Abstract
Quantification of myocardial perfusion from cardiac magnetic resonance (CMR) images relies on manual tracing of myocardial regions of interest (ROIs) and their repositioning frame-by-frame throughout the contrast-enhanced image sequence. Additionally, out-of-plane motion due to patient’s respiration frequently requires that myocardial ROIs to be redrawn.This tedious and potentially inaccurate methodology hinders widespread clinical use of imaging-based quantification of myocardial perfusion.
Highlights
Automated quantification of myocardial perfusion based on segmentation and non-rigid registration of contrast-enhanced cardiac magnetic resonance images
Quantification of myocardial perfusion from cardiac magnetic resonance (CMR) images relies on manual tracing of myocardial regions of interest (ROIs) and their repositioning frame-by-frame throughout the contrast-enhanced image sequence
We developed a technique for automated identification and registration of myocardial ROIs from CMR images as a basis for perfusion quantification
Summary
Quantification of myocardial perfusion from cardiac magnetic resonance (CMR) images relies on manual tracing of myocardial regions of interest (ROIs) and their repositioning frame-by-frame throughout the contrast-enhanced image sequence. Out-of-plane motion due to patient’s respiration frequently requires that myocardial ROIs to be redrawn.This tedious and potentially inaccurate methodology hinders widespread clinical use of imaging-based quantification of myocardial perfusion. Purpose We developed a technique for automated identification and registration of myocardial ROIs from CMR images as a basis for perfusion quantification
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