What is it about?
Brain MRI segmentation is a challenge when coping with artifacts such as intensity non-uniformity, partial volume effects and noise. Because artifacts change the intensity of different part of MRI modalities, describing the intensity of these modalities is highly uncertain. The purpose of this research is to offer a technique based on data fusion of different modalities to segment brain MRIs.
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Why is it important?
In this article, it is proposed that the Dempster-Shafer theory and fuzzy clustering can be combined for brain MRI segmentation. The purpose of this research is to offer a technique based on data fusion of different modalities to segment brain MRIs. T1, T2, PD and Flair were employed in this study.
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This page is a summary of: Brain MRI segmentation by combining different MRI modalities using Dempster-Shafer theory , IET Image Processing, March 2018, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-ipr.2017.0473.
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