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Journal Articles
- 2024
[j3]Sara Saponaro, Francesca Lizzi, Giacomo Serra, Francesca Mainas, Piernicola Oliva, Alessia Giuliano, Sara Calderoni
, Alessandra Retico:
Deep learning based joint fusion approach to exploit anatomical and functional brain information in autism spectrum disorders. Brain Informatics 11(1): 2 (2024)- [j2]Leonardo Barzaghi, Francesca Brero, Raffaella Fiamma Cabini, Matteo Paoletti, Mauro Monforte, Francesca Lizzi, Francesco Santini, Xeni Deligianni, Niels Bergsland, Sabrina Ravaglia, Lorenzo Cavagna, Luca Diamanti, Chiara Bonizzoni, Alessandro Lascialfari, Silvia Figini, Enzo Ricci, Ian Postuma, Anna Pichiecchio:
Myo-regressor Deep Informed Neural NetwOrk (Myo-DINO) for fast MR parameters mapping in neuromuscular disorders. Comput. Methods Programs Biomed. 256: 108399 (2024) - 2022
- [j1]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, Cinzia Talamonti, Alessandra Retico:
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. Int. J. Comput. Assist. Radiol. Surg. 17(2): 229-237 (2022)
Conference and Workshop Papers
- 2024
- [c6]Francesca Lizzi, Francesca Brero, Maria Evelina Fantacci, Alessandro Lascialfari, Gianfranco Paternò, Ian Postuma, Piernicola Oliva, Camilla Scapicchio, Alessandra Retico:
A Multi-input Deep Learning Model to Classify COVID-19 Pneumonia Severity from Imaging and Clinical Data. IWBBIO (2) 2024: 237-248 - 2023
- [c5]Camilla Scapicchio, Elena Ballante, Francesca Brero, Raffaella Fiamma Cabini, Andrea Chincarini, Maria Evelina Fantacci, Silvia Figini, Alessandro Lascialfari, Francesca Lizzi, Ian Postuma, Alessandra Retico:
Integration of a Deep Learning-Based Module for the Quantification of Imaging Features into the Filling-in Process of the Radiological Structured Report. HEALTHINF 2023: 663-670 - [c4]Francesca Lizzi, Alessandra Retico, Maria Evelina Fantacci:
Deep Learning and Medical Image Analysis: Epistemology and Ethical Issues. IMPROVE 2023: 172-179 - 2021
- [c3]Francesca Lizzi, Francesca Brero, Raffaella Fiamma Cabini, Maria Evelina Fantacci, Stefano Piffer, Ian Postuma, Lisa Rinaldi, Alessandra Retico:
Making Data Big for a Deep-learning Analysis: Aggregation of Public COVID-19 Datasets of Lung Computed Tomography Scans. DATA 2021: 316-321 - 2019
- [c2]Francesca Lizzi, Stefano Atzori, Giacomo Aringhieri, Paolo Bosco, Carolina Marini, Alessandra Retico, Antonio C. Traino, Davide Caramella, Maria Evelina Fantacci:
Residual Convolutional Neural Networks for Breast Density Classification. BIOINFORMATICS 2019: 258-263 - [c1]Francesca Lizzi, Francesco Laruina, Piernicola Oliva, Alessandra Retico, Maria Evelina Fantacci:
Residual Convolutional Neural Networks to Automatically Extract Significant Breast Density Features. CAIP Workshops 2019: 28-35
Informal and Other Publications
- 2021
- [i2]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, Cinzia Talamonti, Alessandra Retico:
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. CoRR abs/2105.02566 (2021) - 2019
- [i1]Francesca Lizzi, Maria Evelina Fantacci, Piernicola Oliva:
Deep-Learning Based Analyses of Mammograms to Improve the Estimation of Breast Cancer Risk. ERCIM News 2019(118) (2019)
Coauthor Index
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last updated on 2024-10-07 21:19 CEST by the dblp team
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