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SUMMARY:Cell scaffold dimensional metrology using high resolution 3D print
 ing methods and machine learning - Filippos Tourlomousis\, Stevens Institu
 te of Technology\, Hoboken\, United States
DTSTART:20170207T160000Z
DTEND:20170207T163000Z
UID:TALK69744@talks.cam.ac.uk
CONTACT:Ilana Spilka
DESCRIPTION:The first part of the talk will focus on the Melt Electrospinn
 ing Writing process\, an emerging 3D printing technology that utilizes pol
 ymer melts for the fabrication of biomaterial scaffolds with cellular rele
 vant geometrical features (10 - 50 μm) that are unattainable with current
  3D printing technologies. Using immunofluorescent staining and confocal m
 icroscopy\, detailed cell shape characterization is performed by detecting
  and quantifying important cell morphometry features.  Machine learning al
 gorithms are used for important feature extraction and cell shape classifi
 cation tasks. These fundamental cell-scaffold dimensional metrology studie
 s allow us to inform our fabrication process and engineer fibrous microenv
 ironments that promote a homogeneous cell population.
LOCATION:Online
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