MR fingerprinting offers a rapid way to accurately map multiple tissue parameters. The dictionary based reconstruction under the influence of Gaussian noise is identified as a convex optimization problem and solved by a Nelder-Mead simplex algorithm. Instead of a lengthy and uniform sampling proposed by dictionay matching, the new approach using a heuristic and incoherent sampling in the $$$T_1$$$-$$$T_2$$$ space. More robust $$$T_1$$$ estimations are obtained even under severe noise environments. Thus, a robust and fast MR fingerprinting reconstruction can be made without any dictionary.