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Adaptive step size LMS for ECG artefact reduction during MR

Abstract : During cardiac MRI, fast switching gradients cause artifacts on the electrocardiogram (ECG), disturbing both triggering and patient monitoring. To cancel this noise, the Least Mean Squares (LMS) algorithm is a simple and efficient method. LMS uses one main parameter, its step size, which influences the quality of artifact reduction. We propose a method using the MR gradient variance to choose this parameter accurately using information about the sequence played by the MR scanner. The proposed method achieved systematically better results than the standard LMS with a 1.5T ECG database.
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https://hal.univ-lorraine.fr/hal-01737180
Contributor : Iadi Ul <>
Submitted on : Monday, March 19, 2018 - 12:08:51 PM
Last modification on : Tuesday, October 13, 2020 - 10:46:05 AM

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  • HAL Id : hal-01737180, version 1

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A Guillou, S Ménétré, G Petitmangin, Jacques Felblinger, Bonnemains Laurent. Adaptive step size LMS for ECG artefact reduction during MR. 2015 Computing in Cardiology Conference (CinC 2015), Sep 2015, Nice, France. pp.761-764. ⟨hal-01737180⟩

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