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Poster communications

Monitoring brain tumor evolution using multiparametric MRI

Benjamin Lemasson 1 Nora Collomb 2 Alexis Arnaud 3 Florence Forbes 3 Emmanuel Barbier 4
2 INSERM U836, équipe 1, Physiopathologie du cytosquelette
GIN - Grenoble Institut des Neurosciences
3 MISTIS [2016-2019] - Modelling and Inference of Complex and Structured Stochastic Systems [2016-2019]
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann , Grenoble INP [2007-2019] - Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019]
Abstract : — Analysing brain tumor tissue composition can improve the handling of tumor growth and resistance to therapies. We show on a 6 time point dataset of 8 rats that multiparametric MRI can be exploited via statistical clustering to quantify intra-lesional heterogeneity in space and time.
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Contributor : Florence Forbes <>
Submitted on : Wednesday, November 29, 2017 - 6:38:40 PM
Last modification on : Tuesday, October 6, 2020 - 12:44:47 PM


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  • HAL Id : hal-01652026, version 1



Benjamin Lemasson, Nora Collomb, Alexis Arnaud, Florence Forbes, Emmanuel Barbier. Monitoring brain tumor evolution using multiparametric MRI. 2017 IEEE International Symposium on Biomedical Imaging, Apr 2017, Melbourne, Australia. ⟨hal-01652026⟩



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