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- W2534523861 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." @default.
- W2534523861 created "2016-10-28" @default.
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- W2534523861 date "2005-03-21" @default.
- W2534523861 modified "2023-09-24" @default.
- W2534523861 title "BP-neural network based-characterization of electrographic magnetohydrodynamic signals in MR" @default.
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- W2534523861 doi "https://doi.org/10.1109/iembs.2004.1403186" @default.
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