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Found 4 papers, 2 papers with code
UniXGen: A Unified Vision-Language Model for Multi-View Chest X-ray Generation and Report Generation
We also find that view-specific special tokens can distinguish between different views and properly generate specific views even if they do not exist in the dataset, and utilizing multi-view chest X-rays can faithfully capture the abnormal findings in the additional X-rays.
Unpaired Deep Learning for Accelerated MRI using Optimal Transport Driven CycleGAN
Recently, deep learning approaches for accelerated MRI have been extensively studied thanks to their high performance reconstruction in spite of significantly reduced runtime complexity.
Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data
Time-of-flight magnetic resonance angiography (TOF-MRA) is one of the most widely used non-contrast MR imaging methods to visualize blood vessels, but due to the 3-D volume acquisition highly accelerated acquisition is necessary.
k-Space Deep Learning for Accelerated MRI
The annihilating filter-based low-rank Hankel matrix approach (ALOHA) is one of the state-of-the-art compressed sensing approaches that directly interpolates the missing k-space data using low-rank Hankel matrix completion.
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Denoising
on Darmstadt Noise Dataset
