Title :
Reconstruction of the human cerebral cortex from magnetic resonance images
Author :
Xu, Chenyang ; Pham, Dzung L. ; Rettmann, Maryam E. ; Yu, Daphne N. ; Prince, Jerry L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA
fDate :
6/1/1999 12:00:00 AM
Abstract :
Reconstructing the geometry of the human cerebral cortex from MR images is an important step in both brain mapping and surgical path planning applications. Difficulties with imaging noise, partial volume averaging, image intensity inhomogeneities, convoluted cortical structures, and the requirement to preserve anatomical topology make the development of accurate automated algorithms particularly challenging. Here the authors address each of these problems and describe a systematic method for obtaining a surface representation of the geometric central layer of the human cerebral cortex. Using fuzzy segmentation, an isosurface algorithm, and a deformable surface model, the method reconstructs the entire cortex with the correct topology, including deep convoluted sulci and gyri. The method is largely automated and its 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 six subjects and one simulated MR brain volume are presented.
Keywords :
biomedical MRI; brain; image reconstruction; image segmentation; medical image processing; MR images; MRI; accurate automated algorithms; deep convoluted sulci; deformable surface model; fuzzy segmentation; geometry reconstruction; gyri; human cerebral cortex reconstruction; image intensity inhomogeneities; imaging noise; isosurface algorithm; medical diagnostic imaging; partial volume averaging; simulated MR brain volume; Brain mapping; Brain modeling; Cerebral cortex; Geometry; Humans; Image reconstruction; Magnetic resonance; Surface reconstruction; Surgery; Topology; Algorithms; Cerebral Cortex; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging;
Journal_Title :
Medical Imaging, IEEE Transactions on