1. A method of detecting breast masses and calcifications in digitized images, comprising the steps of: providing a plurality of 2-dimensional (2D) digital X-ray projectional breast images acquired from different viewing angles, each said X-ray projectional image comprising a set of intensities on a 2D grid of pixels; extracting candidate lesions and 2D features from said 2D projectional images; computing spicularity characteristics of said candidate lesions, said characteristics including, but not limited to, location, periodicity, and amplitude; applying machine learning algorithms to said candidate lesions to predict a probability of malignancy of said lesion, wherein said learning algorithms have been trained on a training set containing known examples of the features for lesions identified by a physician; receiving from said learning algorithm a probability map of detections for each breast image, said detections comprising associating pixels with a probability of being associated with a malignancy; creating a synthetic 2D slice for each X-ray image wherein malignant regions are indicated by ellipses on a non-malignant background; and constructing a synthetic 3-dimensional (3D) image volume from said 2D synthetic slices.