BigData III: Frameworks for Quantitative Analysis of Large Image Data [NEUBIAS Academy @Home]
Channel: NEUBIAS
Date: 2021-02-17

BIG DATA III: Frameworks for Quantitative Analysis of Large Image Data
26 January, 2021
Presenters:
Anna Kreshuk, Group Leader at EMBL (Heidelberg, DE) and ilastik project leader.
Jean-Yves Tinevez, Facility manager at Pasteur Institute (Paris, France) and lead developer of MaMuT/Mastodon, co-developer of TrackMate, BDV, more...
Matthias Arzt, software developer at MPI-CBG (Dresden, DE), co-developer of Imglib2-LabKit.

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Moderators:
Marion Louveaux, Anna Klemm, Ofra Golani, Rocco D’Antuono, Julien Colombelli

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Contact: info@neubiasacademy.org

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Q&A posted on image.sc Forum:
https://forum.image.sc/t/neubias-academy-home-webinar-image-big-data-iii-frameworks-for-the-quantitative-analysis-of-large-images-questions-answers/48414/5

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Content:
1. Image segmentation with Labkit on GPU and HPC cluster (MA, 15 min + 5 min). Labkit is a fairly easy to use FIJI Plugin for image segmentation. It allows to perform pixel classification even on large images. You will see the basic usage of the tool, as well as the recently introduced support for NVIDIA graphic cards. The support for GPU dramatically reduces computation times. Finally you will see how to process truely large images on a HPC cluster using Labkit.

2. Image segmentation with ilastik – scaling up. ilastik is a simple tool for machine learning-based image segmentation, object classification and tracking. We will quickly introduce how to use ilastik on bigger datasets, both for training and for batch processing. We will give tips and examples on how to make it faster and how to run from the command line.

3. Using Mastodon to track large data hosted remotely (JYT, 15 min + 5 min). Mastodon is a new cell tracking framework made to harness large images and the large number annotations they can yield. In this short presentation we will introduce it briefly, and demonstrate its capabilities. In particular, because Mastodon is based on the BDV file format, it can be tuned to work on large images hosted remotely, without the need for the user to download or copy the data locally. We will showcase this capabilities on on a large dataset borrowed from the Cell Tracking Challenge.

Moderators:
Marion Louveaux, Anna Klemm, Ofra Golani, Rocco D’Antuono, Julien Colombelli