Spectral Clustering predicts tumor tissue heterogeneity using dynamic 18F-FDG 
PET: a complement to the standard compartmental modeling approach

Katiyar, P.; Divine, M. R.; Kohlhofer, U.; Quintanilla-Martinez, L.; Schölkopf, B; Pichler, B. J.; Disselhorst, J. A.

doi:10.2967/jnumed.116.181370

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Spectral Clustering predicts tumor tissue heterogeneity using dynamic 18F-FDG PET: a complement to the standard compartmental modeling approach

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Katiyar, P.
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Schölkopf, B
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Katiyar, P., Divine, M. R., Kohlhofer, U., Quintanilla-Martinez, L., Schölkopf, B., Pichler, B. J., et al. (2017). Spectral Clustering predicts tumor tissue heterogeneity using dynamic 18F-FDG PET: a complement to the standard compartmental modeling approach. Journal of Nuclear Medicine, 58(4), 651-657. doi:10.2967/jnumed.116.181370.

Cite as: https://hdl.handle.net/21.11116/0000-0001-0126-3

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