title: Machine Learning Approach to Automated Quality Identification of Human Induced Pluripotent Stem Cell Colony Images.
abstract: The focus of this research is on automated identification of the quality of human induced pluripotent stem cell (iPSC) colony images. iPS cell technology is a contemporary method by which the patient's cells are reprogrammed back to stem cells and are differentiated to any cell type wanted. iPS cell technology will be used in future to patient specific drug screening, disease modeling, and tissue repairing, for instance. However, there are technical challenges before iPS cell technology can be used in practice and one of them is quality control of growing iPSC colonies which is currently done manually but is unfeasible solution in large-scale cultures. The monitoring problem returns to image analysis and classification problem. In this paper, we tackle this problem using machine learning methods such as multiclass Support Vector Machines and several baseline methods together with Scaled Invariant Feature Transformation based features. We perform over 80 test arrangements and do a thorough parameter value search. The best accuracy (62.4%) for classification was obtained by using a k-NN classifier showing improved accuracy compared to earlier studies.
authors: School of Information Sciences, University of Tampere, Kanslerinrinne 1, FI-33014 Tampere, Finland.
authors: Henry
authors: 0000-0001-6341-7055
authors: H
authors: Joutsijoki
authors: BioMediTech, University of Tampere, Biokatu 12, FI-33520 Tampere, Finland.
authors: Markus
authors: M
authors: Haponen
authors: School of Information Sciences, University of Tampere, Kanslerinrinne 1, FI-33014 Tampere, Finland.
authors: Jyrki
authors: J
authors: Rasku
authors: School of Medicine, University of Tampere, Biokatu 12, FI-33520 Tampere, Finland.
authors: Katriina
authors: 0000-0003-0334-2172
authors: K
authors: Aalto-Setälä
authors: School of Information Sciences, University of Tampere, Kanslerinrinne 1, FI-33014 Tampere, Finland.
authors: Martti
authors: 0000-0003-2298-9553
authors: M
authors: Juhola
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D018929:Cell Culture Techniques; D005189:False Positive Reactions; D005347:Fibroblasts / Q000166:cytology; D006801:Humans; D057026:Induced Pluripotent Stem Cells / Q000166:cytology*; D016018:Least-Squares Analysis; D000069550:Machine Learning; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D011786:Quality Control; D044968:Regenerative Medicine / Q000379:methods; D015203:Reproducibility of Results; D060388:Support Vector Machine