Abstract
In allusion to non-rigid registration of medical images, the paper gives a novel algorithm based on improved Scale Invariant Features Transform (SIFT) feature matching algorithm. First, Harris corner detection algorithm is used in the process of scale invariant feature extraction, so the number of right matching points is increased; with regard to the feature points detected in the scale space, an improved SIFT feature extraction algorithm with global context vector is presented to solve the problem that SIFT descriptors result in a lot of mismatches when an image has many similar regions. On this basis, affine transformation is chosen to implement the non-rigid registration, and weighted mutual information (WMI) measure and Particle Swarm Optimization (PSO) algorithm are also chosen to optimize the registration process. The experimental results show that the method can achieve better registration results than the method based on mutual information.
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Wang, A., Lv, D., Wang, Z., Li, S. (2010). Research on a Novel Medical Image Non-rigid Registration Method Based on Improved SIFT Algorithm. In: Li, K., Jia, L., Sun, X., Fei, M., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science(), vol 6330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15615-1_12
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DOI: https://doi.org/10.1007/978-3-642-15615-1_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15614-4
Online ISBN: 978-3-642-15615-1
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