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Application of a deep learning-based image analysis and live-cell imaging system for quantifying adipogenic differentiation kinetics of adipose-derived stem/stromal cells.
Brooks, Patrick Terrence; Munthe-Fog, Lea; Rieneck, Klaus; Banch Clausen, Frederik; Rivera, Olga Ballesteros; Kannik Haastrup, Eva; Fischer-Nielsen, Anne; Svalgaard, Jesper Dyrendom.
Affiliation
  • Brooks PT; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
  • Munthe-Fog L; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
  • Rieneck K; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
  • Banch Clausen F; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
  • Rivera OB; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
  • Kannik Haastrup E; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
  • Fischer-Nielsen A; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
  • Svalgaard JD; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Adipocyte ; 10(1): 621-630, 2021 12.
Article in En | MEDLINE | ID: mdl-34747303
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Adipogenesis / Deep Learning Type of study: Prognostic_studies / Qualitative_research Language: En Journal: Adipocyte Year: 2021 Document type: Article
Fulltext
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Adipogenesis / Deep Learning Type of study: Prognostic_studies / Qualitative_research Language: En Journal: Adipocyte Year: 2021 Document type: Article