Ontology-enhanced vision system for new microscopy imaging challenges

Nicolas Lomenie, Daniel Racoceanu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationAdvances in Bio-Imaging
Subtitle of host publicationFrom Physics to Signal Understanding Issues: State-of-the-Art and Challenges
EditorsNicolas Lomenie, Daniel Racoceanu, Alexandre Gouaillard
Pages157-172
Number of pages16
DOIs
StatePublished - 2012
Externally publishedYes

Publication series

NameAdvances in Intelligent and Soft Computing
Volume120
ISSN (Print)1867-5662

Fingerprint

Dive into the research topics of 'Ontology-enhanced vision system for new microscopy imaging challenges'. Together they form a unique fingerprint.

Cite this