Why the study?
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.
Does a deep learning convolutional neural network provide accurate and fast 3D aortic segmentation from 4D-flow MRI compared to manual segmentation in subjects with and without aortic pathology?
Population
1018 subjects with aortic 4D-flow MRI (528 bicuspid aortic valve, 376 tricuspid aortic valve with dilation, 114 healthy controls)
Comparison
Convolutional neural network segmentation vs manual segmentation
Design
Diagnostic imaging validation study
Authors
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Supports automated aortic analysis in 4D-flow research; leaves open prospective validation before clinical use.
Does a deep learning convolutional neural network provide accurate and fast 3D aortic segmentation from 4D-flow MRI compared to manual segmentation in subjects with and without aortic pathology?
Deep learning enables fast, automated, and highly accurate 3D aortic segmentation from 4D-flow MRI, significantly reducing analysis time compared to manual methods.
Berhane et al. (2020) studied this question.
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