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The Applications of Artificial Intelligence in Cardiovascular Magnetic Resonance-A Comprehensive Review.
Argentiero, Adriana; Muscogiuri, Giuseppe; Rabbat, Mark G; Martini, Chiara; Soldato, Nicolò; Basile, Paolo; Baggiano, Andrea; Mushtaq, Saima; Fusini, Laura; Mancini, Maria Elisabetta; Gaibazzi, Nicola; Santobuono, Vincenzo Ezio; Sironi, Sandro; Pontone, Gianluca; Guaricci, Andrea Igoren.
Afiliação
  • Argentiero A; University Cardiology Unit, Cardio-Thoracic Department, Policlinic University Hospital, 70121 Bari, Italy.
  • Muscogiuri G; School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy.
  • Rabbat MG; Department of Radiology, IRCCS Istituto Auxologico Italiano, San Luca Hospital, 20149 Milan, Italy.
  • Martini C; Division of Cardiology, Loyola University of Chicago, Chicago, IL 60660, USA.
  • Soldato N; Radiologic Sciences, Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy.
  • Basile P; University Cardiology Unit, Cardio-Thoracic Department, Policlinic University Hospital, 70121 Bari, Italy.
  • Baggiano A; University Cardiology Unit, Cardio-Thoracic Department, Policlinic University Hospital, 70121 Bari, Italy.
  • Mushtaq S; Perioperative and Cardiovascular Imaging Department, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
  • Fusini L; Perioperative and Cardiovascular Imaging Department, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
  • Mancini ME; Perioperative and Cardiovascular Imaging Department, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
  • Gaibazzi N; Perioperative and Cardiovascular Imaging Department, Centro Cardiologico Monzino IRCCS, 20138 Milan, Italy.
  • Santobuono VE; Department of Cardiology, Azienda Ospedaliero-Universitaria, 43126 Parma, Italy.
  • Sironi S; University Cardiology Unit, Cardio-Thoracic Department, Policlinic University Hospital, 70121 Bari, Italy.
  • Pontone G; School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy.
  • Guaricci AI; Department of Radiology, ASST Papa Giovanni XXIII Hospital, 24127 Bergamo, Italy.
J Clin Med ; 11(10)2022 May 19.
Article em En | MEDLINE | ID: mdl-35628992
ABSTRACT
Cardiovascular disease remains an integral field on which new research in both the biomedical and technological fields is based, as it remains the leading cause of mortality and morbidity worldwide. However, despite the progress of cardiac imaging techniques, the heart remains a challenging organ to study. Artificial intelligence (AI) has emerged as one of the major innovations in the field of diagnostic imaging, with a dramatic impact on cardiovascular magnetic resonance imaging (CMR). AI will be increasingly present in the medical world, with strong potential for greater diagnostic efficiency and accuracy. Regarding the use of AI in image acquisition and reconstruction, the main role was to reduce the time of image acquisition and analysis, one of the biggest challenges concerning magnetic resonance; moreover, it has been seen to play a role in the automatic correction of artifacts. The use of these techniques in image segmentation has allowed automatic and accurate quantification of the volumes and masses of the left and right ventricles, with occasional need for manual correction. Furthermore, AI can be a useful tool to directly help the clinician in the diagnosis and derivation of prognostic information of cardiovascular diseases. This review addresses the applications and future prospects of AI in CMR imaging, from image acquisition and reconstruction to image segmentation, tissue characterization, diagnostic evaluation, and prognostication.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: J Clin Med Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: J Clin Med Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Itália