Cheng Yang

SubDIVIDE: Efficient tensor‐valued diffusion magnetic resonance imaging via joint diffusional variance decomposition modeling and subspace reconstruction

A model‐aware subspace reconstruction framework that integrates DTD‐based DIVIDE modeling with low‐rank signal representations is proposed that suggests that subspace‐constrained reconstruction provides a principled pathway toward efficient and robust multidimensional diffusion MRI.