Archivio Istituzionale della RicercaPANIC, JOVANA
PANIC, JOVANA
Dipartimento di Ingegneria Meccanica e Aerospaziale
052011
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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.
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.
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
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 different classifiers to recognize active bone marrow from CT images
2020 Rosati, S.; Franco, P.; Fiandra, C.; Arcadipane, F.; Silvetti, P.; Gallio, E.; Panic, J.; Ricardi, U.; Balestra, G.
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.
| 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 |
| 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 |
| 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 |
| 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 different classifiers to recognize active bone marrow from CT images / Rosati, S.; Franco, P.; Fiandra, C.; Arcadipane, F.; Silvetti, P.; Gallio, E.; Panic, J.; Ricardi, U.; 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/MeMeA49120.2020.9137173]. | 1-gen-2020 | Rosati S.Panic J.Balestra G. + | bone marrow classifiers final.pdf; 09137173.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 |