77 3 Towards Automatization of Organoid Analysis: A Deep Learning Approach to Localize and Quantify Organoids Images analysis; (2) Development of an e-Science service that detects, segments, and analyses organoids images; (3) Testing the system on a use case to evaluate the area and growth analysis; and (4) Providing public data for the use case. Fig. 1. Organoids display high variability in size and morphology in culture. (A) Representative sketch of a hydrogel dome. Line bars represent the different Z-stacks of the dome. (B) Representative Sketch of the distribution of organoids in a hydrogel dome. i) Organoids accumulate in one area overlapping. ii) Organoids around the edge of the hydrogel dome develop to bigger sizes and more complex morphologies. iii) Organoids in the middle of the dome display smaller sizes and more spherical morphologies. (C) Representative brightfield images exemplifying the different distributions and morphologies described in B. METHOD AND IMPLEMENTATION Murine liver progenitor organoids culture Ductal fragments from male C57BL/6J mice between 3 to 5 weeks of age (Jackson Laboratory, Bar Harbor, ME, USA) were isolated following the published protocol by Broutier et al16. Ethical approval was obtained from the Central Authority for Scientific Procedures on Animals (CCD) of the Netherlands and from the University of Groningen Ethical Committee for Animal Experiments (Animal Use Protocol Number: 171504-01-001/3). These fragments were kept in expansion medium consisting of Advanced DMEM/ F12 supplemented with 10mM HEPES, 1% (v/v) GlutaMax, 1% (v/v) PenicillinStreptomycin (all Gibco), 1% B-27 Supplement (Invitrogen) 1% N-2 Supplement (Invitrogen), 10mM Nicotinamide (Sigma Aldrich), 1.25mM N-Acetylcysteine
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