@InProceedings{Supelec472,
author = {Julien Oster and Olivier Pietquin and Roger Abächerli and Michel Kraemer and Jacques Felblinger},
title = {{A Specific QRS Detector for Electrocardiography during MRI: Using Waveltets and Local Regularity Characterization}},
year = {2009},
booktitle = {{Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2009)}},
pages = {341-344},
month = {April},
address = {Taipei (Taiwan)},
url = {http://doi.ieeecomputersociety.org/10.1109/ICASSP.2009.4959590},
doi = {10.1109/ICASSP.2009.4959590},
abstract = {Automatic Electrocardiogram (ECG) analysis, especially
QRS detection, is still a challenging task. This is even more
the case when the ECG is acquired during Magnetic Resonance
(MR) examination. The MR environment highly
distorts ECG, with Hall Effect, due to the important magnetic
static field, and artifacts, due to fast switching magnetic
field gradients. Detection of the QRS complexes is then
affected.
In this paper, a new specific MR QRS detector is
presented. This method is based on the modulus maximum
lines and on the Lipschitz exponent estimation they offer.
The use of this regularity characterization permits to
distinguish
between QRS complexes and MR artifacts. This
detector outperforms existing algorithms with almost 99%
sensitivity and positive prediction value.}
}