  Quantitative myocardial perfusion mapping has advantages over qualitative
assessment, including the ability to detect global flow reduction. However, it
is not clinically available and remains as a research tool. Building upon the
previously described imaging sequence, this paper presents algorithm and
implementation of an automated solution for inline perfusion flow mapping with
step by step performance characterization.
  An inline perfusion flow mapping workflow is proposed and demonstrated on
normal volunteers. Initial evaluation demonstrates the fully automated proposed
solution for the respiratory motion correction, AIF LV mask detection and
pixel-wise mapping, from free-breathing myocardial perfusion imaging.
