1. A method for classifying features in a digital medical image, said method comprising the steps of: providing a plurality of feature points in an n-dimensional space, wherein said feature points have been extracted from a digital medical image, wherein each feature point is a member of one of two sets; determining an approximate classifying plane that separates feature points in a first of the two sets from feature points in a second of the two sets; transforming the classifying plane wherein a normal vector to said transformed classifying plane has positive coefficients and a feature domain for one or more feature points of one of said two sets is a unit hypercube in a transformed space having n axes; obtaining an upper bound along each of the n-axes of the unit hypercube; inversely transforming said upper bound to obtain a new rule containing one or more feature points of said one of said two sets; and removing the feature points contained by said new rule from said one of two sets.