• DocumentCode
    3684581
  • Title

    Image segmentation of pyramid style identifier based on Support Vector Machine for colorectal endoscopic images

  • Author

    Takumi Okamoto;Tetsushi Koide;Koki Sugi;Tatsuya Shimizu;Anh-Tuan Hoang;Toru Tamaki;Bisser Raytchev;Kazufumi Kaneda;Yoko Kominami;Shigeto Yoshida;Hiroshi Mieno;Shinji Tanaka

  • Author_Institution
    Research Institute for Nanodevice and Bio Systems, Hiroshima University, 739-8527, Japan
  • fYear
    2015
  • Firstpage
    2997
  • Lastpage
    3000
  • Abstract
    With the increase of colorectal cancer patients in recent years, the needs of quantitative evaluation of colorectal cancer are increased, and the computer-aided diagnosis (CAD) system which supports doctor´s diagnosis is essential. In this paper, a hardware design of type identification module in CAD system for colorectal endoscopic images with narrow band imaging (NBI) magnification is proposed for real-time processing of full high definition image (1920 × 1080 pixel). A pyramid style image segmentation with SVMs for multi-size scan windows, which can be implemented on an FPGA with small circuit area and achieve high accuracy, is proposed for actual complex colorectal endoscopic images.
  • Keywords
    "Support vector machines","Design automation","Cancer","Kernel","Computer aided diagnosis","Yttrium","Imaging"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7319022
  • Filename
    7319022