Magnetic Resonance Imaging (MRI) utilizes the spin properties of hydrogen nuclei in a strong magnetic field and the response of radiofrequency impulses to generate high-resolution images, and its non-invasive and multi-parametric imaging capabilities make it irreplaceable in the diagnosis of oncology, neurological and cardiovascular diseases. Diffusion Magnetic Resonance Imaging (dMRI) reveals the microstructure of tissues by measuring the diffusion motion of water molecules. For example, Diffusion Weighted Imaging (DWI) and Diffusion Tensor Imaging (DTI) quantify the direction of nerve fibers, etc., which provide critical information for stroke, tumors and neurodegenerative diseases. Microstructure modeling is an advanced method derived from conventional dMRI. By systematically varying diffusion-weighted parameters—such as gradient strength, direction, and diffusion time. It probes the behavior of water diffusion within biological microenvironments. It then applies mathematical and physical models to resolve key microstructural characteristics of tissue at the cellular level. This technique is broadly divided into two main strategies: q-space modeling, which manipulates diffusion gradient parameters, and t-space modeling, which alters diffusion time.