Partially adaptive stap for fMRI: A method for detecting brain activation regions in simulation and human data

Lejian Huang; Elizabeth A. Thompson; Scott K. Holland; Vincent Schmithorst; Thomas M. Talavage

doi:10.1109/ISBI.2007.356873

Partially adaptive stap for fMRI: A method for detecting brain activation regions in simulation and human data

Lejian Huang^*, Elizabeth A. Thompson, Scott K. Holland, Vincent Schmithorst, Thomas M. Talavage

^*Corresponding author for this work

Neuroscience

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper introduces three partially adaptive space-time processing (STAP) schemes for analyzing fMRI data. Element space partially adaptive STAP can achieve performance close to that of fully adaptive STAP while greatly decreasing the CPU running time and memory requirements when applied to both synthetic as well as real human brain data. In synthetic analyses, partially adaptive STAP algorithms exhibit better detection characteristics than the traditional cross-correlation method. This is supported by human data in which element space and fully adaptive STAP produce activation maps that closely resemble those of cross-correlation.

Original language	English (US)
Title of host publication	2007 4th IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro - Proceedings
Pages	400-403
Number of pages	4
DOIs	https://doi.org/10.1109/ISBI.2007.356873
State	Published - Nov 27 2007
Event	2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07 - Arlington, VA, United States Duration: Apr 12 2007 → Apr 15 2007

Publication series

Name	2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings

Other

Other	2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
Country/Territory	United States
City	Arlington, VA
Period	4/12/07 → 4/15/07

Keywords

Partially adaptive STAP
Statistical signal processing
fMRI

ASJC Scopus subject areas

Electrical and Electronic Engineering
Medicine(all)

Access to Document

10.1109/ISBI.2007.356873

Cite this

Huang, L., Thompson, E. A., Holland, S. K., Schmithorst, V., & Talavage, T. M. (2007). Partially adaptive stap for fMRI: A method for detecting brain activation regions in simulation and human data. In 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings (pp. 400-403). [4193307] (2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings). https://doi.org/10.1109/ISBI.2007.356873

Huang, Lejian ; Thompson, Elizabeth A. ; Holland, Scott K. et al. / Partially adaptive stap for fMRI : A method for detecting brain activation regions in simulation and human data. 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings. 2007. pp. 400-403 (2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings).

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title = "Partially adaptive stap for fMRI: A method for detecting brain activation regions in simulation and human data",

abstract = "This paper introduces three partially adaptive space-time processing (STAP) schemes for analyzing fMRI data. Element space partially adaptive STAP can achieve performance close to that of fully adaptive STAP while greatly decreasing the CPU running time and memory requirements when applied to both synthetic as well as real human brain data. In synthetic analyses, partially adaptive STAP algorithms exhibit better detection characteristics than the traditional cross-correlation method. This is supported by human data in which element space and fully adaptive STAP produce activation maps that closely resemble those of cross-correlation.",

keywords = "Partially adaptive STAP, Statistical signal processing, fMRI",

author = "Lejian Huang and Thompson, {Elizabeth A.} and Holland, {Scott K.} and Vincent Schmithorst and Talavage, {Thomas M.}",

year = "2007",

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day = "27",

doi = "10.1109/ISBI.2007.356873",

language = "English (US)",

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series = "2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings",

pages = "400--403",

booktitle = "2007 4th IEEE International Symposium on Biomedical Imaging",

note = "2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07 ; Conference date: 12-04-2007 Through 15-04-2007",

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Huang, L, Thompson, EA, Holland, SK, Schmithorst, V & Talavage, TM 2007, Partially adaptive stap for fMRI: A method for detecting brain activation regions in simulation and human data. in 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings., 4193307, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings, pp. 400-403, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07, Arlington, VA, United States, 4/12/07. https://doi.org/10.1109/ISBI.2007.356873

Partially adaptive stap for fMRI: A method for detecting brain activation regions in simulation and human data. / Huang, Lejian; Thompson, Elizabeth A.; Holland, Scott K. et al.
2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings. 2007. p. 400-403 4193307 (2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - This paper introduces three partially adaptive space-time processing (STAP) schemes for analyzing fMRI data. Element space partially adaptive STAP can achieve performance close to that of fully adaptive STAP while greatly decreasing the CPU running time and memory requirements when applied to both synthetic as well as real human brain data. In synthetic analyses, partially adaptive STAP algorithms exhibit better detection characteristics than the traditional cross-correlation method. This is supported by human data in which element space and fully adaptive STAP produce activation maps that closely resemble those of cross-correlation.

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Huang L, Thompson EA, Holland SK, Schmithorst V, Talavage TM. Partially adaptive stap for fMRI: A method for detecting brain activation regions in simulation and human data. In 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings. 2007. p. 400-403. 4193307. (2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings). doi: 10.1109/ISBI.2007.356873

Partially adaptive stap for fMRI: A method for detecting brain activation regions in simulation and human data

Abstract

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Keywords

ASJC Scopus subject areas

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