Purpose: To perform a systematic review on the research on the application of artificial intelligence (AI) to imaging published in Italy and identify its fields of application, methods and results. Materials and Methods: A Pubmed search was conducted using terms Artificial Intelligence, Machine Learning, Deep learning, imaging, and Italy as affiliation, excluding reviews and papers outside time interval 2015-2020. In a second phase, participants of the working group AI4MP on Artificial Intelligence of the Italian Association of Physics in Medicine (AIFM) searched for papers on AI in imaging. Results: The Pubmed search produced 794 results. 168 studies were selected, of which 122 were from Pubmed search and 46 from the working group. The most used imaging modality was MRI (44%) followed by CT(12%) ad radiography/mammography (11%). The most common clinical indication were neurological diseases (29%) and diagnosis of cancer (25%). Classification was the most common task for AI (57%) followed by segmentation (16%). 65% of studies used machine learning and 35% used deep learning. We observed a rapid increase of research in Italy on artificial intelligence in the last 5 years, peaking at 155% from 2018 to 2019.
Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy / Avanzo, Michele; Porzio, Massimiliano; Lorenzon, Leda; Milan, Lisa; Sghedoni, Roberto; Russo, Giorgio; Massafra, Raffaella; Fanizzi, Annarita; Barucci, Andrea; Ardu, Veronica; Branchini, Marco; Giannelli, Marco; Gallio, Elena; Cilla, Savino; Tangaro, Sabina; Lombardi, Angela; Pirrone, Giovanni; De Martin, Elena; Giuliano, Alessia; Belmonte, Gina; Russo, Serenella; Rampado, Osvaldo; Mettivier, Giovanni. - In: PHYSICA MEDICA. - ISSN 1120-1797. - 83:(2021), pp. 221-241. [10.1016/j.ejmp.2021.04.010]
Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy
Lombardi, Angela;
2021-01-01
Abstract
Purpose: To perform a systematic review on the research on the application of artificial intelligence (AI) to imaging published in Italy and identify its fields of application, methods and results. Materials and Methods: A Pubmed search was conducted using terms Artificial Intelligence, Machine Learning, Deep learning, imaging, and Italy as affiliation, excluding reviews and papers outside time interval 2015-2020. In a second phase, participants of the working group AI4MP on Artificial Intelligence of the Italian Association of Physics in Medicine (AIFM) searched for papers on AI in imaging. Results: The Pubmed search produced 794 results. 168 studies were selected, of which 122 were from Pubmed search and 46 from the working group. The most used imaging modality was MRI (44%) followed by CT(12%) ad radiography/mammography (11%). The most common clinical indication were neurological diseases (29%) and diagnosis of cancer (25%). Classification was the most common task for AI (57%) followed by segmentation (16%). 65% of studies used machine learning and 35% used deep learning. We observed a rapid increase of research in Italy on artificial intelligence in the last 5 years, peaking at 155% from 2018 to 2019.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
