Camilla Scapicchio

According to our database, Camilla Scapicchio authored at least 10 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Optimized U-Net Convolutional Autoencoder for Low-Dose CT Denoising: Technical Improvements and Clinical Validation.

Simone Damiani, Patrizio Barca, Marco Giannelli, Francesca Lizzi, Emanuele Neri, Alessandra Retico, Chiara Romei, Camilla Scapicchio, Maria Irene Tenerani, Antonio Traino, Arman Zafaranchi, Maria Evelina Fantacci

Proceedings of the 19th International Joint Conference on Biomedical Engineering Systems and Technologies, 2026

2025

Generative super-resolution AI accelerates nanoscale analysis of cells.

Simone Lossano, Simone Capaccioli, Francesca Cella Zanacchi, Eleonora Da Pozzo, Francesca Del Debbio, Maria Evelina Fantacci, Francesca Lizzi, Raffaella Magrassi, Benedetta Noferi, Dario Pisignano, Camilla Scapicchio, Alessandra Retico

Mach. Learn. Sci. Technol., 2025

Human-AI Framework to Investigate New Promising Oncological Radiotherapy Techniques.

Camilla Scapicchio, Silvia Arezzini, Antonino Formuso, Simone Lossano, Enrico Mazzoni, Alessandra Retico

Proceedings of the 4th International Conference on Hybrid Human-Artificial Intelligence, 2025

2.5D Deep Learning Model with Attention Mechanism for Pancreas Segmentation on CT Scans.

Idriss Cabrel Tsewalo Tondji, Francesca Lizzi, Camilla Scapicchio, Alessandra Retico

Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies, 2025

Use of Radiomics in Low Dose Chest CT: A Proposal for a Phantom Multi-Centric Study.

Maria Irene Tenerani, Silvia Arezzini, Antonino Formuso, Francesca Lizzi, Enrico Mazzoni, Stefania Pallotta, Alessandra Retico, Camilla Scapicchio, Cinzia Talamonti, Maria Evelina Fantacci

Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies, 2025

Deep Learning Denoising of Low-Dose Computed Tomography Using Convolutional Autoencoder: A Phantom Study.

Simone Damiani, Manuela Imbriani, Francesca Lizzi, Mariagrazia Quattrocchi, Alessandra Retico, Sara Saponaro, Camilla Scapicchio, Alessandro Tofani, Arman Zafaranchi, Maria Irene Tenerani, Maria Evelina Fantacci

Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies, 2025

2024

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

Proceedings of the Bioinformatics and Biomedical Engineering, 2024

Explainability Applied to a Deep-Learning Based Algorithm for Lung Nodule Segmentation.

Arman Zafaranchi, Francesca Lizzi, Alessandra Retico, Camilla Scapicchio, Maria Evelina Fantacci

Proceedings of the 1st International Conference on Explainable AI for Neural and Symbolic Methods, 2024

Integration and Optimization of XNAT-Based Platforms for the Management of Heterogeneous and Multicenter Data in Biomedical Research.

Camilla Scapicchio, Silvia Arezzini, Maria Evelina Fantacci, Antonino Formuso, Aafke Christine Kraan, Enrico Mazzoni, Sara Saponaro, Maria Irene Tenerani, Alessandra Retico

Proceedings of the 13th International Conference on Data Science, 2024

2023

Integration of a Deep Learning-Based Module for the Quantification of Imaging Features into the Filling-in Process of the Radiological Structured Report.

Camilla Scapicchio, Elena Ballante, Francesca Brero, Raffaella Fiamma Cabini, Andrea Chincarini, Maria Evelina Fantacci, Silvia Figini, Alessandro Lascialfari, Francesca Lizzi, Ian Postuma, Alessandra Retico

Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, 2023