Fuzzy multiscale region growing for segmentation of MR images of the human brain

Abstract

We propose an automatic region growing technique for the segmentation of the cerebral cortex and white matter in MRI data. Our method exploits general anatomical knowledge and uses an iterative multi resolution scheme for the estimation of intensity distributions to compensate for artifacts within the data. We present a comparison to segmentation results created by the neuroimaging software Brainvoyager QX and show advantages of our approach based on a qualitative and quantitative evaluation.