  Purpose: To develop a simple and robust tool for the estimation of gradient
delays from highly undersampled radial k-space data. Theory: In radial imaging
gradient delays induce parallel and orthogonal trajectory shifts, which can be
described using an ellipse model. The intersection points of the radial spokes,
which can be estimated by spoke-by-spoke comparison of k-space samples,
distinctly determine the parameters of the ellipse. Using the proposed method
(RING), these parameters can be obtained using a least-squares fit and utilized
for the correction of gradient delays. Methods: The functionality and accuracy
of the proposed RING method is validated and compared to correlation-based
gradient-delay estimation from opposing spokes using numerical simulations,
phantom and in vivo heart measurements. Results: In all experiments, RING
robustly provides accurate gradient delay estimations even for as few as three
radial spokes. Conclusion: The simple and straightforward to implement RING
method provides accurate gradient delay estimation for highly undersampled
radial imaging. Keywords: trajectory correction, radial imaging, gradient
delay, artifacts, system imperfections, RING
