Compressed Sensing MRI

Compressed sensing MRI (CS-MRI) aims to accelerate MRI scans by acquiring fewer data points than traditional methods, reconstructing high-quality images using sophisticated algorithms. Current research heavily utilizes deep learning, particularly convolutional neural networks (CNNs) and generative adversarial networks (GANs), often integrated with techniques like alternating direction method of multipliers (ADMM) and incorporating variational autoencoders (VAEs) for improved regularization and uncertainty quantification. These advancements are improving image quality and reducing scan times, leading to significant potential for faster and more efficient clinical diagnosis and research in medical imaging.