Even though the brain is microscopically heterogeneous, the majority of currently used quantitative MRI methods in brain research employ idealized models to describe specific structures. Multidimensional relaxation-diffusion correlation (REDCO) is an assumption-free method that measures how water is distributed within the tissue. REDCO had never been used in clinical applications because of the large amount of data it requires. Here we apply the concept of marginal distributions constrained optimization (MADCO) to REDCO-MRI experiments. Using this approach data requirements are vastly reduced, making REDCO-MRI a clinically feasible imaging technique to infer the underlying microstructure, number of compartments, and possibly their function.