Reference signal extraction from corrupted ECG using wavelet decomposition for MRI sequence triggering: application to small animals

Abstract

Background: Present developments in Nuclear Magnetic Resonance (NMR) imaging techniques strive for improved spatial and temporal resolution performances. However, trying to achieve the shortest gradient rising time with high intensity gradients has its drawbacks: It generates high amplitude noises that get superimposed on the simultaneously recorded electrophysiological signals, needed to synchronize moving organ images. Consequently, new strategies have to be developed for processing these collected signals during Magnetic Resonance Imaging (MRI) examinations. The aim of this work is to extract an efficient reference signal, from an electrocardiogram (ECG) that was contaminated by the NMR artefacts. This may be used for image triggering and/or cardiac rhythm monitoring.

Alterations in human ECG due to the MagnetoHydroDynamic effect: A method for accurate R peak detection in the presence of high MHD artifacts

“…Thus, since gating relies on the R peaks, we can define this frequency band as being our region of interest in which we have all necessary information for trigger production. This concept was exploited in a previous work [11] where we developed a peak detection algorithm based on wavelet sub-band decomposition. It consists in decomposing the ECG signal into multiple scales, then reconstructing the details and keeping only those that contain the maximum of the QRS energy in order to compose a reference signal.…”

Independent component analysis-based artefact reduction: application to the electrocardiogram for improved magnetic resonance imaging triggering

“…Furthermore, this method does not work well for patients with low VCG amplitudes, as in overweight patients for instance. Another MR specific QRS detector was designed using wavelets (Abi-Abdallah 2006), but such a method is not compatible with real-time detection. Moreover, the authors assumed that the gradient artefacts were not in the same frequency range as the QRS, which is generally not the case (Felblinger et al 1999).…”

“…In the magnetic resonance imaging (MRI) field, ECG has been 1382 J Oster et al introduced for patient monitoring and magnetic resonance (MR) sequence synchronization purposes, but the signal quality is severely affected by the MR environment. MR specific signal processing methods have been presented to handle this particular noise (Laudon et al 1998, Fischer et al 1999, Felblinger et al 1999, China et al 2000, Abächerli et al 2005, Abi-Abdallah 2006, Odille et al 2007, Oster et al 2009. Among them, several methods require a connection to the MR system to accurately denoise the ECG, which is a major drawback since access to the MR system is often restricted.…”

Selection of Mother Wavelet Functions for Multi-Channel EEG Signal Analysis during a Working Memory Task

“…Zikov et al [ 43 ] chose “coif3” because its shape resembles that of eye blink artifacts. Andrade et al [ 44 ] used “db5” to remove noise from EMG signals; Andrade et al [ 45 , 46 ] also utilized “db4”, “sym7”, “coif3”, “coif4”, and “coif5” to enhance ECG detection. However, a more precise selection of a MWT basis function remains a challenge because the properties of the WT functions and the characteristic of the signal to be analyzed should be carefully matched.…”