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Updated: Jan 22, 2026

Guidelines and Experience Using Imaging Biomarker Explorer IBEX for Radiomics
Published on: January 8, 2018
AI-based applications in hybrid imaging: how to build smart and truly multi-parametric decision models for radiomics
Isabella Castiglioni1, Francesca Gallivanone1, Paolo Soda2
1Institute of Molecular Imaging and Physiology, National Research Council (IBFM-CNR), 20090, Segrate, MI, Italy.
Introduction:
The quantitative imaging features (radiomics) that can be obtained from the different modalities of current-generation hybrid imaging can give complementary information with regard to the tumour environment, as they measure different morphologic and functional imaging properties. These multi-parametric image descriptors can be combined with artificial intelligence applications into predictive models. It is now the time for hybrid PET/CT and PET/MRI to take the advantage offered by radiomics to assess the added clinical benefit of using multi-parametric models for the personalized diagnosis and prognosis of different disease phenotypes.
Objective:
The aim of the paper is to provide an overview of current challenges and available solutions to translate radiomics into hybrid PET-CT and PET-MRI imaging for a smart and truly multi-parametric decision model.
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