We 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 LV shape, smoothness, and connectivity into the compatibility coefficients of a relaxation labeling algorithm. This surface detection method was applied to gated 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 MR 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.
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering