Published November 24, 2023 | Version v3
Dataset Open

Large Spots DeepMIB project, synthetic dataset for testing 2D semantic segmentation

Authors/Creators

  • 1. University of Helsinki

Description

A complete DeepMIB project with a synthetic dataset generated for quick tests of semantic segmentation approaches.
The dataset includes a trained DeepLabV3-Resnet18 network for detection of large spots on a black background. 

The network can be opened by loading "2D_LargeSpots_2cl_DeepLabV3.mibCfg" file by

  • MIB->Menu->Tools->Deep learning segmentation->Options tab->Config files->Load 
  • Drag and drop of the config file into DeepMIB window

Microscopy Image Browser: https://mib.helsinki.fi

Files

2D_LargeSpots_2cl_DeepLabV3.zip

Files (62.2 MB)

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md5:ccbd9f8209c6bf87811cee4bb9eafecd
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Additional details

References

  • DeepMIB: User-friendly and open-source software for training of deep learning network for biological image segmentation I. Belevich, and E. Jokitalo PLoS Comput Biol. 2021 Mar 2;17(3):e1008374. doi: 10.1371/journal.pcbi.1008374
  • Microscopy Image Browser: A platform for segmentation and analysis of multidimensional datasets I. Belevich, M. Joensuu, D. Kumar, H. Vihinen and E. Jokitalo PLoS Biology 2016 Jan 4;14(1):e1002340. doi: 10.1371/journal.pbio.1002340