Modified Iterative Reconstruction Algorithm for Spiral MRI

Anju George, Ajay Kumar
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Abstract

The MRI imaging is an efficient tool for disease diagnosis, and the features of the taken image has much importance. The reconstruction of such images needs much attention. The main limitation of MRI imaging is its long scan time. The time taken for acquisition can be reduced by non Cartesian acquisition. Spiral MRI is a non Cartesian MRI imaging and is less affected by motion and flow artifacts. Still, reconstruction of images from non-Cartesian MRI data will suffer from reconstruction errors and in-homogeneity artifacts. This will adversely affect the disease diagnosis. Algorithms like conjugate phase method, Field map calculating Methods, iterative Next Neighbor re-gridding algorithms etc were proposed for solving such issues. Among these, iterative Next Neighbor re-gridding algorithm proved efficient. The main focus of this paper is on efficient reconstruction of spiral MRI image with an improved Iterative next neighbor algorithm which will result in comparatively better picture quality.
螺旋MRI改进迭代重建算法
MRI成像是一种有效的疾病诊断工具,其图像特征具有重要意义。这类图像的重建需要特别注意。MRI成像的主要限制是扫描时间长。非笛卡儿式习得可以减少习得所需的时间。螺旋核磁共振成像是一种非笛卡尔核磁共振成像,受运动和流动伪影的影响较小。然而,从非笛卡尔核磁共振数据重建图像将遭受重建误差和非均匀性伪影。这将对疾病的诊断产生不利影响。针对这类问题,提出了共轭相位法、场图计算法、迭代近邻重网格法等算法。其中,迭代近邻重网格算法被证明是有效的。本文主要研究了一种改进的迭代下邻算法对螺旋MRI图像的有效重建,从而获得相对较好的图像质量。
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