Automatic Localization and Segmentation of the Ventricles in Magnetic Resonance Images

Automatic localization and segmentation of the ventricles in magnetic resonance (MR) images is important for clinical applications. In this paper, we propose a new ventricle localization method based on slope difference distribution (SDD) clustering and threshold selection to calculate the positions of the left ventricle (LV) and the right ventricle (RV) automatically. Then, we utilize the SDD threshold selection to segment the LV and the RV in the automatically localized region of interest (ROI). To calculate the optimal threshold, we propose a coarse-to-fine SDD threshold selection method. Experimental results verified that both the proposed automatic ventricle localization method and the proposed coarse-to-fine SDD threshold selection method are more robust than state of the art methods.