MRI Sequence

Magnetic Resonance Imaging (MRI) sequences are the specific pulse sequences used to acquire images, and current research focuses on improving their efficiency and diagnostic capabilities. This involves developing novel methods for synthesizing missing sequences from available data using deep learning architectures like U-Nets and diffusion models, as well as optimizing existing sequences for improved resolution and contrast through joint optimization of pulse sequences and neural networks. These advancements aim to enhance the accuracy and speed of diagnosis across various applications, including cerebrovascular disease, brain tumor detection, and the analysis of other pathologies, by improving image quality and enabling more comprehensive analysis from fewer scans.