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2008
Conference Paper
Titel
Hierarchical matching of anatomical trees for medical image registration
Abstract
Today, tomographic images are used in medical applications more and more. To support physicians in diagnosis and treatment, a registration of two images taken at different points in time or under different conditions is needed. As the structure of the vessel or airway trees is relatively stable between two image acquisitions, they provide a good basis for the automatic determination of landmarks. In this work, a hierarchical tree search algorithm is proposed, which efficiently computes a matching between branchpoints of anatomical trees, which can be used as landmarks for an elastic registration. The algorithm is designed to be general and robust in order to be applicable to a variety of different datasets, which are acquired by different sensors or under different conditions. The validation of the algorithm against manually created ground truth data leads to a 80.9% rate of correctly matched branchpoints. Allowing a tolerance of 5 mm, the rate increases to 89.9%. The r untime for 50-700 vertices is about 1-45 seconds.