• Zhong Xue, Dinggang Shen, and Christos Davatzikos.
• Section of Biomedical Image Analysis, Department of Radiology School of Medicine, University of Pennsylvania, 3600 Market ST Suite 380, Philadelphia, PA 19104, USA. zhong.xue@uphs.upenn.edu
• IEEE Trans Med Imaging. 2004 Oct 1; 23 (10): 1276-91.

AbstractFinding point correspondence in anatomical images is a key step in shape analysis and deformable registration. This paper proposes an automatic correspondence detection algorithm for intramodality MR brain images of different subjects using wavelet-based attribute vectors (WAVs) defined on every image voxel. The attribute vector (AV) is extracted from the wavelet subimages and reflects the image structure in a large neighborhood around the respective voxel in a multiscale fashion. It plays the role of a morphological signature for each voxel, and our goal is, therefore, to make it distinctive of the respective voxel. Correspondence is then determined from similarities of AVs. By incorporating the prior knowledge of the spatial relationship among voxels, the ability of the proposed algorithm to find anatomical correspondence is further improved. Experiments with MR images of human brains show that the algorithm performs similarly to experts, even for complex cortical structures.

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