Objective evaluation of methods to track motion from clinical cardiac-gated tagged MRI without the use of a gold standard

Felipe M. Parages; Thomas S. Denney Jr.; Jovan G. Brankov

doi:10.1117/12.2082228

20 March 2015 Objective evaluation of methods to track motion from clinical cardiac-gated tagged MRI without the use of a gold standard

Felipe M. Parages, Thomas S. Denney Jr., Jovan G. Brankov

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Proceedings Volume 9416, Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment; 941616 (2015) https://doi.org/10.1117/12.2082228
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Cardiac-gated MRI is widely used for the task of measuring parameters related to heart motion. More specifically, gated tagged MRI is the preferred modality to estimate local deformation (strain) and rotational motion (twist) of myocardial tissue. Many methods have been proposed to estimate cardiac motion from gated MRI sequences. However, when dealing with clinical data, evaluation of these methods is problematic due to the absence of gold-standards for cardiac motion. To overcome that, a linear regression scheme known as regression-without-truth (RWT) was proposed in the past. RWT uses priors to model the distribution of true values, thus enabling us to assess image-analysis algorithms without knowledge of the ground-truth. Furthermore, it allows one to rank methods by means of an objective figure-of-merit γ (i.e. precision). In this work we apply RWT to compare the performance of several gated MRI motion-tracking methods (e.g. non-rigid registration, feature based, harmonic phase) at the task of estimating myocardial strain and left-ventricle (LV) twist, from a population of 18 clinical human cardiac-gated tagged MRI studies.

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Felipe M. Parages, Thomas S. Denney Jr., and Jovan G. Brankov "Objective evaluation of methods to track motion from clinical cardiac-gated tagged MRI without the use of a gold standard", Proc. SPIE 9416, Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment, 941616 (20 March 2015); https://doi.org/10.1117/12.2082228

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KEYWORDS

Magnetic resonance imaging

Motion estimation

Heart

Motion models

Gold

Tissues

Error analysis

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