Texture Descriptors Ensembles Enable Image-Based Classification of Maturation of Human Stem Cell-Derived Retinal Pigmented Epithelium.

Journal: PloS one
Published Date: Jan 1, 2016

Abstract

AIMS: A fast, non-invasive and observer-independent method to analyze the homogeneity and maturity of human pluripotent stem cell (hPSC) derived retinal pigment epithelial (RPE) cells is warranted to assess the suitability of hPSC-RPE cells for implantation or in vitro use. The aim of this work was to develop and validate methods to create ensembles of state-of-the-art texture descriptors and to provide a robust classification tool to separate three different maturation stages of RPE cells by using phase contrast microscopy images. The same methods were also validated on a wide variety of biological image classification problems, such as histological or virus image classification.

Authors

  • Loris Nanni
    DEI, University of Padova, Via Gradenigo 6, 35131 Padova, Italy.
  • Michelangelo Paci
    Department of Electronics and Communications Engineering, Tampere University of Technology, BioMediTech, Tampere, Finland.
  • Florentino Luciano Caetano dos Santos
    Department of Electronics and Communications Engineering, Tampere University of Technology, BioMediTech, Tampere, Finland.
  • Heli Skottman
    University of Tampere, BioMediTech, Tampere, Finland.
  • Kati Juuti-Uusitalo
    University of Tampere, BioMediTech, Tampere, Finland.
  • Jari Hyttinen
    Department of Electronics and Communications Engineering, Tampere University of Technology, BioMediTech, Tampere, Finland.

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