Improved tissue segmentation by including an MR acquisition model

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.

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