Optimal design of gradient coils in MR imaging: optimizing coil performance versus minimizing cost functions.

The "forward" method of an optimal gradient coil design provides a coil that has the minimal cost function value. It is shown in this study that the solution obtained by minimizing the cost function is directly dependent on the specified cost function and generally results in a deviation from the most desirable coil design. In this paper, a gradient coil design approach for obtaining the best achievable coil performance for pre-determined imaging applications is presented. Through this approach, all intermediate coil performance values calculated during an optimization process, using a simulated annealing algorithm, are stored and presented in a three-dimensional data set. Using this three-dimensional data set, a coil designer is able to make a balance between different coil performance parameters and to select a coil that is the most desirable for the pre-determined imaging applications.