Authors:
Grégory Apou
1
;
Benoît Naegel
1
;
Germain Forestier
2
;
Friedrich Feuerhake
3
and
Cédric Wemmert
1
Affiliations:
1
University of Strasbourg, France
;
2
University of Haute Alsace, France
;
3
Hannover Medical School, Germany
Keyword(s):
Whole Slide Images, Biomedical Image Processing, Segmentation, Classification.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Medical Image Applications
;
Segmentation and Grouping
Abstract:
In recent years, new optical microscopes have been developed, providing very high spatial resolution images called Whole Slide Images (WSI). The fast and accurate display of such images for visual analysis by pathologists and the conventional automated analysis remain challenging, mainly due to the image size (sometimes billions of pixels) and the need to analyze certain image features at high resolution. To propose a decision support tool to help the pathologist interpret the information contained by the WSI, we present a new approach to establish an automatic cartography of WSI in reasonable time. The method is based on an original segmentation algorithm and on a supervised multiclass classification using a textural characterization of the regions computed by the segmentation. Application to breast cancer WSI shows promising results in terms of speed and quality.