• DocumentCode
    3344464
  • Title

    Improving histology images segmentation through spatial constraints and supervision

  • Author

    Herve, Nicolas ; Servais, Aude ; Thervet, Eric ; Olivo-Marin, Jean-Christophe ; Meas-Yedid, Vannary

  • Author_Institution
    Quantitative Image Anal. Unit, Inst. Pasteur, Paris, France
  • fYear
    2010
  • fDate
    26-29 Sept. 2010
  • Firstpage
    3633
  • Lastpage
    3636
  • Abstract
    We introduce two approaches to improve an existing color segmentation technique based on a Split and Merge quantization process for the study of stained histological images. We propose to modify the merge criterion : first, we include a spatial constraints heuristic; then we suggest the use of supervision and a more elaborated visual features representation. We tested these approaches on a renal biopsies dataset to automatically quantify interstitial fibrosis and show that supervision brings very significant improvements.
  • Keywords
    biological tissues; image colour analysis; image segmentation; medical image processing; color segmentation technique; histology image segmentation; interstitial fibrosis; spatial constraint heuristic; spatial supervision; split-and-merge quantization process; visual features representation; Color; Image color analysis; Image segmentation; Merging; Pixel; Quantization; Support vector machines; Color segmentation; color quantization; heuristic; histology; learning framework; spatial constraints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2010 17th IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-7992-4
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2010.5652083
  • Filename
    5652083