Preprint

FZJ-2023-00731

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png ObiWan-Microbi: OMERO-based integrated workflow for annotating microbes in the cloud

Seiffarth, J.FZJ* ; Scherr, T. ; Wollenhaupt, B.FZJ* ; Neumann, O. ; Scharr, H.FZJ* ; Kohlheyer, D.FZJ* ; Mikut, R. ; Nöh, K. (Corresponding author)FZJ*

2022

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Please use a persistent id in citations: http://hdl.handle.net/2128/33787  doi:10.1101/2022.08.01.502297

Abstract: Reliable deep learning segmentation for microfluidic live-cell imaging requires comprehensive ground truth data. ObiWan-Microbi is a microservice platform combining the strength of state-of-the-art technologies into a unique integrated workflow for data management and efficient ground truth generation for instance segmentation, empowering collaborative semi-automated image annotation in the cloud.

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Contributing Institute(s):

1. Biotechnologie (IBG-1)
2. Datenanalyse und Maschinenlernen (IAS-8)

Research Program(s):

1. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)
2. 2171 - Biological and environmental resources for sustainable use (POF4-217) (POF4-217)

Appears in the scientific report 2022

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Database coverage:
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