6. The method of claim 1 , wherein said step of 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 comprises: extracting a plurality of features for each detected LV candidate, said features including a first group of features based on geometrical relationships between each detected LV candidate and the other detected LV candidates, a second group of features based on geometrical relationships between each detected LV candidate and the detected apex candidates, and a third group of features based on geometrical relationships between each detected LV candidate and the detected base candidates; and ranking the plurality of LV candidates based on the extracted features using the 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.