1. A method for detecting a 3D anatomical object in a medical image volume, comprising: determining, by a processor, a constrained search range in the medical image volume based on a set of annotated training volumes; detecting position candidates in said constrained search range using a first trained classifier; generating position-orientation hypotheses from said position candidates based on orientation examples in said set of training volumes; detecting position-orientation candidates from said position-orientation hypotheses using a second classifier; generating similarity transformation hypotheses from said position-orientation candidates based on scale examples in said set of training volumes; detecting similarity transformation candidates from said similarity transformation hypotheses using a third trained classifier; and detecting said 3D anatomical object in the medical image volume based on at least one of said similarity transformation candidates.