of size 31 u00d7 31 u00d7 31 voxels which is shown by the dotted lines centered at the sample location the detection result is a small blob of voxels around the true center location 606 the best 400 locations are kept for further evaluation while the rest are discarded an evaluation of this level indicated that all the true center locations are among the 400 candidate locations the method reduces the search space of location from about 50 u00d7 50 u00d7 60 150 000 to 400 which is a reduction in magnitude of more than 300 the second classifier works in the 6 dimensional space of locations and orientations x u03b8 this space is limited to values x u03b8 for which the location x is among the 400 candidates obtained by the location detector and therefore this 6 dimensional space has already been made more than 300 times smaller fig7 is a functional block diagram of the method in which orientations for the locations are found the locations for which the orientations are to be found are determined by the center detection method which results in a cluster of detected centers 702 the lv orientation detection uses 3d curvature features to detect orientations 704 each feature is computed as a specific voxel location inside a box of size 24 u00d7 24 u00d7 24 voxels translated and rotated by the sample 39 s position and orientation inside this box the locations are organized on a 9 u00d7 9 u00d7 9 lattice so there are 729.