Automated left ventricle segmentation in 2-D LGE-MRI

Abstract

For electrophysiology procedures, obtaining the information of scar within the left ventricle is very important for diagnosis, therapy planning and patient prognosis. The clinical gold standard to visualize scar is late-gadolinium-enhanced-MRI (LGE-MRI). The viability assessment of the myocardium often requires the prior segmentation of the left ventricle (LV). To overcome this problem, we propose an approach for fully automatic LV segmentation in 2-D LGE-MRI. First, the LV is automatically detected using circular Hough transforms. Second, the blood pool is approximated by applying a morphological active contours approach. The refinement of the endo- and epicardial contours is performed in polar space, considering the edge information and scar distribution. The proposed method was evaluated on 26 clinical LGE-MRI data sets. This comparison resulted in a Dice coefficient of 0.85 ± 0.06 for the endocardium and 0.84 ± 0.06 for the epicardium.