Left ventricle segmentation in cardiac MRI using data-driven priors and temporal correlations

1. Prior extraction We first generate priors for the LV endocardium and epicardium respectively by extracting corner points inside the LV cavity (Fig. 1b) and the scale-invariant edges (Fig. 1d). For endocardium, the probabilistic map is obtained by kernel density estimation (Fig. 1c); for epicardium, the probabilistic map is obtained by measuring the likelihood of the extracted edges being on the true epicardial boundary (Fig. 1f). 2. Temporal correlation Instead of segmenting each image independently, we incorporate the temporal correlation among frames. Given one reference frame with reliable segmentation, the myocardial contours in the reference frame are propagated to other frames in the same sequence by non-rigid registration. Based on registration error, we then generate a confidence map for each frame, indicating the reliability of the propagated contours.