Archivio Istituzionale della RicercaGIANNINI, 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.
Development and validation of an AI-based pathomics biomarker to predict response to first-line treatment in metastatic colorectal cancers
2024 Nicoletti, G.; Cafaro, D.; Giannini, V.; Mauri, G.; Marchio, C.; Lazzari, L.; Sartore-Bianchi, A.; Marmorino, F.; Munoz, M. N.; Gonzalez, N. S.; Puccini, A.; Di Como, M.; Aquilano, M. C.; Bonoldi, E.; Siena, S.; Marsoni, 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.
How Do Norms and Noise Impact Clustering Results? A Robustness Analysis Applied to Digital Pathology
2023 Nicoletti, Giulia; Marchiò, Caterina; Rosati, Samanta; Berrino, Enrico; Aquilano, Maria Costanza; Bonoldi, Emanuela; Balestra, Gabriella; Regge, Daniele; Giannini, Valentina
A Deep Learning model to segment liver metastases on CT images acquired at different time-points during chemotherapy
2022 Defeudis, Arianna; Panic, Jovana; Guzzinati, Walter; Pusceddu, Laura; Vassallo, Lorenzo; Regge, Daniele; Giannini, Valentina
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
Impact of network parameters on a U-Net based system for rectal cancer segmentation on MR images
2022 Panic, Jovana; Giannini, Valentina; Defeudis, Arianna; Regge, Daniele; Balestra, Gabriella; Rosati, Samanta
Comparison of radiomics approaches to predict resistance to 1st line chemotherapy in liver metastatic colorectal cancer
2021 Defeudis, A; Cefaloni, L; Giannetto, G; Cappello, G; Rizzetto, F; Panic, J; Barra, D; Nicoletti, G; Mazzetti, S; Vanzulli, A; Regge, D; Giannini, V
Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil
2021 Barra, D; Nicoletti, G; Defeudis, A; Mazzetti, S; Panic, J; Gatti, M; Faletti, R; Russo, F; Regge, D; Giannini, V
Virtual biopsy in prostate cancer: can machine learning distinguish low and high aggressive tumors on MRI?
2021 Nicoletti, Giulia; Barra, Davide; Defeudis, Arianna; Mazzetti, Simone; Gatti, Marco; Faletti, Riccardo; Russo, Filippo; Regge, Daniele; Giannini, Valentina
A Convolutional Neural Network based system for Colorectal cancer segmentation on MRI images
2020 Panic, Jovana; Defeudis, Arianna; Mazzetti, Simone; Rosati, Samanta; Giannetto, Giuliana; Vassallo, Lorenzo; Regge, Daniele; Balestra, Gabriella; Giannini, Valentina
An innovative radiomics approach to predict response to chemotherapy of liver metastases based on CT images
2020 Giannini, Valentina; Defeudis, Arianna; Rosati, Samanta; Cappello, Giovanni; Mazzetti, Simone; Panic, Jovana; Regge, Daniele; Balestra, Gabriella
Comparison of Histogram-based Textural Features between Cancerous and Normal Prostatic Tissue in Multiparametric Magnetic Resonance Images
2020 De Santi, B.; Salvi, M.; Giannini, V.; Meiburger, K. M.; Marzola, F.; Russo, F.; Bosco, M.; Molinari, F.
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.
Multimodal T2w and DWI Prostate Gland Automated Registration
2019 De Santi, B.; Salvi, M.; Giannini, V.; Meiburger, K. M.; Michielli, N.; Seoni, S.; Regge, D.; Molinari, F.
Correlation based Feature Selection impact on the classification of breast cancer patients response to neoadjuvant chemotherapy
2018 Rosati, S.; Gianfreda, C. M.; Balestra, G.; Martincich, L.; Giannini, V.; Regge, D.
Radiomics for pretreatment prediction of pathological response to neoadjuvant therapy using magnetic resonance imaging: Influence of feature selection
2018 Giannini, Valentina; Rosati, Samanta; Castagneri, Cristina; Martincich, Laura; Regge, Daniele; Balestra, Gabriella
Radiomics to predict response to neoadjuvant chemotherapy in rectal cancer: influence of simultaneous feature selection and classifier optimization
2018 Rosati, S; Gianfreda, Cm; Balestra, G; Giannini, V; Mazzetti, S; Regge, D
Dataset homogeneity assessment for a prostate cancer CAD system
2016 Rosati, Samanta; Giannini, Valentina; Castagneri, Cristina; Regge, D.; Balestra, Gabriella
Texture Features and Artificial Neural Networks: A Way to Improve the Specificity of a CAD System for Multiparametric MR Prostate Cancer
2016 Giannini, Valentina; Rosati, Samanta; Regge, Daniele; Balestra, Gabriella
| Citazione | Data di pubblicazione | Autori | File |
|---|---|---|---|
| A Fully Automatic Multi-Vendor AI-System To Segment And Predict Resistance To Treatment Of Rectal Cancer On MRI / 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.. - ELETTRONICO. - (2024). (Intervento presentato al convegno 10th World Congress on New Technologies, NewTech 2024 tenutosi a Barcelona (Spa) nel August 25-27, 2024) [10.11159/icbb24.120]. | 1-gen-2024 | Panic J.Rosati S.Balestra G.Giannini V. + | 2024_World Congress on New Technologies_A Fully Automatic Multi-Vendor AI-System To Segment And Predict Resistance To Treatment Of Rectal Cancer On MRI.pdf |
| Development and validation of an AI-based pathomics biomarker to predict response to first-line treatment in metastatic colorectal cancers / Nicoletti, G.; Cafaro, D.; Giannini, V.; Mauri, G.; Marchio, C.; Lazzari, L.; Sartore-Bianchi, A.; Marmorino, F.; Munoz, M. N.; Gonzalez, N. S.; Puccini, A.; Di Como, M.; Aquilano, M. C.; Bonoldi, E.; Siena, S.; Marsoni, S.; Regge, D.. - (2024). (Intervento presentato al convegno 10th International Conference on Bioengineering and Biotechnology (ICBB 2024) tenutosi a Barcelona (Spa) nel August 25-27 2024) [10.11159/icbb24.122]. | 1-gen-2024 | Nicoletti G.Giannini V. + | nicoletti_ICBB2024.pdf |
| Comparison between different approaches for the creation of the training set: how clustering and dimensionality impact the performance of a Deep Learning model / Panic, J.; Defeudis, A.; Regge, D.; Balestra, G.; Rosati, S.; Giannini, V.. - (2023), pp. 393-396. (Intervento presentato al convegno 23rd IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2023 tenutosi a Dayton (USA) nel 04-06 December 2023) [10.1109/BIBE60311.2023.00070]. | 1-gen-2023 | Panic J.Balestra G.Rosati S.Giannini V. + | 2023_BIBE_Comparison_between_Different_Approaches_for_the_Creation_of_the_Training_Set_How_Clustering_and_Dimensionality_Impact_the_Performance_of_a_Deep_Learnin.pdf |
| How Do Norms and Noise Impact Clustering Results? A Robustness Analysis Applied to Digital Pathology / Nicoletti, Giulia; Marchiò, Caterina; Rosati, Samanta; Berrino, Enrico; Aquilano, Maria Costanza; Bonoldi, Emanuela; Balestra, Gabriella; Regge, Daniele; Giannini, Valentina. - (2023), pp. 333-337. (Intervento presentato al convegno 23rd IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2023 tenutosi a Dayton (USA) nel 04-06 December 2023) [10.1109/bibe60311.2023.00061]. | 1-gen-2023 | Nicoletti, GiuliaRosati, SamantaBalestra, GabriellaGiannini, Valentina + | 2023_BIBE_How_Do_Norms_and_Noise_Impact_Clustering_Results_A_Robustness_Analysis_Applied_to_Digital_Pathology.pdf |
| A Deep Learning model to segment liver metastases on CT images acquired at different time-points during chemotherapy / Defeudis, Arianna; Panic, Jovana; Guzzinati, Walter; Pusceddu, Laura; Vassallo, Lorenzo; Regge, Daniele; Giannini, Valentina. - ELETTRONICO. - (2022), pp. 1-5. (Intervento presentato al convegno 17th IEEE International Symposium on Medical Measurements and Applications (IEEE MeMeA 2022) tenutosi a Giardini Naxos - Taormina, Messina (Italy) nel 22 June - 24 June 2022) [10.1109/MeMeA54994.2022.9856589]. | 1-gen-2022 | Jovana PanicValentina Giannini + | A_Deep_Learning_model_to_segment_liver_metastases_on_CT_images_acquired_at_different_time-points_during_chemotherapy.pdf; ManuscriptFinal.pdf |
| A fully automatic deep learning algorithm to segment Rectal Cancer on MR images: a multi-center study / Panic, Jovana; Defeudis, Arianna; Mazzetti, Simone; Rosati, Samanta; Giannetto, Giuliana; Micilotta, Monica; Vassallo, Lorenzo; Gatti, Marco; Regge, Daniele; Balestra, Gabriella; Giannini, Valentina. - ELETTRONICO. - (2022), pp. 5066-5069. (Intervento presentato al convegno 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'22) tenutosi a Glasgow, United Kingdom nel 11-15 July, 2022) [10.1109/EMBC48229.2022.9871326]. | 1-gen-2022 | Jovana PanicSamanta RosatiGabriella BalestraValentina Giannini + | Manusctipt_DEF_2022_FINAL.pdf; A_fully_automatic_deep_learning_algorithm_to_segment_rectal_Cancer_on_MR_images_a_multi-center_study.pdf |
| Impact of network parameters on a U-Net based system for rectal cancer segmentation on MR images / Panic, Jovana; Giannini, Valentina; Defeudis, Arianna; Regge, Daniele; Balestra, Gabriella; Rosati, Samanta. - ELETTRONICO. - (2022), pp. 1-6. (Intervento presentato al convegno 2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA) tenutosi a Giardini Naxos - Taormina, Italy nel 22-24 June, 2022) [10.1109/MeMeA54994.2022.9856529]. | 1-gen-2022 | Jovana PanicValentina GianniniGabriella BalestraSamanta Rosati + | FinalManuscript.pdf; Rosati-Impact.pdf |
| Comparison of radiomics approaches to predict resistance to 1st line chemotherapy in liver metastatic colorectal cancer / Defeudis, A; Cefaloni, L; Giannetto, G; Cappello, G; Rizzetto, F; Panic, J; Barra, D; Nicoletti, G; Mazzetti, S; Vanzulli, A; Regge, D; Giannini, V. - ELETTRONICO. - 2021:(2021), pp. 3305-3308. (Intervento presentato al convegno 2021 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) tenutosi a Mexico nel 1-5 Nov. 2021) [10.1109/embc46164.2021.9630316]. | 1-gen-2021 | Panic JNicoletti GGiannini V + | Defeudis_EMBC21.pdf; Comparison_of_radiomics_approaches_to_predict_resistance_to_1st_line_chemotherapy_in_liver_metastatic_colorectal_cancer.pdf |
| Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil / Barra, D; Nicoletti, G; Defeudis, A; Mazzetti, S; Panic, J; Gatti, M; Faletti, R; Russo, F; Regge, D; Giannini, V. - ELETTRONICO. - 2021:(2021), pp. 3370-3373. (Intervento presentato al convegno 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) tenutosi a Mexico nel 1-5 Nov. 2021) [10.1109/embc46164.2021.9630792]. | 1-gen-2021 | Nicoletti GPanic JGiannini V + | Deep_learning_model_for_automatic_prostate_segmentation_on_bicentric_T2w_images_with_and_without_endorectal_coil.pdf; Barra_EMBC2021.pdf |
| Virtual biopsy in prostate cancer: can machine learning distinguish low and high aggressive tumors on MRI? / Nicoletti, Giulia; Barra, Davide; Defeudis, Arianna; Mazzetti, Simone; Gatti, Marco; Faletti, Riccardo; Russo, Filippo; Regge, Daniele; Giannini, Valentina. - ELETTRONICO. - 2021:(2021), pp. 3374-3377. (Intervento presentato al convegno 2021 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) tenutosi a Mexico nel 1-5 Nov. 2021) [10.1109/EMBC46164.2021.9630988]. | 1-gen-2021 | Nicoletti, GiuliaGiannini, Valentina + | Nicoletti_EMBC2021.pdf; Virtual_biopsy_in_prostate_cancer_can_machine_learning_distinguish_low_and_high_aggressive_tumors_on_MRI.pdf |
| A Convolutional Neural Network based system for Colorectal cancer segmentation on MRI images / Panic, Jovana; Defeudis, Arianna; Mazzetti, Simone; Rosati, Samanta; Giannetto, Giuliana; Vassallo, Lorenzo; Regge, Daniele; Balestra, Gabriella; Giannini, Valentina. - ELETTRONICO. - (2020), pp. 1675-1678. (Intervento presentato al convegno 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) tenutosi a Montreal, QC, Canada nel 20-24 July 2020) [10.1109/EMBC44109.2020.9175804]. | 1-gen-2020 | Panic, JovanaRosati, SamantaBalestra, GabriellaGiannini, Valentina + | Panic_EMBC2020.pdf; 09175804.pdf |
| An innovative radiomics approach to predict response to chemotherapy of liver metastases based on CT images / Giannini, Valentina; Defeudis, Arianna; Rosati, Samanta; Cappello, Giovanni; Mazzetti, Simone; Panic, Jovana; Regge, Daniele; Balestra, Gabriella. - ELETTRONICO. - (2020), pp. 1339-1342. (Intervento presentato al convegno 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) tenutosi a Montreal, QC, Canada nel 20-24 July 2020) [10.1109/EMBC44109.2020.9176627]. | 1-gen-2020 | Giannini, ValentinaRosati, SamantaPanic, JovanaBalestra, Gabriella + | Giannini_EMBC2020_final.pdf; 09176627.pdf |
| Comparison of Histogram-based Textural Features between Cancerous and Normal Prostatic Tissue in Multiparametric Magnetic Resonance Images / De Santi, B.; Salvi, M.; Giannini, V.; Meiburger, K. M.; Marzola, F.; Russo, F.; Bosco, M.; Molinari, F.. - 2020-:(2020), pp. 1671-1674. (Intervento presentato al convegno 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 tenutosi a can nel 2020) [10.1109/EMBC44109.2020.9176307]. | 1-gen-2020 | De Santi B.Salvi M.Giannini V.Meiburger K. M.Marzola F.Bosco M.Molinari F. + | 2020_EMBC_MRItexture.pdf; MRItexture.pdf |
| Deep learning to segment liver metastases on CT images: Impact on a radiomics method to predict response to chemotherapy / Giannini, V.; Defeudis, A.; Rosati, S.; Cappello, G.; Vassallo, L.; Mazzetti, S.; Panic, J.; Regge, D.; Balestra, G.. - ELETTRONICO. - (2020), pp. 1-5. (Intervento presentato al convegno 15th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2020 tenutosi a Bari (Italy) nel 1 June-1 July 2020) [10.1109/MeMeA49120.2020.9137150]. | 1-gen-2020 | Giannini V.Rosati S.Panic J.Balestra G. + | Giannini_Memea2020_final.pdf; 09137150.pdf |
| Multimodal T2w and DWI Prostate Gland Automated Registration / De Santi, B.; Salvi, M.; Giannini, V.; Meiburger, K. M.; Michielli, N.; Seoni, S.; Regge, D.; Molinari, F.. - ELETTRONICO. - 2019:(2019), pp. 4427-4430. (Intervento presentato al convegno 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 tenutosi a deu nel 2019) [10.1109/EMBC.2019.8856467]. | 1-gen-2019 | De Santi B.Salvi M.Giannini V.Meiburger K. M.Michielli N.Seoni S.Molinari F. + | 08856467.pdf; EMBC_reg.pdf |
| Correlation based Feature Selection impact on the classification of breast cancer patients response to neoadjuvant chemotherapy / Rosati, S.; Gianfreda, C. M.; Balestra, G.; Martincich, L.; Giannini, V.; Regge, D.. - ELETTRONICO. - (2018), pp. 1-5. (Intervento presentato al convegno MeMeA 2018 tenutosi a Rome (Italy) nel 11-13 June 2018) [10.1109/MeMeA.2018.8438698]. | 1-gen-2018 | Rosati, S.Balestra, G.Giannini, V. + | - |
| Radiomics for pretreatment prediction of pathological response to neoadjuvant therapy using magnetic resonance imaging: Influence of feature selection / Giannini, Valentina; Rosati, Samanta; Castagneri, Cristina; Martincich, Laura; Regge, Daniele; Balestra, Gabriella. - ELETTRONICO. - 2018-April:(2018), pp. 285-288. (Intervento presentato al convegno 15th IEEE International Symposium on Biomedical Imaging, ISBI 2018 tenutosi a Washington (USA) nel 2018) [10.1109/ISBI.2018.8363575]. | 1-gen-2018 | Giannini, ValentinaRosati, SamantaCastagneri, CristinaBalestra, Gabriella + | - |
| Radiomics to predict response to neoadjuvant chemotherapy in rectal cancer: influence of simultaneous feature selection and classifier optimization / Rosati, S; Gianfreda, Cm; Balestra, G; Giannini, V; Mazzetti, S; Regge, D. - ELETTRONICO. - (2018), pp. 65-68. (Intervento presentato al convegno 2018 IEEE Life Sciences Conference (LSC) tenutosi a Montreal, QC, Canada nel 28-30 Oct. 2018) [10.1109/LSC.2018.8572194]. | 1-gen-2018 | Rosati, SBalestra, GGiannini, V + | Retto_DEF.pdf |
| Dataset homogeneity assessment for a prostate cancer CAD system / Rosati, Samanta; Giannini, Valentina; Castagneri, Cristina; Regge, D.; Balestra, Gabriella. - ELETTRONICO. - (2016), pp. 1-7. (Intervento presentato al convegno 11th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016 tenutosi a Benevento (IT) nel 15-18 May 2016) [10.1109/MeMeA.2016.7533734]. | 1-gen-2016 | ROSATI, SAMANTAGIANNINI, VALENTINACASTAGNERI, CRISTINABALESTRA, GABRIELLA + | - |
| Texture Features and Artificial Neural Networks: A Way to Improve the Specificity of a CAD System for Multiparametric MR Prostate Cancer / Giannini, Valentina; Rosati, Samanta; Regge, Daniele; Balestra, Gabriella. - ELETTRONICO. - 57:(2016), pp. 296-301. (Intervento presentato al convegno MEDICON 2016 tenutosi a Paphos, Cyprus nel March 31st–April 2nd 2016) [10.1007/978-3-319-32703-7_59]. | 1-gen-2016 | GIANNINI, VALENTINAROSATI, SAMANTABALESTRA, GABRIELLA + | - |