Zobrazeno 1 - 3
of 3
pro vyhledávání: '"M.C. Gilardi c"'
Autor:
P. Pisciotta a, b, c, F.P. Cammarata c, A. Stefano c, F. Romano d, V. Marchese a, F. Torrisi e, G.I. Forte c, L. Cella f, g, G.A.P. Cirrone b, G. Petringa b, M.C. Gilardi c, G. Cuttone b, G. Russo b
Publikováno v:
Physica medica (Testo stamp.) 54 (2018): 173–178. doi:10.1016/j.ejmp.2018.07.003
info:cnr-pdr/source/autori:P. Pisciotta a,b,c, F.P. Cammarata c, A. Stefano c, F. Romano d,b, V. Marchese a,c, F. Torrisi e, G.I. Forte c, L. Cella f,g, G.A.P. Cirrone b, G. Petringa b, M.C. Gilardi c, G. Cuttone b, G. Russo b,c/titolo:Monte Carlo GEANT4-based application for in vivo RBE study using small animals at LNS-INFN preclinical hadrontherapy facility/doi:10.1016%2Fj.ejmp.2018.07.003/rivista:Physica medica (Testo stamp.)/anno:2018/pagina_da:173/pagina_a:178/intervallo_pagine:173–178/volume:54
info:cnr-pdr/source/autori:P. Pisciotta a,b,c, F.P. Cammarata c, A. Stefano c, F. Romano d,b, V. Marchese a,c, F. Torrisi e, G.I. Forte c, L. Cella f,g, G.A.P. Cirrone b, G. Petringa b, M.C. Gilardi c, G. Cuttone b, G. Russo b,c/titolo:Monte Carlo GEANT4-based application for in vivo RBE study using small animals at LNS-INFN preclinical hadrontherapy facility/doi:10.1016%2Fj.ejmp.2018.07.003/rivista:Physica medica (Testo stamp.)/anno:2018/pagina_da:173/pagina_a:178/intervallo_pagine:173–178/volume:54
Preclinical studies represent an important step towards a deep understanding of the biological response to ionizing radiations. The effectiveness of proton therapy is higher than photons and, for clinical purposes, a fixed value of 1.1 is used for th
Autor:
D. Lamia a, G. Russo a, C. Casarino a, L. Gagliano a, G.C. Candiano a, L. Labate b, e, F. Baffigi b, L. Fulgentini b, A. Giulietti b, P. Koester b, D. Palla b, L.A. Gizzi b, M.C. Gilardi c, d
Publikováno v:
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment (Online) 786 (2015): 113–119. doi:10.1016/j.nima.2015.03.044
info:cnr-pdr/source/autori:D. Lamia a, G. Russo a, C. Casarino a, L. Gagliano a, G.C. Candiano a, L. Labate b, e, F. Baffigi b, L. Fulgentini b, A. Giulietti b, P. Koester b, D. Palla b, L.A. Gizzi b,e, M.C. Gilardi c,d/titolo:Monte Carlo application based on GEANT4 toolkit to simulate a Laser-Plasma electron beam line for radiobiological studies/doi:10.1016%2Fj.nima.2015.03.044/rivista:Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment (Online)/anno:2015/pagina_da:113/pagina_a:119/intervallo_pagine:113–119/volume:786
info:cnr-pdr/source/autori:D. Lamia a, G. Russo a, C. Casarino a, L. Gagliano a, G.C. Candiano a, L. Labate b, e, F. Baffigi b, L. Fulgentini b, A. Giulietti b, P. Koester b, D. Palla b, L.A. Gizzi b,e, M.C. Gilardi c,d/titolo:Monte Carlo application based on GEANT4 toolkit to simulate a Laser-Plasma electron beam line for radiobiological studies/doi:10.1016%2Fj.nima.2015.03.044/rivista:Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment (Online)/anno:2015/pagina_da:113/pagina_a:119/intervallo_pagine:113–119/volume:786
We report on the development of a Monte Carlo application, based on the GEANT4 toolkit, for the characterization and optimization of electron beams for clinical applications produced by a laser-driven plasma source. The GEANT4 application is conceive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b71f12d4a43e52f1bf7e8c90c3da6a8
http://www.cnr.it/prodotto/i/328704
http://www.cnr.it/prodotto/i/328704
Autor:
C. Salvatore a, A. Cerasa b, I. Castiglioni c, F. Gallivanone c, A. Augimeri b, M. Lopez d, G. Arabia e, M. Morelli e, M.C. Gilardi c, A. Quattrone b, e
Publikováno v:
Journal of neuroscience methods 222 (2014): 237. doi:10.1016/j.jneumeth.2013.11.016
info:cnr-pdr/source/autori:C. Salvatore a, A. Cerasa b, I. Castiglioni c,*, F. Gallivanone c, A. Augimeri b, M. Lopez d, G. Arabia e, M. Morelli e, M.C. Gilardi c, A. Quattrone b,e/titolo:Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy/doi:10.1016%2Fj.jneumeth.2013.11.016/rivista:Journal of neuroscience methods/anno:2014/pagina_da:237/pagina_a:/intervallo_pagine:237/volume:222
Journal of neuroscience methods (2013). doi:10.1016/j.jneumeth.2013.11.016
info:cnr-pdr/source/autori:Salvatore C, Cerasa A, Castiglioni I, Gallivanone F, Augimeri A, Lopez M, Arabia G, Morelli M, Gilardi MC, Quattrone A/titolo:Machine Learning on Brain MRI Data for Differential Diagnosis of Parkinson's Disease and Progressive Supranuclear Palsy/doi:10.1016%2Fj.jneumeth.2013.11.016/rivista:Journal of neuroscience methods/anno:2013/pagina_da:/pagina_a:/intervallo_pagine:/volume
info:cnr-pdr/source/autori:C. Salvatore a, A. Cerasa b, I. Castiglioni c,*, F. Gallivanone c, A. Augimeri b, M. Lopez d, G. Arabia e, M. Morelli e, M.C. Gilardi c, A. Quattrone b,e/titolo:Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy/doi:10.1016%2Fj.jneumeth.2013.11.016/rivista:Journal of neuroscience methods/anno:2014/pagina_da:237/pagina_a:/intervallo_pagine:237/volume:222
Journal of neuroscience methods (2013). doi:10.1016/j.jneumeth.2013.11.016
info:cnr-pdr/source/autori:Salvatore C, Cerasa A, Castiglioni I, Gallivanone F, Augimeri A, Lopez M, Arabia G, Morelli M, Gilardi MC, Quattrone A/titolo:Machine Learning on Brain MRI Data for Differential Diagnosis of Parkinson's Disease and Progressive Supranuclear Palsy/doi:10.1016%2Fj.jneumeth.2013.11.016/rivista:Journal of neuroscience methods/anno:2013/pagina_da:/pagina_a:/intervallo_pagine:/volume
Supervised machine learning has been proposed as a revolutionary approach for identifying sensitive medical image biomarkers (or combination of them) allowing for automatic diagnosis of individual subjects. The aim of this work was to assess the feas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb9d0b5e36b75e21beee1d85523592b7
http://www.cnr.it/prodotto/i/317125
http://www.cnr.it/prodotto/i/317125