1. A method for segmenting chambers of a heart in three dimensional images comprising the steps of: receiving a set of three dimensional images of a heart; estimating a position of the heart in the three dimensional images; using Marginal Space Learning (MSL) to constrain searching space to three dimensions; identifying a set of candidate locations in the images; dividing the candidates into positive and negative groups based on their distance from the estimated position of the heart; and training the classifier using the positive and negative candidates to identify a subset of candidates that likely coincide with the location of the heart, wherein said subset of candidates localizes the shape of the heart in the three dimensional images; and identifying boundaries of the chambers of the heart in the localized shape using steerable features.