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
University of Birmingham, Birmingham, West
Midlands, United Kingdom,
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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