Abstract
Medical images increase in quality and quantity: More and more detailed image content can be represented on the pixel level, and increasing amounts of medical images are produced in the context of clinical diagnosis. Technological solutions are needed to enhance existing clinical IT solutions helping clinicians to access and use medical images optimally. Within Medico, we developed methods and tools (a) to parse and describe the content of medical images, (b) to extract and annotate the related information from radiology reports, and (c) to provide and manage medical ontologies as a common language for labeling and integrating the various information entities.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
C.P. Langlotz, RadLex: a new method for indexing online educational materials. RadioGraphics 26(6), 1595–1597 (2006)
H. Ling, S. Zhou, Y. Zheng, M. Georgescu, B. Suehling, D. Comaniciu, Hierarchical, learning-based automatic liver segmentation, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’08), Anchorage, June 2008 (Institute of Electrical and Electronics Engineers (IEEE), Washington DC, 2008), pp. 1–8
K. Markó, S. Schulz, U. Hahn, Morphosaurus – design and evaluation of an interlinguabased, cross-language document retrieval engine for the medical domain. Methods Inf. Med. 44(4), 537–545 (2005)
D. Marwede, P. Daumke, K. Markó, D. Lobsien, S. Schulz, T. Kahn, Radlex – German version: a radiological lexicon for indexing image and report information. RöFo – Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren 181(1), 38–44 (2009)
R.E. Schapire, Y. Singer, Improved boosting algorithms using confidence-rated predictions. Mach. Learn. 37(3), 297–336 (1999). The Eleventh Annual Conference on Computational Learning Theory
S. Seifert, A. Barbu, K. Zhou, D. Liu, J. Feulner, M. Huber, M. Suehling, A. Cavallaro, D. Comaniciu, Hierarchical parsing and semantic navigation of full body CT data, in Proceedings of SPIE Medical Imaging, Lake Buena Vista, Mar 2009, vol. 7259. The SPIE Digital Library
S. Seifert, M. Hammon, M. Petri, H. Oberkampf, P. Daumke, Intelligent healthcare applications, in Towards the Internet of Services: The THESEUS Research Program, ed. by W. Wahlster, H.J. Grallert, S. Wess, H. Friedrich, T. Widenka (Springer, Berlin/Heidelberg/New York, 2014)
Z. Tu, Probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering, in 10th IEEE International Conference on Computer Vision (ICCV ’05), Beijing, Oct 2005, vol. 2 (Institute of Electrical and Electronics Engineers (IEEE), Washington DC, 2005), pp. 1589–1596
Z. Tu, X. Zhou, A. Barbu, L. Bogoni, D. Comaniciu, Probabilistic 3D polyp detection in CT images: the role of sample alignment, in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR ’06), New York, vol. 2 (Institute of Electrical and Electronics Engineers (IEEE), Washington DC, 2006), pp. 1544–1551
Y. Zheng, A. Barbu, B. Georgescu, M. Scheuering, D. Comaniciu, Fast automatic heart chamber segmentation from 3D CT data using marginal space learning and steerable features, in IEEE 11th International Conference on Computer Vision (ICCV), Rio de Janeiro, Oct 2007 (Institute of Electrical and Electronics Engineers (IEEE), Washington DC, 2007), pp. 1–8
S. Zillner, D. Sonntag, Aligning medical ontologies by axiomatic models, corpus linguistic syntactic rules and context information, in 24th International Symposium on Computer-Based Medical Systems (CBMS), Bristol, June 2011. (Institute of Electrical and Electronics Engineers (IEEE), Washington DC, 2011), pp. 1–6
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Zillner, S., Seifert, S., Erdt, M., Daumke, P., Kramer, M. (2014). Semantic Processing of Medical Data. In: Wahlster, W., Grallert, HJ., Wess, S., Friedrich, H., Widenka, T. (eds) Towards the Internet of Services: The THESEUS Research Program. Cognitive Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-06755-1_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-06755-1_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06754-4
Online ISBN: 978-3-319-06755-1
eBook Packages: Computer ScienceComputer Science (R0)