Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval
Accurate neuroimaging feature extraction is essential for effective content-based management of the large neuroimaging databases, as well as achieving improved diagnosis. In this paper, we presented a multiscale and multi-orientation neuroimaging feature extraction algorithm with degenerative patterns for content-based 3D neuroimaging analysis and retrieval, based on the localized 3D Gabor wavelets. Our proposed approach was evaluated with 209 3D clinical neurological imaging studies and compared with the 3D discrete curvelet transform based method and the 3D spatial grey level co-occurrence matrices based method. The preliminary results suggested that our algorithm could support more reliable 3D neuroimaging retrieval.