Title :
Creating connected representations of cortical gray matter for functional MRI visualization
Author :
Teo, Patrick C. ; Sapiro, Guillermo ; Wandell, Brian A.
Author_Institution :
Dept. of Comput. Sci., Stanford Univ., CA, USA
Abstract :
Describes a system that is being used to segment gray matter from magnetic resonance imaging (MRI) and to create connected cortical representations for functional MRI visualization (fMRI). The method exploits knowledge of the anatomy of the cortex and incorporates structural constraints into the segmentation. First, the white matter and cerebral spinal fluid (CSF) regions in the MR volume are segmented using a novel techniques of posterior anisotropic diffusion. Then, the user selects the cortical white matter component of interest, and its structure is verified by checking for cavities and handles. After this, a connected representation of the gray matter is created by a constrained growing-out from the white matter boundary. Because the connectivity is computed, the segmentation can be used as input to several methods of visualizing the spatial pattern of cortical activity within gray matter. In the authors´ case, the connected representation of gray matter is used to create a flattened representation of the cortex. Then, fMRI measurements are overlaid on the flattened representation, yielding a representation of the volumetric data within a single image. The software is freely available to the research community.
Keywords :
biomedical NMR; brain; image segmentation; medical image processing; activity pattern; anatomical knowledge; cavities; cerebral spinal fluid; connected representations creation; constrained growing-out; cortical gray matter; cortical white matter component; flattened representation; freely available software; functional MRI visualization; handles; magnetic resonance imaging; medical diagnostic imaging; posterior anisotropic diffusion; spatial pattern visualization; structural constraints; volumetric data representation; white matter boundary; Anatomy; Anisotropic magnetoresistance; Data visualization; Humans; Image segmentation; Magnetic resonance imaging; Nerve fibers; Neurons; Neuroscience; Volume measurement; Cerebral Cortex; Computer Simulation; Humans; Magnetic Resonance Imaging;
Journal_Title :
Medical Imaging, IEEE Transactions on