Deformable vessel-based registration using landmark-guided coherent point drift

Authors:
Yipeng Hu;Erik-Jan Rijkhorst;Richard Manber;David Hawkes;Dean Barratt
Affiliations:
Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Image Computing, University College London, London, UK
Venue:
MIAR'10 Proceedings of the 5th international conference on Medical imaging and augmented reality
Year:
2010

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Abstract

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.