A respiratory motion artifact reduction method in magnetic resonance imaging is presented. The method is an image reconstruction algorithm based on the assumption that the respiratory motion of the chest is linear in space and arbitrary in time. The linear respiratory motion causes phase distortion on the MR data. In addition, as a result of this motion, the MR data will be the samples of the Fourier transform of the spin density on a nonrectangular grid. In image reconstruction, before taking the inverse Fourier transform, the phase distortion is compensated and the rectangular samples are interpolated from the existing nonrectangular samples. Using this method, a significant amount of motion artifact suppression is achieved with a rough knowledge on the motion. In addition, it is demonstrated that the respiratory motion model parameters can be estimated using the information hidden in the motion artifacts.
ASJC Scopus subject areas
- Computer Science Applications
- Electrical and Electronic Engineering
- Radiological and Ultrasound Technology
- Computational Theory and Mathematics
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging