吉林大学学报(工学版) ›› 2009, Vol. 39 ›› Issue (05): 1390-1394.

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Arithmetic harmonic mean divergence measure for elastic image registration

YANG Jin-bao1, LIU Chang-chun2, HU Shun-bo3   

  1. 1.College of Information Engineering,Qingdao University,Qingdao 266071,China|2.School of Control Science and Engineering, Shandong University, Ji′nan 250061, China|3.Department of Physics, Linyi Normal University, Linyi 276005, China
  • Received:2008-01-21 Online:2009-09-01 Published:2009-09-01

Abstract:

   To solve the problem of feature extraction in image registration, an automatic method to extract landmark points for elastic medical image registration is proposed. First, a new similarity measure, named as arithmetic harmonic mean divergence measure (AHM), is induced. The reference image and floating image are rigidly registered by AHM measure. Then, the two images are divided into uniform blocks. The landmarks in object are extracted by regional rigid registration by maximizing AHM measure between the corresponding subimages. According to corresponding landmarks, the global elastic registration is achieved by bicubic Bspline functions. Experiments on registration of brain Magnetic Resonance (MR) images and Computed Tomography (CT) images show that the proposed method is accurate and fast.

Key words: information processing, elastic registration, arithmeticharmonic mean divergence, mutual information

CLC Number: 

  • TP391
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