GPCALMA, a mammographic CAD in a GRID connection. - Ubaldo Bottigli; Piergiorgio Cerello; Pasquale Delogu; Maria Evelina Fantacci; Francesco Fauci; Bruno Golosio; Adele Lauria; Ernesto Lopez Torres; Rosario Magro; Giovanni Luca Masala; Piernicola Oliva; Rosa Palmiero; et al. (CARS, 2003)

Automatic Lung Segmentation in CT Images with Accurate Handling of the Hilar Region. - Giorgio De Nunzio; Eleonora Tommasi; Antonella Agrusti; Rosella Cataldo; Ivan De Mitri; Marco Favetta; Silvio Maglio; Andrea Massafra; Maurizio Quarta; Massimo Torsello; Ilaria Zecca; Roberto Bellotti; et al. (J. Digit. Imaging, 2011)

An improved Marching Cube algorithm for 3D data segmentation. - Giovanni Luca Masala; Bruno Golosio; Piernicola Oliva (Comput. Phys. Commun., 2013)

Monte Carlo simulation of X-ray imaging and spectroscopy experiments using quadric geometry and variance reduction techniques. - Bruno Golosio; Tom Schoonjans; Antonio Brunetti; Piernicola Oliva; Giovanni Luca Masala (Comput. Phys. Commun., 2014)

Processing Magnetic Resonance Image Features with One-class Support Vector Machines - Investigation of the Autism Spectrum Disorder Heterogeneity. - Ilaria Gori; Alessia Giuliano; Piernicola Oliva; Michela Tosetti; Filippo Muratori; Sara Calderoni; Alessandra Retico (BIOIMAGING, 2016)

Residual Convolutional Neural Networks to Automatically Extract Significant Breast Density Features. - Francesca Lizzi; Francesco Laruina; Piernicola Oliva; Alessandra Retico; Maria Evelina Fantacci (CAIP Workshops, 2019)

Radiomic and Dosiomic Profiling of Paediatric Medulloblastoma Tumours Treated with Intensity Modulated Radiation Therapy. - Cinzia Talamonti; Stefano Piffer; Daniela Greto; Monica Mangoni; Antonio Ciccarone; Paolo Dicarolo; Maria Evelina Fantacci; Franco Fusi; Piernicola Oliva; Letizia Palumbo; Claudio Favre; Lorenzo Livi; et al. (CAIP Workshops, 2019)

Deep-Learning Based Analyses of Mammograms to Improve the Estimation of Breast Cancer Risk. - Francesca Lizzi; Maria Evelina Fantacci; Piernicola Oliva (ERCIM News, 2019)

Dealing with confounders and outliers in classification medical studies: The Autism Spectrum Disorders case study. - Elisa Ferrari; Paolo Bosco; Sara Calderoni; Piernicola Oliva; Letizia Palumbo; Giovanna Spera; Maria Evelina Fantacci; Alessandra Retico (Artif. Intell. Medicine, 2020)

Quantification of pulmonary involvement in COVID-19 pneumonia by means of a cascade oftwo U-nets: training and assessment on multipledatasets using different annotation criteria. - Francesca Lizzi; Abramo Agosti; Francesca Brero; Raffaella Fiamma Cabini; Maria Evelina Fantacci; Silvia Figini; Alessandro Lascialfari; Francesco Laruina; Piernicola Oliva; Stefano Piffer; Ian Postuma; Lisa Rinaldi; et al. (CoRR, 2021)

Quantification of pulmonary involvement in COVID-19 pneumonia by means of a cascade of two U-nets: training and assessment on multiple datasets using different annotation criteria. - Francesca Lizzi; Abramo Agosti; Francesca Brero; Raffaella Fiamma Cabini; Maria Evelina Fantacci; Silvia Figini; Alessandro Lascialfari; Francesco Laruina; Piernicola Oliva; Stefano Piffer; Ian Postuma; Lisa Rinaldi; et al. (Int. J. Comput. Assist. Radiol. Surg., 2022)

Effect of data harmonization of multicentric dataset in ASD/TD classification. - Giacomo Serra; Francesca Mainas; Bruno Golosio; Alessandra Retico; Piernicola Oliva (Brain Informatics, 2023)

A Multi-input Deep Learning Model to Classify COVID-19 Pneumonia Severity from Imaging and Clinical Data. - Francesca Lizzi; Francesca Brero; Maria Evelina Fantacci; Alessandro Lascialfari; Gianfranco Paternò; Ian Postuma; Piernicola Oliva; Camilla Scapicchio; Alessandra Retico (IWBBIO (2), 2024)

Deep learning based joint fusion approach to exploit anatomical and functional brain information in autism spectrum disorders. - Sara Saponaro; Francesca Lizzi; Giacomo Serra; Francesca Mainas; Piernicola Oliva; Alessia Giuliano; Sara Calderoni; Alessandra Retico (Brain Informatics, 2024)