Volume 23, Issue Supplement_2, September 2022

Convolutional neural network transformer (CNNT) for free-breathing real-time cine imaging

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The quality of reporting in cardiac MRI artificial intelligence segmentation studies - a systematic review

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Leveraging CMR for 3D echocardiography: an annotated multimodality dataset for AI

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Speeding up cardiac MR segmentation with semi-supervision: applications in cine imaging

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Myocardial fibrosis detection using kernel methods: preliminary results from a cardiac magnetic resonance study

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CNNT DB-LGE: free-breathing dark blood late enhancement imaging using the convolutional neural network transformer speeds acquisition by 50%

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Preliminary data on a fully automated left ventricular late gadolinium enhancement detection by a convolutional neuronal network in chronic myocardial infarction

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Artificial intelligence with spatial-attention for ventricular volumes and mass assessment in cardiac magnetic resonance images with susceptibility artifacts

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Improving the diagnostic accuracy of apical hypertrophic cardiomyopathy using machine learning

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Adverse events prediction in nonischemic dilated cardiomyopathy by two machine learning models integrating clinical and cardiovascular magnetic resonance data

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Asymmetric septal thickening is observed in hypertrophic cardiomyopathy mutation carriers without left ventricular hypertrophy: insights from AI analysis

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The utility of a fully automated cardiac magnetic resonance post-processing tool and radiomics algorithm to non-invasively classify patients with or without significant coronary artery stenosis

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AI-AIF: artificial intelligence-based arterial input function correction for quantitative stress perfusion cardiac MRI

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Annotation and quality assessment of left ventricular filling and relaxation pattern using one-dimensional convolutional neural network

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Robustness of T1 and ECV mapping radiomics features: a between-session evaluation in young athletes

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Fully automated machine learning-based selection of optimal bSSFP frequency offset for artifact reduction in cardiac MRI

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A post processing pipeline to prepare raw data for machine learning algorithms in cardiac magnetic resonance imaging

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Spatiotemporal variational neural network for reconstruction of highly accelerated cardiac cine MRI

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TVnet: automated global analysis of tricuspid valve plane motion in CMR long-axis cines with residual neural networks for assessment of right ventricular function

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Fully automatic AI-based valve motion parameter extraction on long axis CINE images - application on N=11000 patient datasets

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