PARALLEL MAGNETIC RESONANCE IMAGING RECONSTRUCTION USING SIMILARITYBASED REGULARIZATION
The parallel magnetic resonance imaging (parallel imaging) technique reduces the MR data acquisition time by using multiple receiver coils. Because of its ill-conditioned system matrix, the reconstruction suffers from noise amplification at high reduction factors, such as in the standard SENSE reconstruction. Total variation (TV) regularization is a popular technique for solving this problem. However, TV regularized images are vulnerable to staircase artifacts and texture loss. In this paper, we proposed a similarity-based regularization technique which enforces the consistence and similarity of pixel values within the image. The phantom simulation and in vivo experimental results demonstrate that this method can effectively suppress noise amplification in SENSE reconstruction while preserving image details. Compared with TV regularized images, images reconstructed by the new method are free of staircase artifacts and suffer less from structure loss.
parallel imaging magnetic resonance SENSE similarity-based regularization total variation
Sheng Fang Kui Ying Jianping Cheng
Department of Engineering Physics Tsinghua University Beijing,China
国际会议
北京
英文
1-4
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）