Title :
Automated graph-based analysis and correction of cortical volume topology
Author :
Shattuck, David W. ; Leahy, Richard M.
Author_Institution :
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
The human cerebral cortex is topologically equivalent to a sheet and can be considered topologically spherical if it is closed at the brainstem. Low-level segmentation of magnetic resonance (MR) imagery typically produces cerebral volumes whose tessellations are not topologically spherical. The authors present a novel algorithm that analyzes and constrains the topology of a volumetric object. Graphs are formed that represent the connectivity of voxel segments in the foreground and background of the image. These graphs are analyzed and minimal corrections to the volume are made prior to tessellation. The authors apply the algorithm to a simple test object and to cerebral white matter masks generated by a low-level tissue identification sequence. The authors tessellate the resulting objects using the marching cubes algorithm and verify their topology by computing their Euler characteristics. A key benefit of the algorithm is that it localizes the change to a volume to the specific areas of its topological defects.
Keywords :
biomedical MRI; brain; graphs; image segmentation; medical image processing; Euler characteristics; automated graph-based analysis; brainstem; cerebral volumes; cerebral white matter; cortical volume topology topology; image analysis algorithm; low-level segmentation; magnetic resonance imaging; marching cubes algorithm; medical diagnostic imaging; minimal corrections; simple test object; tessellations; topological correction; topological defects; topologically spherical object; voxel segments; Brain; Cerebral cortex; Electroencephalography; Humans; Image processing; Image segmentation; Magnetic analysis; Magnetic resonance; Signal processing; Topology; Algorithms; Automatic Data Processing; Brain Mapping; Cerebral Cortex; Computer Graphics; Humans; Magnetic Resonance Imaging; Statistics as Topic;
Journal_Title :
Medical Imaging, IEEE Transactions on