I'm trying to automatically detect some medical defined anatomical landmarks in a CT reconstructed volume. Medical doctors use these landmarks to measure some patient specific parameters. I have attempted to use the SIFT feature descriptor, since these anatomical landmarks are kind of "keypoints". This did not work very well since the landmarks are points (or tiny regions) that are in general not "interest points" as defined by SIFT. I have been looking many pattern/template matching algorithms but, when I do not have rotation/translation/scale problems, I find that the extracted features do not differentiate each landmark enough (from the rest of the landmarks and from the rest of the non landmark patches) to train a classifier that performs well enough (at least an 80% of detection accuracy).
Please let me know if I'm not stating the problem clearly enough.
I would really appreciate any advise.
The small x crosses and little squares are over the landmarks I want to detect (I forgot to mention that I have a training set, with the labeled landmarks). The white lines represent the measures taken. These are some slices of different cases (of course, I cannot post the full 3D volume).