Perelman School of Medicine at the University of Pennsylvania

Section for Biomedical Image Analysis (SBIA)

participating with CBICA

DTI-DROID: Deformable Registration using Orientation and Intensity Descriptors

Geometry and orientation features are integrated into a hierarchical matching framework. The geometric feature is derived from the structural geometry of diffusion and characterizes the shape of the tensor in terms of prolateness, oblateness, and sphericity of the tensor. Local spatial distributions of the prolate, oblate, and spherical geometry are used to create a geometric feature for matching. The orientation feature improves the matching of the WM fiber tracts by taking into account the statistical information of underlying fiber orientations. These features are incorporated into a hierarchical deformable registration framework. Extensive experiments on simulated and real brain DT data establish the superiority of this algorithm for deformable matching of diffusion tensors, thereby aiding in atlas creation. The robustness of the method makes it potentially useful for group-based analysis of DT images acquired in large studies to identify disease-induced and developmental changes.

Center: Average of human (top) and mouse (bottom) spatially normalized to the template on the left. Sharpness of the average map indicates good registration. The edge maps extracted from the average of the spatially normalized subjects is overlaid on the template (on the right)


To Download please visit our DTI-DROID NITRC page



  • Christos Davatzikos
  • Efsthathios Kanterakis
  • Luke Bloy
  • Ragini Verma
  • Yang Li



  1. Jinzhong Yang, Dinggang Shen, Chandan Misra, Xiaoying Wu, Susan Resnick, Christos Davatzikos, Ragini Verma: "Spatial Normalization of Diffusion Tensor Images Based on Anisotropic Segmentation” International SPIE Medical Imaging, 2008
  2. Jinzhong Yang, Dinggang Shen, Christos Davatzikos, Ragini Verma: "Diffusion Tensor Image Registration Using Tensor Geometry and Orientation Features” International SMICCAI, 2008
  3. Ragini Verma, Feby Abraham, George Biros and Christos Davatzikos: "Landmark guided spatial normalization of Diffusion Tensor Images in the presence of large deformations. ISMRM, Seattle (2nd Prize in Best Poster Awards), May 2006.
  4. Ragini Verma, Feby Abraham, George Biros and Christos Davatzikos: "Correspondence Detection in Diffusion Tensor Images" International Symposium on Biomedical Imaging (ISBI) April 2006.
  5. Ragini Verma, Christos Davatzikos: "Matching and smoothing of diffusion tensor images using oriented Gabor morphological signatures” ISMRM Workshop on methods for quantitative diffusion of human brain, Canada, March 2005.
  6. Ragini Verma, Christos Davatzikos: "Matching of Diffusion Tensor Images Using Gabor Features",Proceedings of the IEEE International Symposium on Biomedical Imaging, p. 396-399, Arlington, Va., 15-18 April 2004.
  7. Ragini Verma and Christos Davatzikos: "Matching of Diffusion Tensor Images using Gabor Features” International Symposium on Biomedical Imaging (ISBI) Page: 396-399, April 2004.
  8. Dongrong Xu, Susumu Mori, Dinggang Shen, Peter C. M. van Zijl, Christos Davatzikos, "Spatial Normalization of Diffusion Tensor Fields", Magnetic Resonance in Medicine, 50(1):175-182 Jul 2003.
  9. Dongrong XU, Susumu Mori, Meiyappan Solaiyappan, Peter C. M. van Zijl, Christos Davatzikos, "A Framework for Callosal Fiber Distribution Analysis", Neuroimage, Vol.14, December 1, 2002, pp.1361-1369.
  10. Dongrong Xu, Susumu Mori,Dinggang Shen, Christos Davatzikos, "Statistically-based Reorientation of Diffusion Tensor Fields",IEEE International Symposium on Biomedical Imaging, Washington, D.C. 7-10 July 2002.