Minimisation of gradient artefacts in cardiac-MRI-gating using adaptive interference cancellation filter with synthesised reference

Park, H.D.; Cho, S.P.; Lee, K.J.; Park, Y.C.

doi:10.1049/el:20070760

Cited by 1 publication

(8 citation statements)

References 3 publications

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“…R was estimated using unbiased auto-correlation of the input. The values of l obtained in this way were in accordance to those used in previous works [1,23]. Performances of ANC are also affected by the order of the filter N [11].…”

Section: Adaptive Noise Cancellingsupporting

confidence: 87%

“…As suggested by a few studies [3,9,[19][20][21][22][23] ANC alone can be insufficient to obtain good artefact suppression. In the present study, ECG was filtered using a low-pass filter (LPF).…”

Section: Pre-processingmentioning

confidence: 97%

“…A number of approaches have been proposed for gradient artefact reduction [1,3,5,6,9,17,[19][20][21][22][23]27]. Simple low-pass filtering can suppress important information from the ECG [6].…”

Section: Introductionmentioning

confidence: 99%

“…Simple low-pass filtering can suppress important information from the ECG [6]. In alternative, an adaptive filtering approach has been used [1,3,23]. Adaptive Noise Cancelling (ANC) is a well-known technique, used in many biomedical contexts, requiring the acquisition of a signal correlated to the interference to be cancelled (see for example [24,32]).…”

Section: Introductionmentioning

confidence: 99%

“…It is worth to mention that ANC is widely used in other applications involving removal of gradient-induced artefacts such as processing of EEG signals simultaneously recorded during fMRI [3,9,[19][20][21][22][23]27].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Adaptive removal of gradients-induced artefacts on ECG in MRI: a performance analysis of RLS filtering

Sansone

Mirarchi

Bracale

2010

Med Biol Eng Comput

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One of the main vital signs used in patient monitoring during Magnetic Resonance Imaging (MRI) is Electro-Cardio-Gram (ECG). Unfortunately, magnetic fields gradients induce artefacts which severely affect ECG quality. Adaptive Noise Cancelling (ANC) is one of the preferred techniques for artefact removal. ANC involves the adaptive estimation of the impulse response of the system constituted by the MRI equipment, the patient and the ECG recording device. Least Mean Square (LMS) adaptive filtering has been traditionally employed because of its simplicity: anyway, it requires the choice of a step-size parameter, whose proper value for the specific application must be estimated case by case: an improper choice could yield slow convergence and unsatisfactory behaviour. Recursive Least Square (RLS) algorithm has, potentially, faster convergence while not requiring any parameter. As far as the authors' knowledge, there is no systematic analysis of performances of RLS in this scenario. In this study we evaluated the performance of RLS for adaptive removal of artefacts induced by magnetic field gradients on ECG in MRI, in terms of efficacy of suppression. Tests have been made on real signals, acquired via an expressly developed system. A comparison with LMS was made on the basis of opportune performance indices. Results indicate that RLS is superior to LMS in several respects.

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Section: Adaptive Noise Cancellingsupporting

confidence: 87%