@inproceedings{Moeller2010a,
  abstract = {We present a rule-based system using medical expert knowledge represented in a formal ontology to check the results of automatic medical object recognition algorithms for anatomical plausibility. Our system is based on the comprehensive Foundation Model of Anatomy ontology and uses a set of forward rules executed by a Prolog engine. In our evaluation we describe how this approach can be used to check the results of a state-of-the-art medical object recognition system for 3D CT volume data sets for anatomical plausibility. Our results show that the combination of sub-symbolic object recognition, medical domain knowledge represented in formal ontologies and yields an improved overall recognition precision.},
  added-at = {2010-07-07T09:29:21.000+0200},
  address = {Kuching, Sarawak, Malaysia},
  author = {M\"oller, Manuel and Ernst, Patrick and Dengel, Andreas},
  biburl = {http://www.bibsonomy.org/bibtex/2ee27dfaa575bcd3eaece45dddc102ba9/manuelm},
  booktitle = {Proc. of the 2nd Malaysian Joint Conference on Artificial Intelligence 	(MJCAI 2010)},
  interhash = {5cdcfc37ca8e0d748b51add1b95355b9},
  intrahash = {ee27dfaa575bcd3eaece45dddc102ba9},
  keywords = {medico},
  month = {26th -- 30th},
  timestamp = {2010-07-07T09:29:21.000+0200},
  title = {Spatial Reasoning for Plausibility Checks of Medical Object Recognition
	Results Using the Foundational Model of Anatomy},
  year = 2010
}