Ontology-driven image analysis for histopathological images

  • Authors:
  • Ahlem Othmani;Carole Meziat;Nicolas Loménie

  • Affiliations:
  • French National Center for Scientific Research, IPAL joint lab, UMI CNRS, Institute for Infocomm Research, A*STAR;French National Center for Scientific Research, IPAL joint lab, UMI CNRS, Institute for Infocomm Research, A*STAR;French National Center for Scientific Research, IPAL joint lab, UMI CNRS, Institute for Infocomm Research, A*STAR

  • Venue:
  • ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
  • Year:
  • 2010

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Abstract

Ontology-based software and image processing engine must cooperate in new fields of computer vision like microscopy acquisition wherein the amount of data, concepts and processing to be handled must be properly controlled. Within our own platform, we need to extract biological objects of interest in huge size and high-content microscopy images. In addition to specific low-level image analysis procedures, we used knowledge formalization tools and high-level reasoning ability of ontology-based software. This methodology made it possible to improve the expressiveness of the clinical models, the usability of the platform for the pathologist and the sensitivity or sensibility of the low-level image analysis algorithms.