Correlated Imaging Series: Multi-modal big image data exploration and sharing
Published December 13, 2021
On Friday, December 17that 13:00 CET, Christian Tischer of EMBL delivers a lecture on “Multi-modal big image data exploration and sharing”, as part of the Correlated Imaging Series, brought to you by COMULIS and Euro-BioImaging.
Abstract:
Multimodal image datasets can comprise several TB of hundreds of images of different spatial resolution and different spatial extent. In addition, there can be thousands of objects that have been segmented in these images. To address the challenge of efficient scientific exploration of such datasets we developed MoBIE, a free and open-source platform for multimodal big image data exploration and sharing. MoBIE is an easy to install Fiji plugin, leveraging the lazy evaluation framework provided by ImgLib2 and BigDataViewer for smooth browsing of TB sized data sets on a standard laptop computer. Both file system and object store backends for image data hosting are supported as well as GitHub based storage of tabular data. MoBIE provides rich functionality for segmentation exploration as well as an expressive JSON schema for the specification of various views on a complex data set. We will also discuss the interplay of MoBIE with the upcoming OME.Zarr file format.
About Christian Tischer
Christian Tischer studied physics in Heidelberg, followed by PhD at EMBL with Philippe Bastiaens working on microscope development and signalling in mammalian cells. Subsequently, he did a postdoc with Marileen Dogertom at AMOLF in the Netherlands working on microtubule dynamics. From 2009 until 2018, he worked at EMBL's Advanced Light Microscopy Facility (ALMF) supporting scientists with both microscopy and image analysis. Since end of 2018, Christian’s focus shifted completely towards image analysis support and he is now running EMBL’s Centre for Bioimage Analysis (CBA).
Friday, December 17th at 13:00 CET
Join via internet:
https://us02web.zoom.us/j/760003029
or via phone:
Meeting ID: 760 003 029
Find your local number: https://zoom.us/u/acj97wMY13
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