Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

Registration of brain structures should bring anatomically equivalent areas into correspondence which is usually done using information from structural MRI modalities. Correspondence can be improved by using other image modalities that provide complementary data. In this paper we propose and evaluate two novel surface registration algorithms which improve within-surface correspondence in brain structures. Both approaches use a white-matter tract similarity function (derived from probabilistic tractography) to match areas of similar connectivity patterns. The two methods differ in the way the deformation field is calculated and in how the multi-scale registration framework is implemented. We validated both algorithms using artificial and real image examples, in both cases showing high registration consistency and the ability to find differences in thalamic sub-structures between Alzheimer's disease and control subjects. The results suggest differences in thalamic connectivity predominantly in the medial dorsal parts of the left thalamus.

Original publication




Conference paper

Publication Date





705 - 712


Centre for Functional MRI of the Brain (FMRIB), University of Oxford.


Thalamus, Nerve Fibers, Myelinated, Humans, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Image Enhancement, Subtraction Technique, Sensitivity and Specificity, Reproducibility of Results, Algorithms, Artificial Intelligence, Signal Processing, Computer-Assisted, Pattern Recognition, Automated, Diffusion Tensor Imaging