Michele Avanzo1, Massimiliano Porzio2, Leda Lorenzon3, Lisa Milan4, Roberto Sghedoni5, Giorgio Russo6, Raffaella Massafra7, Annarita Fanizzi7, Andrea Barucci8, Veronica Ardu9, Marco Branchini10, Marco Giannelli11, Elena Gallio12, Savino Cilla13, Sabina Tangaro14, Angela Lombardi15, Giovanni Pirrone16, Elena De Martin17, Alessia Giuliano18, Gina Belmonte18, Serenella Russo19, Osvaldo Rampado12, Giovanni Mettivier20. 1. Medical Physics Department, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, 33081 Aviano PN, Italy. Electronic address: mavanzo@cro.it. 2. Medical Physics Department, ASL CN1, Via Carlo Boggio 12, 12100 Cuneo CN, Italy. 3. Medical Physics Department, Bolzano Hospital, 39100 Bolzano, Italy. 4. Clinic of Nuclear Medicine and Molecular Imaging, Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland. 5. Medical Physics Unit, Azienda USL-IRCCS di Reggio Emilia, Via Amendola, 2, 42122 Reggio Emilia, Italy. 6. Secondary Site Cefalù - Institute of Bioimaging and Molecular Physiology (IBFM) - National Research Council (CNR), Laboratori Nazionali del Sud - National Institute for Nuclear Physics (LNS-INFN). 7. Struttura Semplice Dipartimentale di Fisica Sanitaria, IRCCS. Istituto Tumori "Giovanni Paolo II", Bari, Italy. 8. Institute of Applied Physics "Nello Carrara", Italian National Research Council, via Madonna del Piano 10, Sesto Fiorentino, FI 50019, Italy. Electronic address: a.barucci@ifac.cnr.it. 9. UOS Fisica Sanitaria, ASST Lodi, Lodi, Italy. 10. Medical Physics Department, ASST Valtellina e Alto Lario, Via Stelvio 25, 23100 Sondrio, Italy. 11. Unit of Medical Physics, Pisa University Hospital "Azienda Ospedaliero-Universitaria Pisana", via Roma 67, 56126 Pisa, Italy. 12. Medical Physics Unit, A.O.U. Città della Salute e della Scienza di Torino, 10126 Torino, Italy. 13. Medical Physics Unit, Gemelli Molise Hospital, Catholic University of Sacred Heart, 86100 Campobasso, Italy. 14. Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti - Università degli Studi di Bari Aldo Moro, Via G. Amendola, 165/a, 70126 Bari, Italy; Istituto Nazionale di Fisica Nucleare - Sezione di Bari, Via Orabona 4, 70125 Bari, Italy. 15. Istituto Nazionale di Fisica Nucleare - Sezione di Bari, Via Orabona 4, 70125 Bari, Italy; Dipartimento Interateneo di Fisica, Università degli Studi di Bari Aldo Moro, Via Orabona 4, 70125 Bari, Italy. 16. Medical Physics Department, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, 33081 Aviano PN, Italy. 17. Health Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy. 18. Medical Physics Department, San Luca Hospital, 55100 Lucca, Italy. 19. Medical Physics Unit, AUSL Toscana Centro, Via dell'Antella 58, 50012 Bagno a Ripoli (FI), Italy. 20. Dipartimento di Fisica E.Pancini, Università degli Studi di Napoli Federico II and INFN Napoli, I-80126 Napoli, Italy.
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. CONCLUSIONS: We are witnessing an unprecedented interest in AI applied to imaging in Italy, in a diversity of fields and imaging techniques. Further initiatives are needed to build common frameworks and databases, collaborations among different types of institutions, and guidelines for research on AI.
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. CONCLUSIONS: We are witnessing an unprecedented interest in AI applied to imaging in Italy, in a diversity of fields and imaging techniques. Further initiatives are needed to build common frameworks and databases, collaborations among different types of institutions, and guidelines for research on AI.
Authors: Jan Endrikat; Gilda Schmidt; Daniel Haverstock; Olaf Weber; Zuzana Jirakova Trnkova; Jörg Barkhausen Journal: Breast Cancer (Auckl) Date: 2022-04-19