Interactive and intelligent approach for brain extraction from high-resolution volumetric MR neuroimages

This paper introduces an interactive and intelligent approach for accurate brain segmentation. A high resolution 3-Tesla magnetic resonance (MR) dataset was tested by state of the art automated algorithms as well as segmented by making use of the proposed interactive tools. The results show that the automated algorithms gave an incomplete or anatomically incorrect brain surface. About 4% false positive and 10% false negative error rates were reported by evaluating three automated methods. The proposed approach improved the quality and accuracy of the segmented results.