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Ontology-Enhanced Vision System for New Microscopy Imaging Challenges

  • Nicolas Lomenie
  • Daniel Racoceanu
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 120)

Abstract

Artificial intelligence and computer vision have long been separate fields basically because the data structures to work with and to reason about were rather distinct and non permeable. Ontology-driven systems may have the ability to build a bridge between these two fundamental topics involved in intelligent system design. We provide preliminary insights about this powerful synergy in the field of digitized pathology as a brand new topic in which, like currently for satellite imaging, the amount of raw data and high-level concepts to handle give no other choice but to innovate about the low-level image image processing machine and the knowledge modeling framework integration. Above all, the end-user who is most of the time naive about signal, image and algorithmic issues can thence play the key role in the design of such enhanced vision system.

Keywords

Resource Description Framework Biological Concept Whole Slide Image Tubule Detection Nucleus Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.IPAL CNRS UMI 2955 (I2R/A*STAR, NUS, UJF, TELECOM, UPMC/Sorbonne)ParisFrance

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