Keywords: Microstructure, Diffusion/other diffusion imaging techniques, Diffusion modeling, Tissue characterization, Soma, Exchange
Motivation: Gray Matter lacks a unified microstructure model, unlike White Matter. This study introduces the Generalized Exchange Model (GEM) to unify Gray Matter models, introducing exchange with simple structures.
Goal(s): Evaluate GEM performance, compare it with other Gray Matter models, and assess its potential for clinical MRI.
Approach: GEM parameters and equations are detailed and validated with simulated data. GEM is applied on clinical MRI data, and compared to other Gray Matter model estimates.
Results: GEM successfully unifies Gray Matter diffusion models, offering plausible estimations in clinical MRI revealing microstructural patterns. Future research will optimize data acquisition and assess accuracy.
Impact: The introduction of the Generalized Exchange Model holds significant implications. For scientists, it provides a unified framework, potentially simplifying and enhancing Gray Matter modeling, promoting consistency in research. Clinicians may benefit from improved specificity in diagnosing neurological conditions.
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