%0 Thesis %1 ernst2010datadriven %A Ernst, Patrick %D 2010 %K anatomy approach atlas data driven fuzzy generation human logic medicine medico quantitative relations set sparql spatial %T A Data-Driven Approach for the Generation of Quantitative Digital Atlases of Human Anatomy %X In medicine spatial relations are important information to describe anatomical facts. Based on them, digital quantitative atlases can be built. The aim of this master’s thesis is to create such atlases using a data-driven approach and to realize a semantic integration of the thereby generated knowledge using Semantic Web technologies. Firstly, a system architecture is explained which allows the data-driven extraction of spatial relations. The relations are formulated using fuzzy sets and fuzzy logic. Based on them, an approach for the creation of two different types of quantitative anatomical atlases is introduced. Single model atlases are constructed by incorporating all information of one particular relation into one overall model representation. For the other atlas type a clustering algorithm is previously applied in order to group anatomies containing similar relations. As result, an extended atlas is defined consisting of multiple single models, whereby one model stands for one cluster. Leveraging those atlases two direct applications are explained. Spatial consistency checks can be used to check the plausibility of the output of automatic object recognition techniques against the quantitative atlases. An evaluation showed that these checks are able to detect incorrect recognitions with an accuracy of 86%. Furthermore, an interface is presented capable to transfer quantitative atlases into qualitative models. On that account, we base on an existing OWL representation provided in advance. The last part of this thesis concerns the retrieval of spatial relations and atlases. Therefore, a SPARQL engine is proposed which directly relies on a spatial database and 3D images. In this context, a complete serialization of all potential relations in RDF is not feasible and the engine must generate query results dynamically, when they are requested. Furthermore, we describe some use cases exemplifying new perspectives which emerge from such a semantic integration. Finally, with the aid of a prototype it will be illustrated how applications could benefit from it.

@mastersthesis{ernst2010datadriven, abstract = {In medicine spatial relations are important information to describe anatomical facts. Based on them, digital quantitative atlases can be built. The aim of this master’s thesis is to create such atlases using a data-driven approach and to realize a semantic integration of the thereby generated knowledge using Semantic Web technologies. Firstly, a system architecture is explained which allows the data-driven extraction of spatial relations. The relations are formulated using fuzzy sets and fuzzy logic. Based on them, an approach for the creation of two different types of quantitative anatomical atlases is introduced. Single model atlases are constructed by incorporating all information of one particular relation into one overall model representation. For the other atlas type a clustering algorithm is previously applied in order to group anatomies containing similar relations. As result, an extended atlas is defined consisting of multiple single models, whereby one model stands for one cluster. Leveraging those atlases two direct applications are explained. Spatial consistency checks can be used to check the plausibility of the output of automatic object recognition techniques against the quantitative atlases. An evaluation showed that these checks are able to detect incorrect recognitions with an accuracy of 86%. Furthermore, an interface is presented capable to transfer quantitative atlases into qualitative models. On that account, we base on an existing OWL representation provided in advance. The last part of this thesis concerns the retrieval of spatial relations and atlases. Therefore, a SPARQL engine is proposed which directly relies on a spatial database and 3D images. In this context, a complete serialization of all potential relations in RDF is not feasible and the engine must generate query results dynamically, when they are requested. Furthermore, we describe some use cases exemplifying new perspectives which emerge from such a semantic integration. Finally, with the aid of a prototype it will be illustrated how applications could benefit from it.}, added-at = {2010-10-07T10:26:31.000+0200}, author = {Ernst, Patrick}, biburl = {https://www.bibsonomy.org/bibtex/2ab07f4ed9de3bc2ba109d03e085d1fd9/patrick6585}, interhash = {4af9ede9b723857bd910e8fdba7af457}, intrahash = {ab07f4ed9de3bc2ba109d03e085d1fd9}, keywords = {anatomy approach atlas data driven fuzzy generation human logic medicine medico quantitative relations set sparql spatial}, month = {July}, school = {University of Technology Kaiserslautern}, timestamp = {2010-10-07T10:26:32.000+0200}, title = {A Data-Driven Approach for the Generation of Quantitative Digital Atlases of Human Anatomy}, year = 2010 }