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Improved Tissue Segmentation by Including an MR Acquisition Model

机译:通过包括先生采集模型改善组织分割

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This paper presents a new MR tissue segmentation method. In contrast to most previous methods the image formation model includes the point spread function of the image acquisition. This allows optimal combination of images acquired with different contrast weighting, resolutions, and orientations. The proposed method computes the regularized maximum likelihood partial volume segmentation from the images. The quality the resulting segmentation is studied with a simulation experiment and by testing the reproducibility of the segmentation on repeated brain MRI scans. Our results demonstrate improved segmentation quality, especially at tissue edges.
机译:本文提出了一种新的MR组织分割方法。与大多数先前的方法相比,图像形成模型包括图像采集的点扩展功能。这允许用不同对比度加权,分辨率和方向获取的图像的最佳组合。所提出的方法从图像计算正则化的最大似然部分卷分割。通过模拟实验研究了所得分割的质量,并通过测试重复脑MRI扫描的分割的再现性。我们的结果表明了分割质量改善,特别是在组织边缘。

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