1. A method for automatic recognition of one or more surface features in 3-D volumetric image data, the method comprising: obtaining 3-D volumetric image data from a computed tomography apparatus; extracting a triangulated mesh surface representation from said 3-D volumetric image data, wherein each vertex p i of said mesh has a corresponding set {t i,j } of adjacent triangles of said mesh, wherein each triangle t i,j has a region r i,j closer to vertex p i than to any other vertex of t i,j , wherein each region r i,j has area R i,j , and wherein a sum of R i,j over all triangles adjacent to said vertex p i is given by R i ; constructing an initial shape operator at each vertex of said triangulated mesh; smoothing said initial shape operator according to an iterative weighted averaging of shape operators at vertices of said triangulated mesh to provide a smoothed shape operator; calculating principal curvatures k 1 (p i ) and k 2 (p i ) at each vertex p i of said mesh from said smoothed shape operator, wherein k 1 (p i )≧k 2 (p i ); selecting one or two feature types of interest from the group consisting of local minimum of surface elevation and local maximum of surface elevation; marking each vertex having principal curvatures consistent with said selected feature types according to feature type; clustering vertices marked as having the same feature type by adjacency on said triangulated mesh to provide a set of candidate patches; computing a feature score for each of said candidate patches; providing said feature scores as output.