Nowadays magnetic resonance images (MRI) are being used to calculate important clinical parameters suchas ejection fraction (EF), left ventricle myocardium mass (MM), and stroke volume (SV) which are crucial toestimate the cardiac function, surgical planning and create patient-specific heart models, therefore for quantifyingaccurately these parameters it is also necessary a good delimitation of cardiac structures. The proposed approachpresents an automatic segmentation of the left ventricle (LV) and basically is composed by three steps: first, heartstructure localization with template matching technique in coronal and sagittal view that is used to restrict axialanalysis. Second, ellipsoidal approximation using the axial projection of previous coarse segmentation. Third, aconventional snake algorithm is performed to refine external myocardium boundaries in axial view. The strategywas evaluated using 100 cardiac MRI volumes provided by the ACDC 2017 MICCAI challenge which is composedof 4 different heart diseases, the strategy had an average Dice Score of 0:79.
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