1. A method for classifying regions of interest within a medical image, comprising the steps of: training a classifier on a set of medical image training data, which training data includes segmented regions where a clinical ground truth classifying the segmented regions is known; acquiring non-training medical image data for investigation; generating an initial segmentation for a region of interest of the medical image; generating a plurality of candidate segmentations based on the initial segmentation; comparing the initial and the plurality of candidate segmentations with each other; selecting a best segmentation from a set of segmentations including the initial and the plurality of candidate segmentations based on the comparisons, where the selected best segmentation is used to train the classifier; processing the segmented regions to extract a full feature set for each of the segmented regions; and classifying the regions of interest using the full feature set; wherein, the step of training includes using a recommender to realize a stable segmentation.