Fully automated 3D aortic segmentation of 4D flow MRI for hemodynamic analysis using deep learning

Purpose To generate fully automated and fast 4D‐flow MRI‐based 3D segmentations of the aorta using deep learning for reproducible quantification of aortic flow, peak velocity, and dimensions. Methods A total of 1018 subjects with aortic 4D‐flow MRI (528 with bicuspid aortic valve, 376 with tricuspid...

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Veröffentlicht in:	Magnetic resonance in medicine 2020-10, Vol.84 (4), p.2204-2218
Hauptverfasser:	Berhane, Haben, Scott, Michael, Elbaz, Mohammed, Jarvis, Kelly, McCarthy, Patrick, Carr, James, Malaisrie, Chris, Avery, Ryan, Barker, Alex J., Robinson, Joshua D., Rigsby, Cynthia K., Markl, Michael
Format:	Artikel
Sprache:	eng
Schlagworte:	4D flow MRI Aorta Aorta - diagnostic imaging Aortic valve Artificial neural networks Automation Coronary vessels Deep Learning Ground truth Heart valves Hemodynamics Humans Image processing Image segmentation Machine learning Magnetic Resonance Imaging Metric space MRI Neural networks Reproducibility Reproducibility of Results thoracic aorta Three dimensional flow Velocity
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