Skip to Main content Skip to Navigation
New interface
Poster communications

Monitoring brain tumor evolution using multiparametric MRI

Benjamin Lemasson 1 Nora Collomb 2 Alexis Arnaud 3 Florence Forbes 3 Emmanuel L. Barbier 4 
2 INSERM U836, équipe 1, Physiopathologie du cytosquelette
GIN - Grenoble Institut des Neurosciences
3 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann
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.
Document type :
Poster communications
Complete list of metadata

Cited literature [5 references]  Display  Hide  Download
Contributor : Florence Forbes Connect in order to contact the contributor
Submitted on : Wednesday, November 29, 2017 - 6:38:40 PM
Last modification on : Friday, February 4, 2022 - 3:22:53 AM


Files produced by the author(s)


  • HAL Id : hal-01652026, version 1



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



Record views


Files downloads