Using Active Contours and Fourier Descriptors for Motion Tracking with Applications in MRI

To estimate motion, the edges of a moving object can be detected using Active Contours. After detecting the edges throughout the duration of the motion, the contours are registered together in order to obtain the motion model parameters. This idea can be applied to motion artifacts in Magnetic Resonance Images (MRI) which are caused by patient motion during the acquisition of an MRI. Thus, if the patient motion can be determined, it will be possible to correct for the motion in the images. The proposed method eliminates motion artifacts by dividing the acquired MRI data into several subbands. These subbands create invariant tissue feature maps called subband images. Using Active Contours, the edges of each subband image are detected and the relative motion is analyzed across the di erent subband images, thus determining the motion parameters. From these motion parameters it is possible to correct the subband images, thus correcting the k-space yielding clear, noise-free MR images.