Measurement of morphological biomarkers using highly under-sampled k -space data without image reconstruction: application in left-ventricular end-diastolic volume assessment
Hamied A Haroon 1,2 , Ross Little 1,2 , Kola Babalola 1,2 , Chris Miller 1,2 , Neal Sherratt 1,2 , Barry Whitnall 1,2 , Tim Cootes 1,2 , Chris Taylor 1,2 , Geoff J Parker 1,2 , and Chris Rose 1,2
Centre for Imaging Sciences, The University
of Manchester, Manchester, England, United Kingdom,
Imaging Institute, The University of Manchester,
Manchester, England, United Kingdom
We present a novel method for measuring left-ventricular
end-diastolic volume (EDV) from highly under-sampled
without need for explicit image reconstruction. Using
data (8%), from 31 healthy volunteers, we show that the
method can accurately (r=0.91,
0.001) estimate EDV with a mean bias of just 11 ml. The
ability to parameterize features in the way we describe
allows for much faster, tailored quantitative imaging.
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