1. A method for left ventricle (LV) detection in a 2D magnetic resonance imaging (MRI) image, comprising: detecting a plurality of LV candidates in the 2D MRI image; detecting a plurality of apex candidates in the 2D MRI image; detecting a plurality of base candidates in the 2D MRI image; and selecting one of the plurality LV candidates by ranking the plurality of LV candidates based on geometrical relationships between each detected LV candidate and the other detected LV candidates, between each detected LV candidate and the detected apex candidates, and between each detected LV candidate and the detected base candidates using a trained ranking model.
1. A method for left ventricle (LV) detection in a 2D magnetic resonance imaging (MRI) image, comprising: detecting a plurality of LV candidates in the 2D MRI image; detecting a plurality of apex candidates in the 2D MRI image; detecting a plurality of base candidates in the 2D MRI image; and selecting one of the plurality LV candidates by ranking the plurality of LV candidates based on geometrical relationships between each detected LV candidate and the other detected LV candidates, between each detected LV candidate and the detected apex candidates, and between each detected LV candidate and the detected base candidates using a trained ranking model. 10. The method of claim 1 , wherein the trained ranking model is trained based on geometrical relationships between LV candidates, apex candidates, and base candidates detected in annotated training data.