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

Julien Oster1,2, Olivier Pietquin1,2,3, Roger Abächerli4, Michel Kraemer5 and Jacques Felblinger1,2

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Electrocardiogram (ECG) is required during magnetic resonance (MR) examination for monitoring patients under anaesthesia or with heart diseases and for synchronizing image acquisition with heart activity (triggering). Accurate and fast QRS detection is therefore desirable, but this task is complicated by artefacts related to the complex MR environment (high magnetic field, radio-frequency pulses and fast switching magnetic gradients). Specific signal processing has been proposed, whether using specific MR QRS detectors or ECG denoising methods. Most state-of-the-art techniques use a connection to the MR system for achieving their task, which is a major drawback since access to the MR system is often restricted. This paper introduces a new method for on-line ECG signal enhancement, called ICARE, which takes advantage of using multi-lead ECG and does not require any connection to the MR system. It is based on independent component analysis (ICA) and applied in real time. This algorithm yields accurate QRS detection for efficient triggering.


PACS

87.85.Ng Biological signal processing

87.61.Tg Clinical applications

02.70.Rr General statistical methods

87.19.Hh Cardiac dynamics

87.19.R- Mechanical and electrical properties of tissues and organs

87.19.X- Diseases

Subjects

Computational physics

Biological physics

Medical physics

Dates

Issue 12 (December 2009)

Received 16 June 2009, accepted for publication 12 October 2009

Published 4 November 2009



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