Presentation
9 March 2020 Digital imaging biomarkers for quantitative guidance of pluripotent stem cell passaging (Conference Presentation)
Author Affiliations +
Abstract
We investigate the process of induced pluripotent stem cell (iPSC) passaging. Subcultures are created by transferring cells from iPSC cultures to new growth mediums. We found that standard protocols for iPSC passaging primarily have researchers use their eyesight to determine cultures' confluencies and cell counts. With the consequences of inaccurate estimates going as far as cell death due to passaging at the suboptimal confluency, we sought to circumvent human error and develop a culture analyzing algorithm (CAA) that calculates both confluency and cell count primarily through Otsu's method. We incorporate multi-image machine learning into our CAA, improving its ability to recognize colonies as it is fed more images. In comparing our algorithm to standard protocols, we found that there was a significant percent difference between both methods when measuring the confluency and cell count of iPSC cultures. Through further refinement, we hope to streamline our CAA for large-scale use.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daniel S. Gareau, Jack Tapay, Tomomi Haremaki, and James Browning "Digital imaging biomarkers for quantitative guidance of pluripotent stem cell passaging (Conference Presentation)", Proc. SPIE 11243, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVIII, 112430J (9 March 2020); https://doi.org/10.1117/12.2550829
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KEYWORDS
Stem cells

Algorithm development

Digital imaging

Detection and tracking algorithms

Image segmentation

Medical research

Analytical research

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