Title
Combining patient metadata extraction and automatic image parsing for the generation of an anatomic atlas
Abstract
We present a system that integrates ontology-based metadata extraction from medical images with a state-of-the-art object recognition algorithm for 3D volume data sets generated by Computed Tomography scanners. Extracted metadata and automatically generated medical image annotations are stored as instances of OWL classes. This system is applied to a corpus of over 750 GB of clinical image data. A spatial database is used to store and retrieve 3D representations of the generated medical image annotations. Our integrated data representation allows us to easily analyze our corpus and to estimate the quality of image metadata. A rule-based system is used to check the plausibility of the output of the automatic object recognition technique against the Foundational Model of Anatomy ontology. All combined, these methods are used to determine an appropriate set of metadata and image features for the automatic generation of a spatial atlas of human anatomy.
Year
DOI
Venue
2010
10.1007/978-3-642-15387-7_33
KES (1)
Keywords
Field
DocType
patient metadata extraction,metadata extraction,rule-based system,medical image,extracted metadata,automatic image,medical image annotation,image feature,image metadata,anatomic atlas,volume data,integrated data representation,clinical image data,computed tomography,spatial database,object recognition,data representation,image features,rule based system
Metadata,Automatic image annotation,External Data Representation,Information retrieval,Data element,Feature (computer vision),Computer science,Foundational Model of Anatomy,Spatial database,Cognitive neuroscience of visual object recognition
Conference
Volume
ISSN
ISBN
6276
0302-9743
3-642-15386-0
Citations 
PageRank 
References 
1
0.41
7
Authors
7
Name
Order
Citations
PageRank
Manuel Moller1698.77
Patrick Ernst2706.51
Michael Sintek32305212.92
Sascha Seifert4958.08
Gunnar Grimnes513920.78
Alexander Cavallaro611114.22
Andreas Dengel71926280.42