A New Algorithm for Sampling Density Compensation in the Gridding of PROPELLER MRI Data

FENG Yan-qiu; CHEN Wu-fan; YAN Gang; HUANG Xin; CHEN Yang

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A New Algorithm for Sampling Density Compensation in the Gridding of PROPELLER MRI Data

更新时间：2025-07-16

- A New Algorithm for Sampling Density Compensation in the Gridding of PROPELLER MRI Data
- Acta Electronica Sinica Vol. 35, Issue 4, Pages: 766-768(2007)
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  CLC： R445.2
- Published：2007
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FENG Yan-qiu, CHEN Wu-fan, YAN Gang, et al. A New Algorithm for Sampling Density Compensation in the Gridding of PROPELLER MRI Data[J]. Acta Electronica Sinica, 2007, 35(4): 766-768.
DOI：

FENG Yan-qiu, CHEN Wu-fan, YAN Gang, et al. A New Algorithm for Sampling Density Compensation in the Gridding of PROPELLER MRI Data[J]. Acta Electronica Sinica, 2007, 35(4): 766-768. DOI：

摘要

PROPELLER磁共振数据的重建是一个典型的K空间非笛卡尔采样数据的重建问题.由于现有网格化重建算法中的密度补偿需要计算每个采样点的密度补偿系数

须对非笛卡尔分布的数据进行卷积运算

给定

采样点

该卷积运算需要

N×N

/2次距离运算

由于PROPELLER采集的数据量

很大

计算耗时非常长.本文提出PROPELLER数据网格化重建中的密度补偿新算法

通过基于网格化分量全为1的向量来计算在均匀网格点上的采样密度分布值进而加以补偿

使得算法复杂度大大下降.实验表明

本文算法比现有算法的运行时间缩短400多倍

而重建质量与原有算法基本相同.

Abstract

The reconstruction of PROPELLER MRI data is a typical reconstruction of non-Cartesian data.The sampling density compensation in the current gridding reconstruction is accomplished through the convolution of non-Cartesian data

which requires calculating a large number of distances between each other non-Cartesian positions when the number of data is large such as PROPELLER.Therefore the density compensation is highly computationally intensive.In this paper

a new algorithm was proposed for density estimation based on gridding a unity data vector.Since no more computations of distances were needed

the time complexity of the algorithm was decreased greatly.In the experiments

the proposed algorithm is shown to be able to perform the density compensation much more rapidly than the traditional algorithm while achieving equivalent quality of reconstruction.

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Affine Motion Compensation with Improved Reconstruction in PROPELLER MRI

Study on Image Reconstruction of Diffraction Tomography with Density Compensation Algorithm by Voronoi Diagrams

Related Author

LIU Xiao-wu

CHEN Wu-fan

FENG Yan-qiu

FANG Jie

LIU Ren-jin

Related Institution

（南方医科大学生物医学工程学院医学信息研究所，）

College of Mechanical and Electronic Engineering, West Anhui University, Liu'an

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