Segmentation of Left Ventricle in Cardiac Cine MRI: An Automatic Image-Driven Method

This study investigates a fully automatic left ventricle segmentation method from cine short axis MR images. Advantages of this method include that it: 1) does not require manually drawn initial contours, trained statistical shape or gray-level appearance model; 2) provides not only endocardial and epicardial contours, but also papillary muscles and trabeculations' contours; 3) introduces a roundness measure that is fast and automatically locates the left ventricle; 4) simplifies the epicardial contour segmentation by mapping the pixels from Cartesian to approximately polar coordinates; and 5) applies a fast Fourier transform to smooth the endocardial and epicardial contours. Quantitative evaluation was performed on 41 subjects. The average perpendicular distance between manually drawn and automatically selected contours over all slices, all studies, and two phases (end-diastole and end-systole) was 1.40 +/- 1.18 mm for endocardial and 1.75 +/- 1.15 mm for epicardial contours. These results indicate a promising method for automatic segmentation of left ventricle for clinical use.