Multi Echo

Multi-echo MRI techniques acquire multiple images at varying echo times, improving the accuracy and efficiency of various MRI applications. Current research focuses on accelerating data acquisition and improving reconstruction quality using deep learning methods, such as deep image priors, physics-driven networks, and convolutional neural networks, often incorporating self-supervised learning or optimized sampling patterns. These advancements aim to enhance the speed and accuracy of quantitative measurements, such as triglyceride double bond quantification and quantitative susceptibility mapping, leading to improved diagnostic capabilities and potentially reducing scan times for patients.