2016
DOI: 10.1166/jmihi.2016.1971
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Improving Mesenchymal Stem Cell Classification Using Machine Learning Techniques

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“…The typically reported challenges of applying such methods in live cell imaging pertain to segmentation accuracy; the consequent time required to separate accurately and inaccurately segmented images, as well as robustness across cell types and human operators [128]. Machine learning methods ease these challenges by automating segmentation and facilitating classification [129]. Deep learning, a category of machine learning, has recently shown exceptional performance in this area by offering the advantage of independently learning key features.…”
Section: Imaging and Other Label-free Methodsmentioning
confidence: 99%
“…The typically reported challenges of applying such methods in live cell imaging pertain to segmentation accuracy; the consequent time required to separate accurately and inaccurately segmented images, as well as robustness across cell types and human operators [128]. Machine learning methods ease these challenges by automating segmentation and facilitating classification [129]. Deep learning, a category of machine learning, has recently shown exceptional performance in this area by offering the advantage of independently learning key features.…”
Section: Imaging and Other Label-free Methodsmentioning
confidence: 99%