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Found 3 papers, 2 papers with code
VS-Net: Variable splitting network for accelerated parallel MRI reconstruction
In this work, we propose a deep learning approach for parallel magnetic resonance imaging (MRI) reconstruction, termed a variable splitting network (VS-Net), for an efficient, high-quality reconstruction of undersampled multi-coil MR data.
Automatic 3D bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach
The proposed pipeline is fully automated, due to network's ability to infer landmarks, which are then used downstream in the pipeline to initialise atlas propagation.
Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension
In this paper we introduce a novel and accurate optimisation method for segmentation of cardiac MR (CMR) images in patients with pulmonary hypertension (PH).
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