European Microscopy Congress, Lyon, France. https://emc-proceedings.com/abstract/microscopy-image-browser-an-open-source-platform-for-segmentation-and-analysis-of-multidimensional-datasets/. Accessed: December 2, 2023
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