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Deep learning super-resolution improves flow quantification over standard interpolation in 4D-flow MRI for bicuspid aortic valve

31 August 2026 (11:15 - 12:00)
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Congress Presentation Part of: Artificial intelligence in cardiovascular imaging: methods, performance, and clinical readiness Magnetic Resonance Imaging ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

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Ms Houriehsadat Jamalidinan

University of Calgary, Calgary (Canada)

4 More presentations in this session

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Optimizing echocardiography workflow to increase access to high quality care for patients
Miss C. Alonso Casero (Madrid, ES)
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A dual modal collaborative learning network for echocardiography video segmentation
Mr X. Zhou (Beijing, CN)
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Deep learning for x-ray coronary angiography: a systematic review of methods, validation, and clinical readiness
Doctor C. Goelz (Munich, DE)
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Electrocardiogram complexity determines large language model diagnostic accuracy: a pathology-stratified analysis of 599 cases across 22 diagnostic categories
Doctor H. Kamalanathan (Sydney, AU)
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Artificial intelligence in cardiovascular imaging: methods, performance, and clinical readiness

The Event

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ESC Congress 2026

31 August 2026 11:15 CET
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