Summary
New methods are presented to generate random germs regionalized by a previous classification in order to use probabilistic watershed on hyperspectral images. These germs are much more efficient than the standard uniform random germs.
This is a preview of subscription content, log in via an institution to check access.
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
Angulo, J., Jeulin, D.: Stochastic watershed segmentation. In Banon, G., et al. (eds.) Proceedings of the 8th International Symposium on Mathematical Morphology, vol. 1, pp. 265–276. Instituto Nacional de Pesquisas Espaciais (INPE), 2007
Balvay, D., Frouin, F., Calmon, G., Bessoud, B., Kahn, E., Siauve, N., Clment, O., Cuenod, C.A.: New criteria for assessing fit quality in dynamic contrast-enhanced T 1-weighted MRI for perfusion and permeability imaging. Magn. Reson. Med. 54, 868–877 (2005)
Meyer, F.: An overview of morphological segmentation. Intern. J. Pattern Recognit Artif. Intell. 15(7), 1089–1118 (2001)
Noyel, G., Angulo, J., Jeulin, D.: Morphological segmentation of hyperspectral images. Image Anal. Stereol. 26, 101–109 (2007)
Noyel, G., Angulo, J., Jeulin, D.: Random germs and stochastic watershed for unsupervised multispectral image segmentation. In: Apolloni, B., et al. (eds.) KES 2007/ WIRN 2007, volume III of LNAI 4694, pp. 17–24. Knowledge-Based Intelligent Information and Engineering Systems. Springer, Heidelberg (2007)
Noyel, G., Angulo, J., Jeulin, D.: Filtering, segmentation and region classification by hyperspectral mathematical morphology of DCE-MRI series for angiogenesis imaging. In: Proceedings of the IEEE International Symposium on Biomedical Imaging ISBI 2008, pp. 1517–1520. (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Noyel, G., Angulo, J., Jeulin, D. (2010). Regionalized Random Germs by a Classification for Probabilistic Watershed Application: Angiogenesis Imaging Segmentation. In: Fitt, A., Norbury, J., Ockendon, H., Wilson, E. (eds) Progress in Industrial Mathematics at ECMI 2008. Mathematics in Industry(), vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12110-4_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-12110-4_29
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12109-8
Online ISBN: 978-3-642-12110-4
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)