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Semantic BigData and Deep Learning for Radiomics

DIETI Contact person / Partner: Antonio Maria Rinaldi

Abstract

The need of having advanced tools for data analysis is one of the most important trends in the current economic, technological and social scenario and, nowadays, it is mainly based on methodologies and techniques of artificial intelligence and BigData. One of the goals of modern medicine is the "precision medicine", whose purpose is to offer personalized treatments based on the specific characteristics of patients and pathologies. In this context, new analysis techniques such as Radiomics is becoming a novel research field. The analysis of the large number of data derived from medical images allows to recognize many characteristics of cancers and they can be integrated with other molecular and genomic characteristics by obtaining further correlations.

Objective

The implementation of a decision support system based on a sematic multimedia bigdata to support the analysis of medical images represented by novel radiomics descriptors and texture analysis.

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Can be assigned to one doctoral student of cycle XXXVI 

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