Temi di Ricerca

 

Tecniche di imaging non invasive: Positron Emission Tomography (PET), Computerized  Tomography (CT) and Magnetic Resonance (MR)

Big data, Radiomica e Intelligenza Artificiale in Ambito Clinico

Processing, quantificazione e correzione di immagini medicali in-vivo ed ex-vivo

 

CV

 

Collaborazioni Nazionali

 

Dipartimento di Medicina Nucleare, Ospedale Giglio, Cefalù

Dipartimento di Medicina Nucleare, Ospedale Cannizzaro, Catania

Dipartimento di Medicina Nucleare, Policlinico di Messina, Messina

Dipartimento di Radiologia, Policlinico di Palermo, Palermo

Dipartimento di Radiologia, Policlinico di Catania, Catania

Fondazione Ri.MED, Palermo

 

Collaborazioni Internazionali

 

Prof. Anthony Yezzi, Laboratory of Computational Computer Vision (LCCV), School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA

Dr. Samuel Bignardi, Laboratory of Computational Computer Vision (LCCV), School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA

 

Bibliografia recente di maggior rilevanza 

 

• • Comelli A, Stefano A, Coronnello C, Russo G, Vernuccio F, Cannella R, Selvaggio G, Lagalla R, and Barone S. Radiomics: a New Biomedical Workflow to Create a Predictive Model. Communications in Computer and Information Science. Springer, Cham, 2020. In press.
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  • Stefano A, Comelli A, Bravata V, Barone S, Daskalovski I, Savoca G, et al. A preliminary PET radiomics study of brain metastases using a fully automatic segmentation method. BMC Bioinformatics, 2020. In press.
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  • Stefano A, Gioè M, Russo G, Palmucci S, Torrisi SE, Bignardi S, et al. Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT. Diagnostics 2020, Vol 10, Page 306 2020;10:306. https://doi.org/10.3390/DIAGNOSTICS10050306.
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  • Comelli A, Stefano A*, Russo G, Bignardi S, Sabini MG, Petrucci G, et al. K-nearest neighbor driving active contours to delineate biological tumor volumes. Eng Appl Artif Intell 2019;81:133–44. https://doi.org/10.1016/j.engappai.2019.02.005.
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  • Comelli A, Stefano A*, Bignardi S, Russo G, Sabini MG, Ippolito M, et al. Active contour algorithm with discriminant analysis for delineating tumors in positron emission tomography. Artif Intell Med 2019;94:67–78 https://doi.org/10.1016/j.artmed.2019.01.002.
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  • Comelli A, Stefano A*, Russo G, Sabini MG, Ippolito M, Bignardi S, et al. A smart and operator independent system to delineate tumours in Positron Emission Tomography scans. Comput Biol Med 2018;102:1–15. https://doi.org/10.1016/j.compbiomed.2018.09.002.
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  • Raccagni I, Belloli S, Valtorta S, Stefano A, Presotto L, Pascali C, et al. [18F]FDG and [18F]FLT PET for the evaluation of response to neo-adjuvant chemotherapy in a model of triple negative breast cancer. PLoS One 2018;13. https://doi.org/10.1371/journal.pone.0197754.
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  • D`Urso D, Stefano A^#, Romano A, Russo G, Cosentino S, Fallanca F, et al. Analysis of Metabolic Parameters Coming from Basal and Interim PET in Hodgkin Lymphoma. Curr Med Imaging Rev 2017;14:533–44. https://doi.org/10.2174/1573405613666170331110119.
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  • Rundo L, Stefano A, Militello C, Russo G, Sabini MG, D’Arrigo C, et al. A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning. Comput Methods Programs Biomed 2017;144:77–96. https://doi.org/10.1016/j.cmpb.2017.03.011.
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  • Gallivanone F, Stefano A, Grosso E, Canevari C, Gianolli L, Messa C, et al. PVE correction in PET-CT whole-body oncological studies from PVE-affected images. IEEE Trans Nucl Sci 2011;58:736–47.