Denoising of high-resolution 3D UTE-MR angiogram data using lightweight and efficient convolutional neural networks
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High-resolution magnetic resonance angiography (~ 50 μm3 MRA) data plays a critical role in the accurate diagnosis of various vascular disorders. However, it is very challenging to acquire, and it is susceptible to artifacts and noise which limits its ability... ...
