Tekalp Artifacts due to involuntary patient motion have been a major source of image degradation in 2-D and 3-D Fourier Magnetic Resonance Imaging (MRI) for many years. These artifacts, often called "ghosts," manifest themselves as a series of repeated and blurred versions of some features in the patient. Most of the contemporary methods which account for motion effects require additional hardware or instrumentation to monitor the patient motion. This research is examining novel signal/image processing methods for the detection and correction of motion artifacts in MRI by means of postprocessing of the motion-corrupted raw MR data. The research entails modeling (mathematically) the data acquisition process in the presence of arbitrary patient motion, the development of signal/image enhancement algorithms based on the resulting model, and their verification with controlled MRI experiments as well as clinical MRI data. A major advantage of the proposed methods is that they can be implemented in software and do not require any additional hardware installation to existing systems.
