Automatic Detection of Good/Bad Colonies of iPS Cells Using Local Features

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9352)


In this paper we propose a method able to automatically detect good/bad colonies of iPS cells using local patches based on densely extracted SIFT features. Different options for local patch classification based on a kernelized novelty detector, a 2-class SVM and a local Bag-of-Features approach are considered. Experimental results on 33 images of iPS cell colonies have shown that excellent accuracy can be achieved by the proposed approach.


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Authors and Affiliations

  1. 1.Department of Information EngineeringHiroshima UniversityHiroshimaJapan
  2. 2.School of Bioscience and BiotechnologyTokyo University of TechnologyTokyoJapan
  3. 3.Biotechnology Research Institute for Drug DiscoveryAISTTokyoJapan

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