Global pdf-based temporal non-local means filtering reveals individual differences in brain connectivity.

GLOBAL PDF-BASED TEMPORAL NON-LOCAL MEANS FILTERING REVEALS INDIVIDUAL DIFFERENCES IN BRAIN CONNECTIVITY.
Proc IEEE Int Symp Biomed Imaging. 2018 Apr;2018:15-19
Authors: Li J, Choi S, Joshi AA, Wisnowski JL, Leahy RM
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.
PMID: 30713593 [PubMed]

Source: Proceedings - International Symposium on Biomedical Imaging - February 5, 2019 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research