基于em算法的自动人脑MRI体积分析技术

M. Nazari, Y. P. Singh
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引用次数: 1

摘要

本文介绍了基于期望最大化(EM)算法的多种应用的人脑MR图像自动体积分析。它包括体素标记、计数和计算组织体积。体素标记需要对脑磁共振图像进行分割,通常是基于体素强度信号进行分割。一种广泛使用的分割方法是通过EM算法创建高斯混合模型(GMM),同样可以用来寻找组织,类别标签和体积。实验结果为自动分割男性和女性受试者的体积分析以及正常组织类别的体积分析提供了实验结果,以验证用于诊断应用的自动体积分析和统计推断的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic human brain MRI volumetric analysis technique using EM-algorithm
The paper presents automated volumetric analysis of human brain MR images for many applications based on the Expectation-maximization (EM) algorithm. It involves voxel labeling, counting, and calculating tissues volume. The voxel labeling requires the brain magnetic resonance image segmentation which is most commonly performed based on voxels intensity signals. A widely used method for segmentation is by creating a Gaussian Mixture Model (GMM) through the EM algorithm and the same can be used to find the tissues, class label and volumes. The experimental results are provided for volumetric analysis of automated segmentation of male and female subjects as well as normal volumes of tissue classes for verifying correctness of automated volumetric analysis and statistical inference for diagnostic applications.
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