UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

Diffusion tensor orientation matching for image registration

Curran, KM; Alexander, DC; (2003) Diffusion tensor orientation matching for image registration. Proceedings of SPIE - The International Society for Optical Engineering , 5032 I pp. 149-156. 10.1117/12.481130.

Full text not available from this repository.


We present a new method to perform registration of DT-MRI (Diffusion Tensor Magnetic Resonance Imaging) data. The goal of image registration is to determine the spatial alignment between multiple images of the same or different subjects, acquired intra or inter-modality. Registration of DT-MRI is more complex than for scalar data because it contains additional directional information. The exploitation of DT-MR data for registration should improve the accuracy of image matching for scalar data because the information in DT-MRI is complementary to that contained in standard MR images and thus provides additional cues for matching, which can be used both to test registration quality and improve it. Moreover, developing techniques for spatial normalisation of DT-MR images allows for cross-population studies to be performed using the whole tensor. The novelty of the proposed approach is that it uses the tensor orientation to calculate the registration transformation. We have quantitatively shown that this new algorithm reconstructs some synthetic transformations more closely than current techniques. However, further analysis of our results is necessary to quantify the advantage of our methods more clearly.

Type: Article
Title: Diffusion tensor orientation matching for image registration
DOI: 10.1117/12.481130
UCL classification: UCL > School of BEAMS
UCL > School of BEAMS > Faculty of Engineering Science
URI: http://discovery.ucl.ac.uk/id/eprint/215853
Downloads since deposit
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item