Literature DB >> 30713593

GLOBAL PDF-BASED TEMPORAL NON-LOCAL MEANS FILTERING REVEALS INDIVIDUAL DIFFERENCES IN BRAIN CONNECTIVITY.

Jian Li1, Soyoung Choi2,1, Anand A Joshi1, Jessica L Wisnowski3, Richard M Leahy1.   

Abstract

Characterizing functional brain connectivity using resting fMRI is challenging due to the relatively small BOLD signal contrast and low SNR. Gaussian filtering tends to undermine the individual differences detected by analysis of BOLD signal by smoothing signals across boundaries of different functional areas. Temporal non-local means (tNLM) filtering denoises fMRI data while preserving spatial structures but the kernel and parameters for tNLM filter need to be chosen carefully in order to achieve optimal results. Global PDF-based tNLM filtering (GPDF) is a new, data-dependent optimized kernel function for tNLM filtering which enables us to perform global filtering with improved noise reduction effects without blurring adjacent functional regions.

Entities:  

Keywords:  connectivity; fMRI; filtering; non-local means; optimization

Year:  2018        PMID： 30713593      PMCID： PMC6354009          DOI： 10.1109/ISBI.2018.8363513

Source DB:  PubMed          Journal:  Proc IEEE Int Symp Biomed Imaging        ISSN： 1945-7928


  11 in total

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  5 in total

1.  Temporal non-local means filtering for studies of intrinsic brain connectivity from individual resting fMRI.

Authors:  Jian Li; Soyoung Choi; Anand A Joshi; Jessica L Wisnowski; Richard M Leahy
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