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Unifying Semantic Annotation and Querying in Biomedical Images Repositories

by: Daniel Sonntag, and Manuel Möller

In: Proceedings of the International Conference on Knowledge Management and Information Sharing KMIS, Madeira, Portugal (2009) .

Abstract

In the medical domain, semantic image retrieval should provide the basis for the help in decision support and computer aided diagnosis. But knowledge engineers cannot easily acquire the necessary medical knowledge about the image contents. Based on their semantics, we present a set of techniques for annotating images and querying image data sets. The unification of semantic annotation using a GUI and querying using natural dialogue in biomedical image repositories is based on a unified view of the knowledge acquisition process. We use a central RDF repository to capture both medical domain knowledge as well as image annotations and understand medical knowledge engineering as an interactive process between the knowledge engineer and the clinician. Our system also supports the interactive process between the dialogue engineer and the clinician.

BibTeX record

@inproceedings{SonntagMoeller09KMIS,
  abstract = {In the medical domain, semantic image retrieval should provide the basis for the help in decision support and computer aided diagnosis. But knowledge engineers cannot easily acquire the necessary medical knowledge about the image contents. Based on their semantics, we present a set of techniques for annotating images and querying image data sets. The unification of semantic annotation (using a GUI) and querying (using natural dialogue) in biomedical image repositories is based on a unified view of the knowledge acquisition process. We use a central RDF repository to capture both medical domain knowledge as well as image annotations and understand medical knowledge engineering as an interactive process between the knowledge engineer and the clinician. Our system also supports the interactive process between the dialogue engineer and the clinician.},
  added-at = {2010-10-31T22:46:15.000+0100},
  author = {Sonntag, Daniel and M{\"o}ller, Manuel},
  biburl = {http://www.bibsonomy.org/bibtex/298701ed0cef454fc2aea0347bd7d749a/flint63},
  booktitle = {Proceedings of the International Conference on Knowledge Management and Information Sharing (KMIS), Madeira, Portugal},
  file = {Preprint:2009/SonntagMoeller09KMIS.pdf:PDF},
  interhash = {1b9646fc1a24fe5567e8b9beb1a4e94e},
  intrahash = {98701ed0cef454fc2aea0347bd7d749a},
  keywords = {information knowledge zzz.a.it09 paper multimodal semantic image web retrieval zzz.th.c4 dfki health ai v1010 search zzz.th.med processing dialog},
  timestamp = {2010-10-31T22:46:15.000+0100},
  title = {Unifying Semantic Annotation and Querying in Biomedical Images Repositories},
  year = 2009
}

Endnote record

%0 Conference Paper
%1 SonntagMoeller09KMIS
%A Sonntag, Daniel
%A M{\"o}ller, Manuel
%B Proceedings of the International Conference on Knowledge Management and Information Sharing (KMIS), Madeira, Portugal
%D 2009
%K 
%T Unifying Semantic Annotation and Querying in Biomedical Images Repositories
%X In the medical domain, semantic image retrieval should provide the basis for the help in decision support and computer aided diagnosis. But knowledge engineers cannot easily acquire the necessary medical knowledge about the image contents. Based on their semantics, we present a set of techniques for annotating images and querying image data sets. The unification of semantic annotation (using a GUI) and querying (using natural dialogue) in biomedical image repositories is based on a unified view of the knowledge acquisition process. We use a central RDF repository to capture both medical domain knowledge as well as image annotations and understand medical knowledge engineering as an interactive process between the knowledge engineer and the clinician. Our system also supports the interactive process between the dialogue engineer and the clinician.