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Abstract #4489

Data-driven dynamic coil-bias correction for segmented myocardial perfusion images.

Roman Wesolowski 1,2 , Eva Sammut 2 , Niloufar Zarinabad Nooralipour 2 , Eike Nagel 2 , and Amedeo Chiribiri 2

1 University of Birmingham, Birmingham, West Midlands, United Kingdom, 2 King's College London, London, United Kingdom

Coil-bias most persistently contaminates cardiac magnetic resonance (CMR) imaging despite the vendors efforts in reducing its effects. Due to the hearts shape and its oblique position in reference to the coils receiving element, perfusion abnormalities can often be disguised in the areas highly affected by this effect, which can reduce CMRs diagnostic capabilities. Although proton density-based solutions have been in practice, we propose a data-driven dynamic coil-bias correction (DCBC) algorithm for segmented myocardial perfusion. DCBC does not require additional scans and can be applied retrospectively. We show that it significantly reduces the effect of coil-bias, superseding proton density-based technique.

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