Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Piernicola Oliva"'
Autor:
Sara Saponaro, Francesca Lizzi, Giacomo Serra, Francesca Mainas, Piernicola Oliva, Alessia Giuliano, Sara Calderoni, Alessandra Retico
Publikováno v:
Brain Informatics, Vol 11, Iss 1, Pp 1-13 (2024)
Abstract Background: The integration of the information encoded in multiparametric MRI images can enhance the performance of machine-learning classifiers. In this study, we investigate whether the combination of structural and functional MRI might im
Externí odkaz:
https://doaj.org/article/95e49b4b3f694885875c848e78650032
Publikováno v:
Brain Informatics, Vol 10, Iss 1, Pp 1-11 (2023)
Abstract Machine Learning (ML) is nowadays an essential tool in the analysis of Magnetic Resonance Imaging (MRI) data, in particular in the identification of brain correlates in neurological and neurodevelopmental disorders. ML requires datasets of a
Externí odkaz:
https://doaj.org/article/8ef41a4d533b4180804530fb3cd0a6df
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7632 (2024)
The investigation of functional magnetic resonance imaging (fMRI) data with traditional machine learning (ML) and deep learning (DL) classifiers has been widely used to study autism spectrum disorders (ASDs). This condition is characterized by sympto
Externí odkaz:
https://doaj.org/article/6b88890d6d1f44588e98142479c17c5a
Autor:
Camilla Scapicchio, Andrea Chincarini, Elena Ballante, Luca Berta, Eleonora Bicci, Chandra Bortolotto, Francesca Brero, Raffaella Fiamma Cabini, Giuseppe Cristofalo, Salvatore Claudio Fanni, Maria Evelina Fantacci, Silvia Figini, Massimo Galia, Pietro Gemma, Emanuele Grassedonio, Alessandro Lascialfari, Cristina Lenardi, Alice Lionetti, Francesca Lizzi, Maurizio Marrale, Massimo Midiri, Cosimo Nardi, Piernicola Oliva, Noemi Perillo, Ian Postuma, Lorenzo Preda, Vieri Rastrelli, Francesco Rizzetto, Nicola Spina, Cinzia Talamonti, Alberto Torresin, Angelo Vanzulli, Federica Volpi, Emanuele Neri, Alessandra Retico
Publikováno v:
European Radiology Experimental, Vol 7, Iss 1, Pp 1-14 (2023)
Abstract Background The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widely recognized. We evaluated the performance of a software for quantitative analysis of chest
Externí odkaz:
https://doaj.org/article/c7bf35ba3d4644329a58313bbc82b18a
Publikováno v:
Applied Sciences, Vol 13, Iss 11, p 6486 (2023)
Magnetic resonance imaging (MRI) nowadays plays an important role in the identification of brain underpinnings in a wide range of neuropsychiatric disorders, including Autism Spectrum Disorders (ASD). Characterizing the hallmarks in these pathologies
Externí odkaz:
https://doaj.org/article/f9fbd272fa774e7ba9d3576a8b2dc1d4
Autor:
Sara Saponaro, Alessia Giuliano, Roberto Bellotti, Angela Lombardi, Sabina Tangaro, Piernicola Oliva, Sara Calderoni, Alessandra Retico
Publikováno v:
NeuroImage: Clinical, Vol 35, Iss , Pp 103082- (2022)
Machine Learning (ML) techniques have been widely used in Neuroimaging studies of Autism Spectrum Disorders (ASD) both to identify possible brain alterations related to this condition and to evaluate the predictive power of brain imaging modalities.
Externí odkaz:
https://doaj.org/article/836e71292a6f4e5b83bb9528a5c4af57
Autor:
Giovanna Spera, Alessandra Retico, Paolo Bosco, Elisa Ferrari, Letizia Palumbo, Piernicola Oliva, Filippo Muratori, Sara Calderoni
Publikováno v:
Frontiers in Psychiatry, Vol 10 (2019)
No univocal and reliable brain-based biomarkers have been detected to date in Autism Spectrum Disorders (ASD). Neuroimaging studies have consistently revealed alterations in brain structure and function of individuals with ASD; however, it remains di
Externí odkaz:
https://doaj.org/article/fb091dd2d7a9490bb4b3e695f97e637b
Autor:
Lorenzo Giuntini, Lisa Castelli, Mirko Massi, Mariaelena Fedi, Caroline Czelusniak, Nicla Gelli, Lucia Liccioli, Francesca Giambi, Chiara Ruberto, Anna Mazzinghi, Serena Barone, Francesca Marchegiani, Stefano Nisi, Carmine Lubritto, Simona Altieri, Luca Tortora, Paolo Branchini, Andrea Fabbri, Valerio Graziani, Sergio Barcellos Lins, Laura Guidorzi, Alessandro Lo Giudice, Alessandro Re, Leandro Sottili, Antonella Balerna, Mariangela Cestelli Guidi, Lucilla Pronti, Martina Romani, Fauzia Albertin, Matteo Bettuzzi, Rosa Brancaccio, Maria Pia Morigi, Daniele Alloni, Andrea Salvini, Barbara Smilgys, Michele Prata, Saverio Altieri, Maurizio Bonesini, Daniela Di Martino, Massimiliano Clemenza, Massimo Carpinelli, Piernicola Oliva, Valeria Sipala, Anna Maria Gueli, Stefania Pasquale, Giuseppe Stella, Giancarlo Pepponi, Francesco Grazzi, Francesco Taccetti
Publikováno v:
Applied Sciences, Vol 11, Iss 8, p 3462 (2021)
Detectors are a key feature of the contemporary scientific approach to cultural heritage (CH), both for diagnostics and conservation. INFN-CHNet is the network of the Italian National Institute of Nuclear Physics that develops and applies new instrum
Externí odkaz:
https://doaj.org/article/79af47f9105d483484af82615a96e84a
Publikováno v:
Journal of Systemics, Cybernetics and Informatics, Vol 4, Iss 3, Pp 18-22 (2006)
Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the tradition
Externí odkaz:
https://doaj.org/article/5330f47c31f140789e18c8d55f16dea5
Autor:
Francesca Lizzi, Ian Postuma, Francesca Brero, Raffaella Fiamma Cabini, Maria Evelina Fantacci, Alessandro Lascialfari, Piernicola Oliva, Lisa Rinaldi, Alessandra Retico
Publikováno v:
The European Physical Journal Plus. 138
Computed tomography (CT) scans are used to evaluate the severity of lung involvement in patients affected by COVID-19 pneumonia. Here, we present an improved version of the LungQuant automatic segmentation software (LungQuantv2), which implements a c