• DocumentCode
    178505
  • Title

    Segmenting Reddish Lesions in Capsule Endoscopy Images Using a Gastrointestinal Color Space

  • Author

    Hai Vu ; Echigo, Tomio ; Imura, Yuma ; Yanagawa, Yukiko ; Yagi, Yasushi

  • Author_Institution
    Int. Res. Inst. MICA, Hanoi Univ. of Sci. & Technol., Hanoi, Vietnam
  • fYear
    2014
  • fDate
    24-28 Aug. 2014
  • Firstpage
    3263
  • Lastpage
    3268
  • Abstract
    Segmenting reddish lesions in capsule endoscopy (CE) images is an initial step for further computer-assisted applications such as image enhancement, abnormal measurement/tracking, and so on. In this paper, we propose an automatic segmentation method that is successful even with CE image including unclear reddish lesions. To obtain this, the proposed method seeks good features to discriminate the reddish lesions from normal tissues. For implementations, we first extract only meaningful regions in a CE image through a pre-segmentation step. The proposed features then are extracted for the meaningful regions in stead of the whole image. We approaches segmentation task through considering a statistical operator for the extracted features, that is local mean image. Candidates of the abnormal regions are located in the local mean image with assistants of a diffusion process. Evaluations in the experiments confirm effectiveness of the proposed method with both qualitative and quantitative measurement.
  • Keywords
    biodiffusion; endoscopes; feature extraction; image colour analysis; image segmentation; medical image processing; statistical analysis; CE image; abnormal measurement; automatic segmentation method; capsule endoscopy images; computer-assisted applications; diffusion process; feature extraction; gastrointestinal color space; image enhancement; local mean image; reddish lesion segmentation; statistical operator; Educational institutions; Endoscopes; Feature extraction; Hemorrhaging; Image color analysis; Image segmentation; Lesions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2014 22nd International Conference on
  • Conference_Location
    Stockholm
  • ISSN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2014.562
  • Filename
    6977274