• DocumentCode
    3665072
  • Title

    Automatic classification of neoplastic lesion on gastric biopsy images

  • Author

    Emi Morotomi;Toshiyuki Tanaka

  • Author_Institution
    Department of Science and Technology, Keio University, Kanagawa, Japan
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    60
  • Lastpage
    63
  • Abstract
    In histopathological diagnosis, pathologists observe the biopsy images and diagnose the tumor grade. However, the number of pathologists has been decreasing, so the demand for cancer diagnosis support system has been increasing in recent years. Therefore, this study proposes the method for automatic classification to two classes which are neoplastic lesion, and non-neoplastic lesion. Our method consists of image inputting, region extraction, feature calculation, and discriminant analysis. As the result, our method showed 93.33% accuracy on the neoplastic lesion, and 82.86% accuracy on the non-neoplastic lesion.
  • Keywords
    "Glands","Feature extraction","Biopsy","Lesions","Accuracy","Shape","Cancer"
  • Publisher
    ieee
  • Conference_Titel
    Society of Instrument and Control Engineers of Japan (SICE), 2015 54th Annual Conference of the
  • Type

    conf

  • DOI
    10.1109/SICE.2015.7285506
  • Filename
    7285506