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用于磁共振成像的电势能量优化三维径向采样轨迹

Electric potential energy optimized 3D radial sampling trajectories for MRI.

作者信息

Huynh Christopher, Goolaub Datta Singh, Macgowan Christopher K

机构信息

Translational Medicine, Hospital for Sick Children, Toronto, ON, Canada.

Medical Biophysics, University of Toronto, Toronto, ON, Canada.

出版信息

Sci Rep. 2024 Oct 15;14(1):24084. doi: 10.1038/s41598-024-74437-x.

Abstract

A novel method for creating "golden" 3D center-out radial MRI sampling trajectories was developed and analyzed. This method, called ELECTRO (ELECTRic potential energy Optimized), uses repulsive forces to minimize electric potential energy. An objective function [Formula: see text], the electric potential energies of all subsets of consecutive readouts in a 3D radial trajectory, and its reduced form were minimized using a multi-stage optimization strategy. A metric called normalized mean nearest neighbor angular distance (NMNA) was proposed for describing distributions of points on a sphere. ELECTRO and other relevant golden trajectories were compared in silico using NMNA and point spread function analysis. Consecutive readouts from an ELECTRO trajectory were well spread out, with consistent NMNA values across sphere sizes (σ = 0.005) and between regions on the sphere (NMNA ≈ 1.49). Conversely, the supergolden trajectory had poor consistency in NMNA values (σ = 0.090) and clustering (NMNA = 1.28 at the pole with 40,000 readouts) that lead to artifact in the point spread function. Multi-stage optimization was faster than single-stage and obtained lower values of [Formula: see text] (e.g., 0.87 vs. 0.91, for a sphere size of 40). In conclusion, ELECTRO trajectories are more golden than other 3D center-out radial trajectories, making them a suitable candidate for dynamic 3D MR imaging.

摘要

开发并分析了一种用于创建“黄金”3D中心向外径向MRI采样轨迹的新方法。这种方法称为ELECTRO(电能优化),利用排斥力来最小化电势能。使用多阶段优化策略,将目标函数[公式:见正文](即3D径向轨迹中连续读出的所有子集的电势能)及其简化形式最小化。提出了一种称为归一化平均最近邻角距离(NMNA)的度量,用于描述球面上点的分布。使用NMNA和点扩散函数分析在计算机模拟中比较了ELECTRO和其他相关的黄金轨迹。ELECTRO轨迹的连续读出分布良好,在不同球体大小(σ = 0.005)和球面上各区域之间具有一致的NMNA值(NMNA≈1.49)。相反,超黄金轨迹的NMNA值一致性较差(σ = 0.090)且存在聚类现象(在极点处有40,000次读出时,NMNA = 1.28),这导致点扩散函数中出现伪影。多阶段优化比单阶段优化更快,并且获得了更低的[公式:见正文]值(例如,对于球体大小为40的情况,分别为0.87和0.91)。总之,ELECTRO轨迹比其他3D中心向外径向轨迹更具黄金特性,使其成为动态3D MR成像的合适候选者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f584/11480509/8ee7a97616d3/41598_2024_74437_Fig1_HTML.jpg

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