Improved 3D wavelet-based de-noising of fMRI data

Siddharth Khullar; Andrew M. Michael; Nicolle Correa; Tulay Adali; Stefi A. Baum; Vince D. Calhoun

doi:10.1117/12.878276

15 March 2011 Improved 3D wavelet-based de-noising of fMRI data

Siddharth Khullar, Andrew M. Michael, Nicolle Correa, Tulay Adali, Stefi A. Baum, Vince D. Calhoun

Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 79624P (2011) https://doi.org/10.1117/12.878276
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

Functional MRI (fMRI) data analysis deals with the problem of detecting very weak signals in very noisy data. Smoothing with a Gaussian kernel is often used to decrease noise at the cost of losing spatial specificity. We present a novel wavelet-based 3-D technique to remove noise in fMRI data while preserving the spatial features in the component maps obtained through group independent component analysis (ICA). Each volume is decomposed into eight volumetric sub-bands using a separable 3-D stationary wavelet transform. Each of the detail sub-bands are then treated through the main denoising module. This module facilitates computation of shrinkage factors through a hierarchical framework. It utilizes information iteratively from the sub-band at next higher level to estimate denoised coefficients at the current level. These de-noised sub-bands are then reconstructed back to the spatial domain using an inverse wavelet transform. Finally, the denoised group fMRI data is analyzed using ICA where the data is decomposed in to clusters of functionally correlated voxels (spatial maps) as indicators of task-related neural activity. The proposed method enables the preservation of shape of the actual activation regions associated with the BOLD activity. In addition it is able to achieve high specificity as compared to the conventionally used FWHM (full width half maximum) Gaussian kernels for smoothing fMRI data.

Citation Download Citation

Siddharth Khullar, Andrew M. Michael, Nicolle Correa, Tulay Adali, Stefi A. Baum, and Vince D. Calhoun "Improved 3D wavelet-based de-noising of fMRI data", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79624P (15 March 2011); https://doi.org/10.1117/12.878276

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available