磁共振成像数据非均匀性梯度的快速算法。
Fast algorithm for calculation of inhomogeneity gradient in magnetic resonance imaging data.
机构信息
Department of Diagnostic and Interventional Imaging, University of Texas Medical School at Houston, Houston, Texas, USA.
出版信息
J Magn Reson Imaging. 2010 Nov;32(5):1197-208. doi: 10.1002/jmri.22344.
PURPOSE
To develop and implement a new approach for correcting the intensity inhomogeneity in magnetic resonance imaging (MRI) data.
MATERIALS AND METHODS
The algorithm is based on the assumption that intensity inhomogeneity in MR data is multiplicative and smoothly varying. Using a statistically stable method, the algorithm first calculates the partial derivative of the inhomogeneity gradient across the data. The algorithm then solves for the gradient field and fits it to a parametric surface. It was tested on both simulated and real human and animal MRI data.
RESULTS
The algorithm is shown to restore the homogeneity in all images that were tested. On real human brain images the algorithm demonstrated superior or comparable performance relative to some of the commonly used intensity inhomogeneity correction methods such as SPM, BrainSuite, and N3.
CONCLUSION
The proposed algorithm provides an alternative method for correcting the intensity inhomogeneity in MR images. It is shown to be fast and its performance is superior or comparable to algorithms described in the published literature. Due to its generality, this algorithm is applicable to MR images of both humans and animals.
目的
开发并实现一种新的磁共振成像（MRI）数据强度不均匀性校正方法。
材料与方法
该算法基于磁共振数据强度不均匀性是乘法和平滑变化的假设。该算法首先使用统计上稳定的方法计算数据中不均匀性梯度的偏导数。然后，该算法求解梯度场并将其拟合到参数曲面上。在模拟和真实的人体和动物 MRI 数据上对该算法进行了测试。
结果
该算法可恢复所有测试图像的均匀性。在真实的人脑图像上，该算法的性能优于或可比于一些常用的强度不均匀性校正方法，如 SPM、BrainSuite 和 N3。
结论
该算法为校正磁共振图像的强度不均匀性提供了一种替代方法。它的速度很快，其性能优于或可比于已发表文献中描述的算法。由于其通用性，该算法适用于人类和动物的磁共振图像。
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