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Torlasco, C., Papetti, D., Castelletti, S., Sabatini, M., Muscogiuri, G., Badano, L., et al. (2023). Use of artificial intelligence to automatically predict the optimal patient-specific inversion time for late gadolinium enhancement imaging. Tool development and clinical validation. In EACVI 2023 Abstract (pp.153-154). Oxford University Press [10.1093/ehjci/jead119.103].

Use of artificial intelligence to automatically predict the optimal patient-specific inversion time for late gadolinium enhancement imaging. Tool development and clinical validation

Papetti, D M;Muscogiuri, G;Parati, G;Besozzi, D;
2023
abstract + slide
cardiac magnetic resonance; late gadolinium enhancement imaging; inversion time; artificial intelligence; THAITI
English
EACVI 2023 - 10 May - 12 May 2023
2023
EACVI 2023 Abstract
2023
24
Supplement_1
153
154
https://academic.oup.com/ehjcimaging/article/24/Supplement_1/jead119.103/7198784?login=true#google_vignette
none
Torlasco, C., Papetti, D., Castelletti, S., Sabatini, M., Muscogiuri, G., Badano, L., et al. (2023). Use of artificial intelligence to automatically predict the optimal patient-specific inversion time for late gadolinium enhancement imaging. Tool development and clinical validation. In EACVI 2023 Abstract (pp.153-154). Oxford University Press [10.1093/ehjci/jead119.103].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/456659
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