A methodology for automated CPA extraction using liver biopsy image analysis and machine learning techniques.

Journal: Computer methods and programs in biomedicine
Published Date: Nov 29, 2016

Abstract

BACKGROUND AND OBJECTIVE: Collagen proportional area (CPA) extraction in liver biopsy images provides the degree of fibrosis expansion in liver tissue, which is the most characteristic histological alteration in hepatitis C virus (HCV). Assessment of the fibrotic tissue is currently based on semiquantitative staging scores such as Ishak and Metavir. Since its introduction as a fibrotic tissue assessment technique, CPA calculation based on image analysis techniques has proven to be more accurate than semiquantitative scores. However, CPA has yet to reach everyday clinical practice, since the lack of standardized and robust methods for computerized image analysis for CPA assessment have proven to be a major limitation.

Authors

  • Markos G Tsipouras
    Division of Gastroenterology, Faculty of Medicine, School of Health Sciences, University of Ioannina, GR45110 Ioannina, Greece; Department of Computer Engineering, School of Applied Technology, Technological Educational Institute of Epirus, Kostakioi, GR47100, Arta, Greece. Electronic address: tsipouras@teiep.gr.
  • Nikolaos Giannakeas
    Division of Gastroenterology, Faculty of Medicine, School of Health Sciences, University of Ioannina, GR45110 Ioannina, Greece; Department of Computer Engineering, School of Applied Technology, Technological Educational Institute of Epirus, Kostakioi, GR47100, Arta, Greece. Electronic address: giannakeas@teiep.gr.
  • Alexandros T Tzallas
    Division of Gastroenterology, Faculty of Medicine, School of Health Sciences, University of Ioannina, GR45110 Ioannina, Greece; Department of Computer Engineering, School of Applied Technology, Technological Educational Institute of Epirus, Kostakioi, GR47100, Arta, Greece. Electronic address: tzallas@teiep.gr.
  • Zoe E Tsianou
    Division of Gastroenterology, Faculty of Medicine, School of Health Sciences, University of Ioannina, GR45110 Ioannina, Greece. Electronic address: z.tsianou@gmail.com.
  • Pinelopi Manousou
    Liver Unit, St Mary's Hospital, Imperial College NHS Trust, London, UK. Electronic address: pinelopi.manousou@imperial.nhs.uk.
  • Andrew Hall
    Department of Histopathology, UCL Medical School, Royal Free Campus, Rowland Hill Street, London NW3 2QG, UK. Electronic address: andrewhall1@nhs.net.
  • Ioannis Tsoulos
    Department of Computer Engineering, School of Applied Technology, Technological Educational Institute of Epirus, Kostakioi, GR47100, Arta, Greece. Electronic address: itsoulos@teiep.gr.
  • Epameinondas Tsianos
    Division of Gastroenterology, Faculty of Medicine, School of Health Sciences, University of Ioannina, GR45110 Ioannina, Greece. Electronic address: etsianos@uoi.gr.

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