DEFEUDIS, ARIANNA
DEFEUDIS, ARIANNA
SCIENZE CHIRURGICHE
A Convolutional Neural Network based system for Colorectal cancer segmentation on MRI images
2020-01-01 Panic J.; Defeudis A.; Mazzetti S.; Rosati S.; Giannetto G.; Vassallo L.; Regge D.; Balestra G.; Giannini V.
A Deep Learning model to segment liver metastases on CT images acquired at different time-points during chemotherapy
2022-01-01 Defeudis A.; Panic J.; Guzzinati W.; Pusceddu L.; Vassallo L.; Regge D.; Giannini V.
A Fully Automatic Artificial Intelligence System Able to Detect and Characterize Prostate Cancer Using Multiparametric MRI: Multicenter and Multi-Scanner Validation
2021-01-01 Giannini V.; Mazzetti S.; Defeudis A.; Stranieri G.; Calandri M.; Bollito E.; Bosco M.; Porpiglia F.; Manfredi M.; De Pascale A.; Veltri A.; Russo F.; Regge D.
A fully automatic deep learning algorithm to segment rectal Cancer on MR images: a multi-center study
2022-01-01 Panic, Jovana; Defeudis, Arianna; Mazzetti, Simone; Rosati, Samanta; Giannetto, Giuliana; Micilotta, Monica; Vassallo, Lorenzo; Gatti, Marco; Regge, Daniele; Balestra, Gabriella; Giannini, Valentina
A Fully Automatic Multi-Vendor AI-System To Segment And Predict Resistance To Treatment Of Rectal Cancer On MRI
2024-01-01 Panic J.; Defeudis A.; Vassallo L.; Cirillo S.; Gatti M.; Esposito A.; Dell'aversana S.; Siena S.; Vanzulli A.; Regge D.; Rosati S.; Balestra G.; Giannini V.
An innovative radiomics approach to predict response to chemotherapy of liver metastases based on CT images
2020-01-01 Giannini V.; Defeudis A.; Rosati S.; Cappello G.; Mazzetti S.; Panic J.; Regge D.; Balestra G.
Artificial intelligence in oncologic imaging
2023-01-01 Cappello G.; Defeudis A.; Giannini V.; Mazzetti S.; Regge D.
Comparison between different approaches for the creation of the training set: how clustering and dimensionality impact the performance of a Deep Learning model
2023-01-01 Panic J.; Defeudis A.; Regge D.; Balestra G.; Rosati S.; Giannini V.
CT texture analysis to predict response to target therapy of hepatic metastases from colorectal cancer
2019-01-01 Mazzetti, Simone; Giannini, Valentina; Vassallo, Lorenzo; Defeudis, Arianna; Vanzulli, Angelo; Golfieri, Rita; Marsoni, Silvia; Regge, Daniele
Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil
2021-01-01 Barra, Davide; Nicoletti, Giulia; Defeudis, Arianna; Mazzetti, Simone; Panic, Jovana; Gatti, Marco; Faletti, Riccardo; Russo, Filippo; Regge, Daniele; Giannini, Valentina
Deep learning to segment liver metastases on CT images: Impact on a radiomics method to predict response to chemotherapy
2020-01-01 Giannini V.; Defeudis A.; Rosati S.; Cappello G.; Vassallo L.; Mazzetti S.; Panic J.; Regge D.; Balestra G.
Development and validation of a clinical decision support system based on PSA, microRNAs, and MRI for the detection of prostate cancer
2024-01-01 Mazzetti, Simone; Defeudis, Arianna; Nicoletti, Giulia; Chiorino, Giovanna; De Luca, Stefano; Faletti, Riccardo; Gatti, Marco; Gontero, Paolo; Manfredi, Matteo; Mello-Grand, Maurizia; Peraldo-Neia, Caterina; Zitella, Andrea; Porpiglia, Francesco; Regge, Daniele; Giannini, Valentina
Exploring the complexities of radiomics: an in-depth analysis of a machine learning pipeline for predicting rectal cancer therapy response using MRI
2025-01-01 Defeudis, Arianna; Panic, Jovana; Vassallo, Lorenzo; Cirillo, Stefano; Gatti, Marco; Faletti, Riccardo; Esposito, Antonio; Palmisano, Anna; Dell'Aversana, Serena; Ragozzino, Alfonso; Siena, Salvatore; Vanzulli, Angelo; Regge, Daniele; Rosati, Samanta; Balestra, Gabriella; Giannini, Valentina
Impact of inter-reader contouring variability on textural radiomics of colorectal liver metastases
2020-01-01 Rizzetto F.; Calderoni F.; De Mattia C.; Defeudis A.; Giannini V.; Mazzetti S.; Vassallo L.; Ghezzi S.; Sartore-Bianchi A.; Marsoni S.; Siena S.; Regge D.; Torresin A.; Vanzulli A.
Impact of network parameters on a U-Net based system for rectal cancer segmentation on MR images
2022-01-01 Panic J.; Giannini V.; Defeudis A.; Regge D.; Balestra G.; Rosati S.
Liver metastases: The role of magnetic resonance imaging
2023-01-01 Maino, Cesare; Vernuccio, Federica; Cannella, Roberto; Cortese, Francesco; Franco, Paolo Niccolò; Gaetani, Clara; Giannini, Valentina; Inchingolo, Riccardo; Ippolito, Davide; Defeudis, Arianna; Pilato, Giulia; Tore, Davide; Faletti, Riccardo; Gatti, Marco
MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study
2022-01-01 Defeudis, Arianna; Mazzetti, Simone; Panic, Jovana; Micilotta, Monica; Vassallo, Lorenzo; Giannetto, Giuliana; Gatti, Marco; Faletti, Riccardo; Cirillo, Stefano; Regge, Daniele; Giannini, Valentina
Normalization strategies in multi-center radiomics abdominal MRI: systematic review and meta-analyses
2023-01-01 Panic, Jovana; Defeudis, Arianna; Balestra, Gabriella; Giannini, Valentina; Rosati, Samanta
Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice
2021-01-01 Coppola, Francesca; Giannini, Valentina; Gabelloni, Michela; Panic, Jovana; Defeudis, Arianna; Lo Monaco, Silvia; Cattabriga, Arrigo; Cocozza, Maria Adriana; Pastore, Luigi Vincenzo; Polici, Michela; Caruso, Damiano; Laghi, Andrea; Regge, Daniele; Neri, Emanuele; Golfieri, Rita; Faggioni, Lorenzo
Radiomics features on CT scans to predict response to HER2-targeted therapy of hepatic metastases from colorectal cancer
2019-01-01 Giannini, Valentina; Mazzetti, Simone; Defeudis, Arianna; Cappello, Giovanni; Vassallo, Lorenzo; Vanzulli, Angelo; De Mattia, Cristina; Torresin, Alberto; Siena, Salvatore; Sartore-Bianchi, Andrea; Leone, Francesco; Martino, Cosimo; Zagonel, Vittorina; Marsoni, Silvia; Regge, Daniele
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| A Convolutional Neural Network based system for Colorectal cancer segmentation on MRI images | 2020 | Panic J.; Defeudis A.; Mazzetti S.; Rosati S.; Giannetto G.; Vassallo L.; Regge D.; Balestra G.; Giannini V. | |
| A Deep Learning model to segment liver metastases on CT images acquired at different time-points during chemotherapy | 2022 | Defeudis A.; Panic J.; Guzzinati W.; Pusceddu L.; Vassallo L.; Regge D.; Giannini V. | |
| A Fully Automatic Artificial Intelligence System Able to Detect and Characterize Prostate Cancer Using Multiparametric MRI: Multicenter and Multi-Scanner Validation | 2021 | Giannini V.; Mazzetti S.; Defeudis A.; Stranieri G.; Calandri M.; Bollito E.; Bosco M.; Porpiglia F.; Manfredi M.; De Pascale A.; Veltri A.; Russo F.; Regge D. | |
| A fully automatic deep learning algorithm to segment rectal Cancer on MR images: a multi-center study | 2022 | Panic, Jovana; Defeudis, Arianna; Mazzetti, Simone; Rosati, Samanta; Giannetto, Giuliana; Micilotta, Monica; Vassallo, Lorenzo; Gatti, Marco; Regge, Daniele; Balestra, Gabriella; Giannini, Valentina | |
| A Fully Automatic Multi-Vendor AI-System To Segment And Predict Resistance To Treatment Of Rectal Cancer On MRI | 2024 | Panic J.; Defeudis A.; Vassallo L.; Cirillo S.; Gatti M.; Esposito A.; Dell'aversana S.; Siena S.; Vanzulli A.; Regge D.; Rosati S.; Balestra G.; Giannini V. | |
| An innovative radiomics approach to predict response to chemotherapy of liver metastases based on CT images | 2020 | Giannini V.; Defeudis A.; Rosati S.; Cappello G.; Mazzetti S.; Panic J.; Regge D.; Balestra G. | |
| Artificial intelligence in oncologic imaging | 2023 | Cappello G.; Defeudis A.; Giannini V.; Mazzetti S.; Regge D. | |
| Comparison between different approaches for the creation of the training set: how clustering and dimensionality impact the performance of a Deep Learning model | 2023 | Panic J.; Defeudis A.; Regge D.; Balestra G.; Rosati S.; Giannini V. | |
| CT texture analysis to predict response to target therapy of hepatic metastases from colorectal cancer | 2019 | Mazzetti, Simone; Giannini, Valentina; Vassallo, Lorenzo; Defeudis, Arianna; Vanzulli, Angelo; Golfieri, Rita; Marsoni, Silvia; Regge, Daniele | |
| Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil | 2021 | Barra, Davide; Nicoletti, Giulia; Defeudis, Arianna; Mazzetti, Simone; Panic, Jovana; Gatti, Marco; Faletti, Riccardo; Russo, Filippo; Regge, Daniele; Giannini, Valentina | |
| Deep learning to segment liver metastases on CT images: Impact on a radiomics method to predict response to chemotherapy | 2020 | Giannini V.; Defeudis A.; Rosati S.; Cappello G.; Vassallo L.; Mazzetti S.; Panic J.; Regge D.; Balestra G. | |
| Development and validation of a clinical decision support system based on PSA, microRNAs, and MRI for the detection of prostate cancer | 2024 | Mazzetti, Simone; Defeudis, Arianna; Nicoletti, Giulia; Chiorino, Giovanna; De Luca, Stefano; Faletti, Riccardo; Gatti, Marco; Gontero, Paolo; Manfredi, Matteo; Mello-Grand, Maurizia; Peraldo-Neia, Caterina; Zitella, Andrea; Porpiglia, Francesco; Regge, Daniele; Giannini, Valentina | |
| Exploring the complexities of radiomics: an in-depth analysis of a machine learning pipeline for predicting rectal cancer therapy response using MRI | 2025 | Defeudis, Arianna; Panic, Jovana; Vassallo, Lorenzo; Cirillo, Stefano; Gatti, Marco; Faletti, Riccardo; Esposito, Antonio; Palmisano, Anna; Dell'Aversana, Serena; Ragozzino, Alfonso; Siena, Salvatore; Vanzulli, Angelo; Regge, Daniele; Rosati, Samanta; Balestra, Gabriella; Giannini, Valentina | |
| Impact of inter-reader contouring variability on textural radiomics of colorectal liver metastases | 2020 | Rizzetto F.; Calderoni F.; De Mattia C.; Defeudis A.; Giannini V.; Mazzetti S.; Vassallo L.; Ghezzi S.; Sartore-Bianchi A.; Marsoni S.; Siena S.; Regge D.; Torresin A.; Vanzulli A. | |
| Impact of network parameters on a U-Net based system for rectal cancer segmentation on MR images | 2022 | Panic J.; Giannini V.; Defeudis A.; Regge D.; Balestra G.; Rosati S. | |
| Liver metastases: The role of magnetic resonance imaging | 2023 | Maino, Cesare; Vernuccio, Federica; Cannella, Roberto; Cortese, Francesco; Franco, Paolo Niccolò; Gaetani, Clara; Giannini, Valentina; Inchingolo, Riccardo; Ippolito, Davide; Defeudis, Arianna; Pilato, Giulia; Tore, Davide; Faletti, Riccardo; Gatti, Marco | |
| MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study | 2022 | Defeudis, Arianna; Mazzetti, Simone; Panic, Jovana; Micilotta, Monica; Vassallo, Lorenzo; Giannetto, Giuliana; Gatti, Marco; Faletti, Riccardo; Cirillo, Stefano; Regge, Daniele; Giannini, Valentina | |
| Normalization strategies in multi-center radiomics abdominal MRI: systematic review and meta-analyses | 2023 | Panic, Jovana; Defeudis, Arianna; Balestra, Gabriella; Giannini, Valentina; Rosati, Samanta | |
| Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice | 2021 | Coppola, Francesca; Giannini, Valentina; Gabelloni, Michela; Panic, Jovana; Defeudis, Arianna; Lo Monaco, Silvia; Cattabriga, Arrigo; Cocozza, Maria Adriana; Pastore, Luigi Vincenzo; Polici, Michela; Caruso, Damiano; Laghi, Andrea; Regge, Daniele; Neri, Emanuele; Golfieri, Rita; Faggioni, Lorenzo | |
| Radiomics features on CT scans to predict response to HER2-targeted therapy of hepatic metastases from colorectal cancer | 2019 | Giannini, Valentina; Mazzetti, Simone; Defeudis, Arianna; Cappello, Giovanni; Vassallo, Lorenzo; Vanzulli, Angelo; De Mattia, Cristina; Torresin, Alberto; Siena, Salvatore; Sartore-Bianchi, Andrea; Leone, Francesco; Martino, Cosimo; Zagonel, Vittorina; Marsoni, Silvia; Regge, Daniele |