Abstract
In this paper, we describe a radiology web system with an image analysis tool associated in order to measure bone density in fracture zones. These measures can be used to track the evolution of fractures in hip, knee, spine and long bones. It is being incorporated into the application a module that enables data mining. This module will induce a model for predicting the length of medical casualties based on patients’ data.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Berry, E.: A practical approach to Medical Image Processing. Series in Medical Physics and Biomedical Engineering, pp. 111–174. Taylor & Francis, Abington (2008)
Image Processing and Analysis in Java, http://rsbweb.nih.gov/ij/
Biomedical Imaging Group, http://bigwww.epfl.ch/thevenaz/turboreg/
Quinlan, J.R.: Programs for Machine Learning. Morgan Kaufmann Publishers, San Francisco (1993)
Cortés, C., Vapnik, V.: Support Vector Networks. Machine Learning 20, 237–297 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Álvarez, B.R.C., Nistal, Á.M., Jiménez, J.P., Tamargo, M.A.G., García, A.S.A., Aparicio, J.P. (2009). Web Application and Image Analysis Tool to Measure and Monitoring the Density in Bone Fractures with a Predictive Approach. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_108
Download citation
DOI: https://doi.org/10.1007/978-3-642-02481-8_108
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02480-1
Online ISBN: 978-3-642-02481-8
eBook Packages: Computer ScienceComputer Science (R0)