Reconstruction of the human cerebral cortex from magnetic resonance images

Reconstructing the geometry of the human cerebral cortex from MR images is an important step in both brain mapping and surgical path planning applicat ions, Difficulties with imaging noise, partial volume averaging, image inte nsity inhomogeneities, convoluted cortical structures, and the requirement to preserve anatomical topology make the development of accurate automated algorithms particularly challenging. In this paper ne address each of these problems and describe a systematic method for obtaining a surface represen tation of the geometric central layer of the human cerebral cortex. Using f uzzy segmentation, an isosurface algorithm, and a deformable surface model, the method reconstructs the entire cortex with the correct topology, inclu ding deep convoluted sulci and gyri. The method is largely automated and it s results are robust to imaging noise, partial volume averaging, and image intensity inhomogeneities. The performance of this method is demonstrated, both qualitatively and quantitatively and the results of its application to sis subjects and one simulated MR brain volume are presented.