MRI Brain Extraction with Combined Expectation Maximization and Geodesic Active Contours

This paper presents a new fully automated method for the extraction of brain cortex from Tl-weighted magnetic resonance imaging (MRI) head scans. Combined with the expectation maximization (EM) algorithm, and a hybrid of pre- and post-processing techniques, incorporating mathematical morphology and connected component analysis, geodesic active contours are evolved in 3D space to segment the cortex. The robustness and accuracy of our proposed method are validated with both synthetic and real MRI data. Our method outperforms standard techniques including the brain extraction tool (BET) and statistical parametric mapping (SPM) by lowering the misclassification rate, especially when analyzing real MRI data