Research on a novel medical image non-rigid registration method based on improved SIFT algorithm

Authors:
Anna Wang;Dan Lv;Zhe Wang;Shiyao Li
Affiliations:
College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China
Venue:
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Year:
2010

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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.