Wavelet-based denoising and independent component analysis for improving multi-group inference in fMRI data

Siddharth Khullar, Andrew Michael, Nicolle Correa, Tulay Adali, Stefi Baum, Vince Calhoun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Denoising is amongst the most challenging steps involved in analyzing fMRI data. The conventionally used Gaussian smoothing improves the SNR at the cost of spatial sensitivity and specificity. We briefly describe a 3-D framework for wavelet based fMRI analysis that includes denoising and signal separation followed by a detailed illustration of the benefits and improvements when applied to multi-group (healthy/patient) fMRI studies. We utilize a novel shape metric to highlight the accuracy of the shape of activation regions obtained through different processing frameworks. The proposed algorithm results in higher specificity and increased shape accuracy which in turn is likely to be more sensitive to important differences in the patient and control group.

Original languageEnglish (US)
Title of host publication2011 8th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI'11
Pages456-459
Number of pages4
DOIs
StatePublished - Nov 2 2011
Externally publishedYes
Event2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States
Duration: Mar 30 2011Apr 2 2011

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
CountryUnited States
CityChicago, IL
Period3/30/114/2/11

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Keywords

  • 3-D
  • Denoising
  • Shape metrics
  • Wavelets
  • fMRI

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Khullar, S., Michael, A., Correa, N., Adali, T., Baum, S., & Calhoun, V. (2011). Wavelet-based denoising and independent component analysis for improving multi-group inference in fMRI data. In 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 (pp. 456-459). [5872444] (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2011.5872444