2. The method of claim 1 further comprising: creating a set of frequently occurring concept labels based on the one or more concept labels detected in the textual reports.
1. A method for automatic ground truth generation of medical image collections, the method comprising: receiving a plurality of imaging studies, wherein each imaging study comprises one or more images and a textual report associated with the one or more images; selecting a key image from each of the plurality of imaging studies; extracting one or more discriminating image features from a region of interest within the key image; processing the textual report associated with the one or more images to detect one or more concept labels; assigning an initial label from the one or more concept labels to the one or more discriminating image features; and learning an association between each of the one or more discriminating image features and the one or more concept labels; wherein learning the association between each of the one or more discriminating image features and the one or more concept labels comprises executing a convex optimization learning algorithm.