一种用于自动校正MRI数据中强度不均匀性的非参数方法。

A nonparametric method for automatic correction of intensity nonuniformity in MRI data.

作者信息

Sled J G, Zijdenbos A P, Evans A C

机构信息

McConnell Brain Imaging Centre, Montréal Neurological Institute and McGill University, Canada.

出版信息

IEEE Trans Med Imaging. 1998 Feb;17(1):87-97. doi: 10.1109/42.668698.

DOI:10.1109/42.668698

PMID:9617910

Abstract

A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present. The method has the advantage that it can be applied at an early stage in an automated data analysis, before a tissue model is available. Described as nonparametric nonuniform intensity normalization (N3), the method is independent of pulse sequence and insensitive to pathological data that might otherwise violate model assumptions. To eliminate the dependence of the field estimate on anatomy, an iterative approach is employed to estimate both the multiplicative bias field and the distribution of the true tissue intensities. The performance of this method is evaluated using both real and simulated MR data.

摘要

本文描述了一种校正磁共振（MR）数据强度非均匀性的新方法，该方法无需现有组织类别的模型即可实现高性能。该方法的优点是可以在自动化数据分析的早期阶段应用，此时组织模型尚未建立。该方法被称为非参数非均匀强度归一化（N3），它与脉冲序列无关，并且对可能违反模型假设的病理数据不敏感。为了消除场估计对解剖结构的依赖性，采用迭代方法来估计乘法偏置场和真实组织强度的分布。使用真实和模拟的MR数据评估了该方法的性能。