The aim of this project is to develop Computer Aided Diagnosis Systems that can support radiologist in the detection and characterization of breast lesions and that can provide predictive biomarkers of response to treatment.
The aim of this study is to develop an AI-based multi-omics signatures predict response to treatment
The aim of this project is to develop and validate radiomics signature to timely predict response to therapy of tumors based on radiomics and artificial intelligence.
The aim of this project is to develop new and innovative Deep Learning (DL) algorithms to automatically segment anatomical structures on radiological images. The main research branches are:
The aim of this study was to develop and validate on multivendor data a fully automated computer-aided diagnosis (CAD) system based on artificial intelligence, to automatically localize, segment, and classify PCa lesions according to their aggressiveness.