Chauvin, L., Kumar, K., Wachinger, C., Vangel, M., de Guise, J., Desrosiers, C., Wells, W., Toews, M. and Alzheimer’s Disease Neuroimaging Initiative, 2020. Neuroimage signature from salient keypoints is highly specific to individuals and shared by close relatives. NeuroImage, 204, p.116208.

featExtract is the program used to extract SIFT-Ranked [1] features from images. It accepts nifti images (.nii, .hdr, .nii.gz) as input, and output a list of keypoints and their descriptors.

Volumetric local feature extraction v1.1
Usage: featExtract [options] <input image> <output features>
      <input image>: nifti (.nii,.hdr,.nii.gz).
      <output features>: output file with features.

The program will output a .key file (with the same name as the input file), containing a list of features, with their coordinates, scale, orientation, and descriptor.

featMatchMultiple is the program, based on FLANN library [2], used to match features.

Volumetric Feature matching v1.1
Usage: featMatchMultiple [options] -f <input filelist>
      <input filelist>: Text file containing the list of .key files (from featExtract). 1 key file per line.

The program will output different files:

https://central.xnat.org/data/projects/SIFTFeatures

[1] Toews, Matthew, and William Wells. "Sift-rank: Ordinal description for invariant feature correspondence." 2009 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2009.
[2] Muja, Marius, and David G. Lowe. "Scalable nearest neighbor algorithms for high dimensional data." IEEE transactions on pattern analysis and machine intelligence 36.11 (2014): 2227-2240.

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