MANIFOLD OPTIMIZATION-BASED DEEP LEARNING METHOD FOR DYNAMIC MAGNETIC RESONANCE IMAGING

摘要

A manifold optimization-based deep learning method and apparatus for dynamic magnetic resonance (MR) imaging, a device, and a storage medium. The method comprises: creating a fixed rank-based manifold space, and deploying an entire optimization process into a neural network to obtain a manifold optimization-based deep model (110); for a dynamic MR image in which there is an interrelation between frames, constructing an image reconstruction model on a nonlinear manifold space (120); designing an iterative reconstruction algorithm on a corresponding manifold (130); and deploying the iterative reconstruction algorithm as a deep neural network (140). The solution avoids a complicated parameter adjustment process, and greatly shortens the reconstruction time; in addition, an original complicated nonlinear optimization process in a linear space is converted into a linear optimization process in a manifold space, and the reconstruction performance is expected to be further improved.