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Bias field correction based tissue classification of MR images of brain

机译:基于偏场校正的脑MR图像组织分类

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摘要

Segmentation of MR images into tissue classes is often required in clinical applications. But automatic segmentation and tissue classification can be hardly satisfactory because of the overlapped distribution of intensities between tissues. This paper describes a new method called adaptive segmentation that uses knowledge of tissue properties and intensity inhomogeneities to correct and segment multi-spectral MR images. Use of the expectation-maximization (EM) algorithm leads to more accurate results.
机译:在临床应用中通常需要将MR图像分割成组织类别。但是由于组织之间强度的重叠分布,自动分割和组织分类很难令人满意。本文介绍了一种称为自适应分割的新方法,该方法利用组织特性和强度不均匀性的知识来校正和分割多光谱MR图像。期望最大化(EM)算法的使用可导致更准确的结果。

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