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Conference Papers Year : 2015

Tumor classification and prediction using robust multivariate clustering of multiparametric MRI

Abstract

In neuro-oncology, the use of multiparametric MRI may better characterize brain tumor heterogeneity. To fully exploit multiparametric MRI (e.g. tumor classification), appropriate analysis methods are yet to be developed. In this work, we show on small animals data that advanced statistical learning approaches can help 1) in organizing existing data by detecting and excluding outliers and 2) in building a dictionary of tumor fingerprints from a clustering analysis of their microvascular features.
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Dates and versions

hal-01253584 , version 1 (11-01-2016)

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  • HAL Id : hal-01253584 , version 1

Cite

Alexis Arnaud, Florence Forbes, Benjamin Lemasson, Emmanuel Luc Barbier. Tumor classification and prediction using robust multivariate clustering of multiparametric MRI. International Society for Magnetic Resonance in Medicine, May 2015, Toronto, Canada. ⟨hal-01253584⟩
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