Abstract
The paper deals with the integrated use of Information Visualization techniques and clustering algorithms to analyze Magnetic Resonance Imaging (MRI) data sets. The paper also describes the criteria we followed in designing and implementing the prototype, according to the above approach. Finally, some preliminary results are given for the considered medical application.
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References
Bemmel, J., Musen, M.A.: Handbook of medical informatic. Springer, Heidelberg (2002)
Card, S.K., Mackinglay, J.D., Shneiderman, B.: Readings in Information Visualization - Using Vision to Think. Morgan Kaufmann, San Francisco (1999)
Marzola, P., Degrassi, A., Calderan, L., Farace, P., Crescimanno, C., Nicolato, E., Giusti, A., Pesenti, E., Terron, A., Sbarbati, A., Abrams, T., Murray, L., Osculati, F.: In vivo assessment of antiangiogenic activity of su6668 in an experimental colon carcinoma model. Clin. Cancer Res. 2(10), 739–750 (2004)
Pelleg, D., Moore, A.: X-means: Extending K-means with efficient estimation of the number of clusters. In: Proc. 17th International Conf. on Machine Learning, pp. 727–734. Morgan Kaufmann, San Francisco (2000)
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Castellani, U., Combi, C., Marzola, P., Murino, V., Sbarbati, A., Zampieri, M. (2005). Towards Information Visualization and Clustering Techniques for MRI Data Sets. In: Miksch, S., Hunter, J., Keravnou, E.T. (eds) Artificial Intelligence in Medicine. AIME 2005. Lecture Notes in Computer Science(), vol 3581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527770_44
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DOI: https://doi.org/10.1007/11527770_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27831-3
Online ISBN: 978-3-540-31884-2
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