Multimedia Tools and Applications

, Volume 70, Issue 3, pp 1585–1615 | Cite as

A modified medical image registration

  • Mei-sen Pan
  • Jian-jun Jiang
  • Qiu-sheng Rong
  • Fen Zhang
  • Hui-can Zhou
  • Fang-yan Nie


Medical image registration is commonly used in clinical diagnosis, treatment, quality assurance, evaluation of curative efficacy and so on. In this paper, the edges of the original reference and floating images are detected by the B-spline gradient operator and then the binarization images are acquired. By computing the binarization image moments, the centroids are obtained. Also, according to the binarization image coordinates, the rotation angles of the reference and floating images are computed respectively, on the foundation of which the initial values for registering the images are produced. When searching the optimal geometric transformation parameters, the modified peak signal-to-noise ratio (MPSNR) is viewed as the similarity metric between the reference and floating images. At the same time, the simplex method is chosen as multi-parameter optimization one. The experimental results show that, this proposed method has a fairly simple implementation, a low computational load, a fast registration and good registration accuracy. It also can effectively avoid trapping in the local optimum and is adapted to both mono-modality and multi-modality image registrations. Also, the improved iterative closest point algorithm based on acquiring the initial values for registration from the least square method (LICP) is introduced. The experiments reveal that the measure acquiring the initial values for registration from image moments and the least square method (LSM) is feasible and resultful strategy.


Image moment Improved PSNR Medical image Image registration Least square method 



This paper was partially supported by the Key Discipline-Leader Foundation of Hunan Provincial Institutions of Higher Education, PRC and supported by Outstanding Young Scientific Research Fund of Hunan Provincial Education Department, PRC(No.09B071).


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Mei-sen Pan
    • 1
  • Jian-jun Jiang
    • 2
  • Qiu-sheng Rong
    • 1
  • Fen Zhang
    • 1
  • Hui-can Zhou
    • 1
  • Fang-yan Nie
    • 1
  1. 1.College of Computer Science and TechnologyHunan University of Arts and ScienceChangdePeople’s Republic of China
  2. 2.Library of Hunan University of Arts and ScienceChangdePeople’s Republic of China

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