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Utility of deep learning networks for the generation of artificial cardiac magnetic resonance images in congenital heart disease.

, , , , , , , , , , and . BMC Medical Imaging, 20 (1): 113 (2020)

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Measurement of Aortic Pressure Wave Velocity by 4D Image Registration., , , , , , , , and . MIUA, page 275-280. BMVA, (2011)Developing and Evaluating Virtual Cardiotomy for Preoperative Planning in Congenital Heart Disease., , , and . MMVR, volume 142 of Studies in Health Technology and Informatics, page 340-345. IOS Press, (2009)Developing a Data Driven Approach for Early Detection of SIRS in Pediatric Intensive Care Using Automatically Labeled Training Data., , , , , , , , , and 7 other author(s). ICIMTH, volume 289 of Studies in Health Technology and Informatics, page 228-231. IOS Press, (2021)euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling, , , , , , , , , and 13 other author(s). Interface Focus, 1 (3): 349--364 (2011)How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalise to rare congenital heart diseases for surgical planning?, , , , , , , , , and . CoRR, (2020)Utility of deep learning networks for the generation of artificial cardiac magnetic resonance images in congenital heart disease., , , , , , , , , and 1 other author(s). BMC Medical Imaging, 20 (1): 113 (2020)How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalize to rare congenital heart diseases for surgical planning?, , , , , , , , , and . Medical Imaging: Image-Guided Procedures, volume 11315 of SPIE Proceedings, page 113151K. SPIE, (2020)