Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy. (March 2021)
- Record Type:
- Journal Article
- Title:
- Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy. (March 2021)
- Main Title:
- Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy
- Authors:
- 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 - Abstract:
- Highlights: A systematic search for papers on applications of AI to medical imaging in Italy was performed. 168 research papers were selected 65% using machine learning, 35% deep learning. A rapid increase of interest in AI was observed in the last years. Further collaborations, initiatives and guidelines are needed to develop the research on AI on Imaging. 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 ofHighlights: A systematic search for papers on applications of AI to medical imaging in Italy was performed. 168 research papers were selected 65% using machine learning, 35% deep learning. A rapid increase of interest in AI was observed in the last years. Further collaborations, initiatives and guidelines are needed to develop the research on AI on Imaging. 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. … (more)
- Is Part Of:
- Physica medica. Volume 83(2021)
- Journal:
- Physica medica
- Issue:
- Volume 83(2021)
- Issue Display:
- Volume 83, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 83
- Issue:
- 2021
- Issue Sort Value:
- 2021-0083-2021-0000
- Page Start:
- 221
- Page End:
- 241
- Publication Date:
- 2021-03
- Subjects:
- Machine learning -- Deep learning -- Artificial intelligence -- Imaging -- Radiomics -- Radiotherapy
Medical physics -- Periodicals
Biophysics -- Periodicals
Biophysics -- Periodicals
Imagerie médicale -- Périodiques
Radiothérapie -- Périodiques
Rayons X -- Sécurité -- Mesures -- Périodiques
Physique -- Périodiques
Médecine -- Périodiques
610.153 - Journal URLs:
- http://www.sciencedirect.com/science/journal/11201797 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/11201797 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/11201797 ↗
http://www.elsevier.com/journals ↗
http://www.physicamedica.com ↗ - DOI:
- 10.1016/j.ejmp.2021.04.010 ↗
- Languages:
- English
- ISSNs:
- 1120-1797
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6475.070000
British Library DSC - BLDSS-3PM
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- 16993.xml