title: Denoising of single-trial matrix representations using 2D nonlinear diffusion filtering.
abstract: In this paper we present a novel application of denoising by means of nonlinear diffusion filters (NDFs). NDFs have been successfully applied for image processing and computer vision areas, particularly in image denoising, smoothing, segmentation, and restoration. We apply two types of NDFs for the denoising of evoked responses in single-trials in a matrix form, the nonlinear isotropic and the anisotropic diffusion filters. We show that by means of NDFs we are able to denoise the evoked potentials resulting in a better extraction of physiologically relevant morphological features over the ongoing experiment. This technique offers the advantage of translation-invariance in comparison to other well-known methods, e.g., wavelet denoising based on maximally decimated filter banks, due to an adaptive diffusion feature. We compare the proposed technique with a wavelet denoising scheme that had been introduced before for evoked responses. It is concluded that NDFs represent a promising and useful approach in the denoising of event related potentials. Novel NDF applications of single-trials of auditory brain responses (ABRs) and the transcranial magnetic stimulation (TMS) evoked electroencephalographic responses denoising are presented in this paper.
authors.affiliation: Computational Diagnostics and Biocybernetics Unit, Saarland University Hospital & Saarland University of Applied Sciences, Building 90.5, D-66421 Homburg/Saar, Germany.
authors.forename: I
authors.initials: I
authors.lastname: Mustaffa
authors.forename: C
authors.initials: C
authors.lastname: Trenado
authors.forename: K
authors.initials: K
authors.lastname: Schwerdtfeger
authors.forename: D J
authors.initials: DJ
authors.lastname: Strauss
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D004058:Diffusion; D004569:Electroencephalography; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated; D012815:Signal Processing, Computer-Assisted; D050781:Transcranial Magnetic Stimulation