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Segmentation of the aorta in 4D flow MRI using 4D convolutional kernels and learning from sparse annotations
Automated aortic segmentation in 4D flow MRI is essential for reproducible hemodynamic assessment but is limited by scarce dense annotations and high computational demands. We developed a fully automated 4D (3D+time) U-Net for segmenting the ascending aorta, arch, and proximal descending aorta, usin
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