An Automated Multi-spectral MRI Segmentation Algorithm Using Approximate Reducts

We introduce an automated multi-spectral MRI segmentation technique based on approximate reducts derived from the data mining paradigm of the theory of rough sets. We utilized the T1, T2 and PD MRI images from the Simulated Brain Database as a ”gold standard” to train and test our segmentation algorithm. The results suggest that approximate reducts, used alone or in combination with other classification methods, may provide a novel and efficient approach to the segmentation of volumetric MRI data sets.

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