• DocumentCode
    2723972
  • Title

    Graph-based multi-resolution segmentation of histological whole slide images

  • Author

    Roullier, V. ; Ta, V.-T. ; Lézoray, O. ; Elmoataz, A.

  • Author_Institution
    GREYC, Univ. de Caen Basse-Normandie, Caen, France
  • fYear
    2010
  • fDate
    14-17 April 2010
  • Firstpage
    153
  • Lastpage
    156
  • Abstract
    In this paper, we present a graph-based multi-resolution approach for mitosis extraction in breast cancer histological whole slide images. The proposed segmentation uses a multi-resolution approach which reproduces the slide examination done by a pathologist. Each resolution level is analyzed with a focus of attention resulting from a coarser resolution level analysis. At each resolution level, a spatial refinement by semi-supervised clustering is performed to obtain more accurate segmentation around edges. The proposed segmentation is fully unsupervised by using domain specific knowledge.
  • Keywords
    biomedical optical imaging; cancer; graph theory; image resolution; image segmentation; mammography; medical image processing; pattern clustering; breast cancer; coarser resolution level analysis; domain specific knowledge; graph-based multi-resolution segmentation; histological whole slide imaging; mitosis extraction; semi-supervised clustering; spatial refinement; Breast cancer; Decision making; Focusing; Hilbert space; Image segmentation; Lymph nodes; Medical treatment; Microscopy; Multiresolution analysis; Spatial resolution; Breast cancer; Graph; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
  • Conference_Location
    Rotterdam
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-4125-9
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2010.5490390
  • Filename
    5490390