1. A computer implemented method for directed machine learning comprising: receiving features including intensity data and location data of an image; condensing the intensity data and the location data into a feature vector; processing the feature vector by a plurality of classifiers, each classifier trained for a respective trained class among a plurality of classes; outputting, from each classifier, a probability of the feature vector belong to the respective trained class; and assigning the feature vector a label according to the probabilities of the classifiers, wherein the assignment produces a segmentation of the image.