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New Insights in Brain Tumor Magnetic Resonance Investigation

  • Remy Guillevin
Chapter
Part of the Contemporary Clinical Neuroscience book series (CCNE)

Abstract

Today MR sequence development generates a dramatic increase of parameters, thus providing informations which requires specific mathematic tools to extract and post-process them. Concomitantly, a huge increase of knowledge in the biometabolic and genomic fields generates new heuristic and therapeutic ways especially in neuro-oncology. Then, imaging data should be integrated in new conceptual approaches based on powerful mathematic tools as graph theory, machine learning, and low-fast systems. This chapter will focus on those new challenges of brain tumor imaging.

Keywords

MRI Multinuclear spectroscopy Perfusion Brain tumors Machine learning Radiomics Biometabolic modeling rsfMRI Graph theory 

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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Clinical Neuroimaging & Research team DACTIM-MIS/LMA CNRS 7348, CHU and University of PoitiersPoitiersFrance

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