BP-neural network based-characterization of electrographic magnetohydrodynamic signals in MR

Yurong Xu; Zhifeng Wang; Fillia S Makedon; Justin D Pearlman

doi:10.1109/IEMBS.2004.1403186

BP-neural network based-characterization of electrographic magnetohydrodynamic signals in MR

Conf Proc IEEE Eng Med Biol Soc. 2004:2006:431-3. doi: 10.1109/IEMBS.2004.1403186.

Authors

Yurong Xu¹, Zhifeng Wang, Fillia S Makedon, Justin D Pearlman

Affiliation

¹ Dept. of Comput. Sci., Dartmouth Coll., Hanover, NH, USA.

PMID: 17271704
DOI: 10.1109/IEMBS.2004.1403186

Abstract

Electrocardiographs (ECG) signal collected during magnetic resonance (MR) imaging is affected by signal artifact because magnetic fields produce competing signals, from moving conductors in the large vessels. That is called the magnetohydrodynamic effect, which makes it difficult to recognize ST-T changes from ECG signal collected in a magnetic field (MRI). Resolving that problem is important both for accurate triggering (elimination of false triggers from tall peaked T waves) and for monitoring (identifying if or when patient develops ischemia or myocardial injury). This work describes an algorithm based on neural network that is designed to cancel this artifact for ECG signal acquired during MR imaging.