Automatic and adaptive brain morphometry on MR images

Automatic segmentation of brain tissue on magnetic resonance images remains a challenge due to variations in brain shape and size, use of different pulse sequences, overlapping signal intensities, and imaging artifacts. An image analysis system that combines robust image processing techniques with anatomic knowledge was developed to meet this challenge. The system is fast, accurate, and robust to the variability of brain anatomy and imaging conditions and is useful for studying the brain in healthy adults, patients with a shrunken brain due to brain atrophy, and children. With this new thresholding method, the range of the proportion of brain tissue can be determined, thereby making good segmentation possible even in the presence of intrasectional inhomogeneity and noise. The system can adaptively adjust the morphologic processing to break the connection between brain and nonbrain tissue while preserving small brain fragments. It can also segment the white matter and gray matter of the two hemispheres sep...