Abstract
We present an advanced approach to representing knowledge about breast radiographs or mammograms which has advantages in terms of both usability and software engineering. The approach uses ontologies to create not merely a class hierarchy for a vocabulary but a full formal representation and, further, takes advantage of reasoning with description logic to provide application behaviour. The ontologies support a disjoint representation of graphical features and their interpretation in terms of medical findings. This separation of image features and medical findings allows the representation of different conceptual interpretations of the same graphical object, allowing different opinions of radiologists to be used in reasoning, which makes the approach useful for describing images to be used in computer-based learning and other applications. Three applications are discussed in detail: assessment of overlap in annotations, a conceptual consistency check in radiology training, and modelling temporal changes in parenchymal patterns. Reasoner usage, software testing, and implementation in Java are presented. The results show that, despite performance problems using the current implementations of reasoners, the description logic approach can be useful in practical applications.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
American College of Radiology (ACR). Illustrated breast imaging reporting and data system (BI-RADS). American College of Radiology, Reston, VA (1998)
Qi, D.: Development and evaluation of an ontology for a mammographic computer aided diagnosis system (2006), Ph.D. Thesis, Aberystwyth, 56-17272
Horridge, M., Drummond, N., Goodwin, J., Rector, A., Stevens, R., Wang, H.: The Manchester OWL syntax. In: OWL: Experiences and Directions (OWLED 2006), Athens, Georgia, CEUR (2006)
Dasmahapatra, S., Dupplaw, D., Hu, B., Lewis, H., Lewis, P., Shadbolt, N.: Facilitating multi-disciplinary knowledge-based support for breast cancer screening. International Journal of Healthcare Technology and Management 7(5), 403–420 (2006) ISSN 1368-2156
Iakovidis, D.K., Schober, D., Boeker, M., Schulz, S.: An Ontology of Image Representations for Medical Image Mining. In: Proc. IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB), Cyprus (2009) ISBN: 978-1-4244-5379-5
Langlotz, C.P.: RadLex: a new method for indexing online educational materials. Radiographics 26(6), 1595–1597 (2006)
Sun, S., Taylor, P., Wilkinson, L., Khoo, L.: An Ontology to Support Adaptive Training for Breast Radiologists. In: Krupinski, E.A. (ed.) IWDM 2008. LNCS, vol. 5116, pp. 257–264. Springer, Heidelberg (2008)
Sun, S., Taylor, P., Wilkinson, L., Khoo, L.: Individualised training to address variability of radiologists’ performance. In: Proceedings of the SPIE Symposium on Medical Imaging (SPIE-MI 2008). SPIE, San Diego (2008)
Toujilov, I., Taylor, P.: Developing the GIMI Mammography Ontology in OWL 2 using Protege 4, http://protege.stanford.edu/conference/2009/abstracts/D6-Taylor.pdf
GIMI Mammography Ontology, http://sourceforge.net/projects/gimimammography
Ceusters, W., Smith, B., Goldberg, L.: A terminological and ontological analysis of the NCI Thesaurus. Methods of Information in Medicine (2005)
Tabar, L., Tot, T., Dean, P.: Breast Cancer - The Art and Science of Early Detection with Mammography. Georg Thieme Verlag, Stuttgart (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Taylor, P., Toujilov, I. (2012). Mammographic Knowledge Representation in Description Logic. In: Riaño, D., ten Teije, A., Miksch, S. (eds) Knowledge Representation for Health-Care. KR4HC 2011. Lecture Notes in Computer Science(), vol 6924. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27697-2_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-27697-2_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27696-5
Online ISBN: 978-3-642-27697-2
eBook Packages: Computer ScienceComputer Science (R0)