SLAS TECHNOLOGY · 2014 · 47 citations · 11 references
Tissue EngineeringEngineeringAdult Stem CellCell CultureBiomedical EngineeringRegenerative MedicineIpsc GrowthInduced Pluripotent Stem CellsStem CellsIpsc ColoniesMedical Image ComputingCell EngineeringCell BiologyEmbryonic Stem CellsInduced Pluripotent Stem CellDevelopmental BiologyMicroscope Image ProcessingBioimage AnalysisBiomedical ImagingStem Cell ResearchStem-cell TherapyMorphology-based EvaluationTissue CultureMedicineIpsc CulturesEmbryonic Stem CellCell Detection
Due to the rapid adoption and use of human induced pluripotent stem cells (iPSCs) in recent years, there is a need for new technologies that standardize the evaluation of iPSCs to allow the objective comparison of results across different experiments and groups. In this article, we present a noninvasive, fully automated, and analytical system for morphology-based evaluation of iPSC cultures that consists of time-lapse microscopy and novel image analysis software. The presented system acquires low-light phase-contrast images of iPSC growth collected during a period of several days in culture, measures geometrical- and texture-based features of iPSC colonies throughout time, and derives a set of six biologically relevant features to automatically rank the quality of the cell culture. In a study of 94 iPSC cultures, we demonstrated the accuracy of the system by comparing the automated ranking with an independent expert evaluation based on visual review of the time-lapse movies. To our knowledge, this is the first demonstration of a fully automated and objective assessment of iPSC culture quality using noninvasive methods.
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Chih-Chung Chang, Chih‐Jen Lin · ACM Transactions on Intelligent Systems and Technology · 2011 · 41.1K citations
Data Classification, Support Vector Machine, Classification Method +15
Chemically defined conditions for human iPSC derivation and culture
Guokai Chen, Daniel R. Gulbranson, Zhonggang Hou et al. · Nature Methods · 2011 · 1.5K citations · Full text