Automatic, non-rigid registration of blood vessels (and other tubular structures) within a timescale suitable for use in image-guided surgical applications remains a significant challenge. We describe a novel approach to this problem in which an extension to the coherent point drift (CPD) algorithm is developed to enable landmarks, such as vessel bifurcations, to improve the registration accuracy and speed of execution. The new method - referred to as landmark-guided CPD (LGCPD) - is validated using vessels extracted from brain MRA and liver MR images, and is shown to be robust to missing vessel segments and noise, commonly encountered in realworld applications. © 2010 Springer-Verlag.
CITATION STYLE
Hu, Y., Rijkhorst, E. J., Manber, R., Hawkes, D., & Barratt, D. (2010). Deformable vessel-based registration using landmark-guided coherent point drift. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6326 LNCS, pp. 60–69). https://doi.org/10.1007/978-3-642-15699-1_7
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