A new physics-based deformable model method successfully extracted left ventricular shape and motion from tagged MRI data, allowing quantitative characterization of normal and abnormal hearts.
We develop a new method for analyzing the motion of the left ventricle (LV) of a heart from tagged MRI data. Our technique is based on the development of a new class of physics-based deformable models whose parameters are functions allowing the definition of new parameterized primitives and parameterized deformations. These parameter functions improve the accuracy of shape description through the use of a few intuitive parameters such as functional twisting. Furthermore, these parameters require no complex post-processing in order to be used by a physician. Using a physics-based approach, we convert these geometric models into deformable models that deform due to forces exerted from the datapoints and conform to the given dataset. We present experiments involving the extraction of shape and motion of the LV from MRI-SPAMM data based on a few parameter functions. Furthermore, by plotting the variations over time of the extracted model parameters from normal and abnormal heart data we are able to characterize quantitatively their differences.>
Park et al. (Tue,) conducted a other in Left ventricular motion analysis. Physics-based deformable models for MRI-SPAMM data was evaluated on Extraction of shape and motion of the LV and characterization of differences between normal and abnormal heart data. A new physics-based deformable model method successfully extracted left ventricular shape and motion from tagged MRI data, allowing quantitative characterization of normal and abnormal hearts.
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