GA-BASED OPTIMIZATION OF TAPERING WINDOWS FOR ARTIFACT REDUCTION IN FOURIER ELECTRON MAGNETIC RESONANCE IMAGES

摘要

Optimization of tapering windows for artifact reduction in two-dimensional (2D) Fourier electron magnetic resonance (EMR) tomography using genetic algorithm (GA) is presented. EMR imaging (EMRI) is a fast emerging functional imaging modality for studying free radicals in biological systems. EMRI by single point imaging (SPI) modality is a Fourier imaging technique. The bioclearance of the imaging agent as well as the need to minimize the radio frequency power deposition on the live animals, dictate reduced k-space sampling. This leads to ringing (Gibbs) artifacts in both directions of the 2D image, because, unlike the conventional MRI, SPI is phase encoding in both directions. To dampen the high-frequency components, data tapering windows are multiplicatively applied to provide tolerable blurred resultant image with reduced Gibbs ringing. To find a compromise between blur and ringing artifact, in this paper a method of optimizing the window functions by using GA is proposed. Our experiments suggest GA-based Kaiser window shows better performance by visual as well as quantitative evaluation.