A model-based four-dimensional left ventricular surface detector.
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Abstract
The authors have developed a general model-based surface detector for finding the four-dimensional (three spatial dimensions plus time) endocardial and epicardial left ventricular boundaries. The model encoded left ventricular (LV) shape, smoothness, and connectivity into the compatibility coefficients of a relaxation labeling algorithm. This surface detection method was applied to gated single photon emission computed tomography (SPECT) perfusion images, tomographic radionuclide ventriculograms, and cardiac rotation magnetic resonance images. Its accuracy was investigated using actual patient data. Global left ventricular volumes correlated well, with a maximum correlation coefficient of 0.98 for magnetic resonance imaging (MRI) endocardial surfaces and a minimum of 0.88 for SPECT epicardial surfaces. The average absolute errors of edge detection were 6.4, 5.6. and 4.6 mm for tomographic radionuclide ventriculograms, gated perfusion SPECT, and magnetic resonance images, respectively.