Voxel-wise functional connectomics using arterial spin labeling functional magnetic resonance imaging: The role of denoising

Journal article


Liang, Xiaoyun, Connelly, Alan and Calamante, Fernando. (2015) Voxel-wise functional connectomics using arterial spin labeling functional magnetic resonance imaging: The role of denoising. Brain Connectivity. 5(9), pp. 543 - 553. https://doi.org/10.1089/brain.2014.0290
AuthorsLiang, Xiaoyun, Connelly, Alan and Calamante, Fernando
Abstract

The objective of this study was to investigate voxel-wise functional connectomics using arterial spin labeling (ASL) functional magnetic resonance imaging (fMRI). Since ASL signal has an intrinsically low signal-to-noise ratio (SNR), the role of denoising is evaluated; in particular, a novel denoising method, dual-tree complex wavelet transform (DT-CWT) combined with the nonlocal means (NLM) algorithm is implemented and evaluated. Simulations were conducted to evaluate the performance of the proposed method in denoising images and in detecting functional networks from noisy data (including the accuracy and sensitivity of detection). In addition, denoising was applied to in vivo ASL datasets, followed by network analysis using graph theoretical approaches. Efficiencies cost was used to evaluate the performance of denoising in detecting functional networks from in vivo ASL fMRI data. Simulations showed that denoising is effective in detecting voxel-wise functional networks from low SNR data and/or from data with small total number of time points. The capability of denoised voxel-wise functional connectivity analysis was also demonstrated with in vivo data. We concluded that denoising is important for voxel-wise functional connectivity using ASL fMRI and that the proposed DT-CWT-NLM method should be a useful ASL preprocessing step.

Keywordsarterial spin labeling; denoising; dual-tree complex wavelet; network efficiency; nonlocal means; voxel-wise functional connectomics
Year2015
JournalBrain Connectivity
Journal citation5 (9), pp. 543 - 553
PublisherMary Ann Liebert, Inc. Publishers
ISSN2158-0014
Digital Object Identifier (DOI)https://doi.org/10.1089/brain.2014.0290
Scopus EID2-s2.0-84954358937
Page range543 - 553
Research GroupMary MacKillop Institute for Health Research
Place of publicationUnited States of America
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