Fig. 2.

Data driven respiratory motion detection. a Respiratory motion is extracted from the profiles through the k-space center d(k_x, k_y = 0, k_z = 0). The temporal evolution of readouts through the k-space center shows a modulation with respiratory motion and cardiac motion. b The 2nd principal component provides the main variation of the signal. c A lowpass filter limits the spectral components to the expected frequency range of respiratory motion. d) Coil clustering is used to combine the signals from different channels and provides a final estimate of respiratory motion