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Partial volume tissue classification of multichannel magnetic resonance images-a mixel model

机译:多通道磁共振图像的局部组织分类-混合模型

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摘要

A single volume element (voxel) in a medical image may be composed of a mixture of multiple tissue types. The authors call voxels which contain multiple tissue classes mixels. A statistical mixel image model based on Markov random field (MRF) theory and an algorithm for the classification of mixels are presented. The authors concentrate on the classification of multichannel magnetic resonance (MR) images of the brain although the algorithm has other applications. The authors also present a method for compensating for the gray-level variation of MR images between different slices, which is primarily caused by the inhomogeneity of the RF field produced by the imaging coil.
机译:医学图像中的单个体积元素(体素)可以由多种组织类型的混合物组成。作者称其中包含多个组织类混合像素的体素。提出了基于马尔可夫随机场(MRF)理论的统计混合图像模型和混合图像分类算法。尽管该算法还有其他应用,但作者仍专注于大脑的多通道磁共振(MR)图像的分类。作者还提出了一种用于补偿不同切片之间MR图像灰度级变化的方法,这主要是由成像线圈产生的RF场的不均匀性引起的。

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