@inproceedings{1e9c2a84f2d04e28aa470caddb6208b9,
title = "Surface-based imaging methods for high-resolution functional magnetic resonance imaging",
abstract = "Functional magnetic resonance imaging (fMRI) has become an exceedingly 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 roughly average through the typically 1.5-4-mm thickness of cerebral cortex. The use of higher spatial resolutions, <1.5-mm sampling, complicates the use of fMRI, as one must now consider activity variations within the depth of the brain. 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. These surfaces provide vertex positions and surface normals, vector references for depth calculations. That information enables 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.",
keywords = "Brain, Laminae, MRI, Neuroimaging, fMRI",
author = "David Ress and Sankari Dhandapani and Sucharit Katyal and Clint Greene and Chandra Bajaj",
year = "2010",
doi = "10.1007/978-3-642-12712-0_12",
language = "English (US)",
isbn = "3642127118",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "130--140",
booktitle = "Computational Modeling of Objects Represented in Images - Second International Symposium, CompIMAGE 2010, Proceedings",
note = "2nd International Symposium on Computational Modeling of Objects Represented in Images, Fundamentals, Methods and Applications, CompIMAGE 2010 ; Conference date: 05-05-2010 Through 07-05-2010",
}