Surface-based analysis methods for high-resolution functional magnetic resonance imaging.
Surface-based analysis methods for high-resolution functional magnetic resonance imaging.
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DOI：
10.1016/j.gmod.2010.11.002
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发表时间：
2011-11
期刊：
影响因子：
1.7
通讯作者：
Ress D
中科院分区：
文献类型：
--
作者：
Khan R;Zhang Q;Darayan S;Dhandapani S;Katyal S;Greene C;Bajaj C;Ress D
Functional magnetic resonance imaging (fMRI) has become a popular technique for studies of human brain activity. Typically, fMRI is performed with >3-mm sampling, so that the imaging data can be regarded as two-dimensional samples that average through the 1.5—4-mm thickness of cerebral cortex. The increasing use of higher spatial resolutions, <1.5-mm sampling, complicates the analysis of fMRI, as one must now consider activity variations within the depth of the brain tissue. We present a set of surface-based methods to exploit the use of high-resolution fMRI for depth analysis. These methods utilize white-matter segmentations coupled with deformable-surface algorithms to create a smooth surface representation at the gray-white interface and pial membrane. These surfaces provide vertex positions and normals for depth calculations, enabling averaging schemes that can increase contrast-to-noise ratio, as well as permitting the direct analysis of depth profiles of functional activity in the human brain.
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