A Novel Noise-removed Algorithm for Tagging Effects in Intermolecular Multiple-quantum Coherence Magnetic Resonance Images

摘要

Since the acquired images are often distorted by noise resulting from various experimental and other sources (e.g., the RF tagging effects) in magnetic resonance imaging (MRI), removing noise is a very important work and at the same time useful information should be well preserved. In this paper, a novel, fast denoising algorithm has been proposed to make tradeoff between reducing noise and enlarging contrast of MRI images. Finally the computed results are in good agreement with our theoretical prediction.