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Found 4 papers, 2 papers with code
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation
In cardiac magnetic resonance (CMR) imaging, a 3D high-resolution segmentation of the heart is essential for detailed description of its anatomical structures.
A Comprehensive Approach for Learning-based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks
If long axis (LA) images are available, PSMs are generated for them and combined to create the target PSM; if not, the target PSM is produced from the same stack using a 3D model trained from motion-free stacks.
Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling
However, current approaches to the diagnosis of cardiovascular diseases often rely on subjective human assessment as well as manual analysis of medical images.
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation
However, in most recent and promising techniques such as CNN based segmentation it is not obvious how to incorporate such prior knowledge.
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