1. A method for detecting an object in a 2D medical image, comprising: detecting candidates for the object in the 2D medical image using a hierarchical tree-structured array of trained classifiers comprising: a first classifier trained for an object class to detect object candidates in a first search space, wherein the object is a pigtail catheter tip and the first classifier is a global pigtail catheter tip position classifier trained based on all shape variations of pigtail catheter tips in a set of annotated training data to detect pigtail catheter tip position candidates in the 2D image; and a plurality of second classifiers, each trained for a respective one of a plurality of sub-classes of the object class to detect object candidates of the respective one of the plurality of sub-classes in a second search space having a greater dimensionality than the first search space based on the object candidates detected by the first classifier, wherein the plurality of second classifiers comprise: a circular sub-class position-orientation classifier trained based on a circular sub-class of pigtail catheter tips in the training data to detect pigtail catheter tip position-orientation candidates based on the pigtail catheter tip position candidates detected by the global pigtail catheter tip position classifier, and an ellipsoid-line sub-class position-orientation classifier trained based on ellipsoid and line sub-classes of pigtail catheter tips in the training data to detect pigtail catheter tip position-orientation candidates based on the pigtail catheter tip position candidates detected by the global pigtail catheter tip position classifier.