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A Novel 3D Correspondence-Less Method for MRI and Paxinos-Watson Atlas of Rat Brain Registration

  • Chao Cai
  • Mingyue Ding
  • Hao Lei
  • Jie Cao
  • Ailing Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4091)

Abstract

In this paper, a novel three-dimensional registration method for Magnetic Resonance Image (MRI) and Paxinos-Watson Atlas of rat brain involving 3D affine transformations is proposed. For the purpose of adapting to a large range of transform parameters in a high registration accuracy, the registration procedure includes two steps: a principle components analysis (PCA) based coarse registration and a Hausdorff distance based fine registration. Both steps are free from the correspondence of the feature points of MRI and Atlas. We implemented this registration method in a rat brain 3D reconstruction and analysis system. Experiments have demonstrated that this two-step method can be successfully applied to registering the low resolution and noise affection MRI with Paxinos-Watson Atlas of rat brain.

Keywords

principle component analysis(PCA) Hausdorff distance image registration 3D reconstruction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chao Cai
    • 1
  • Mingyue Ding
    • 1
  • Hao Lei
    • 2
  • Jie Cao
    • 1
  • Ailing Liu
    • 1
  1. 1.Institute for Pattern Recognition and Artificial Intelligence,State Education Commission Key Lab for Image Processing and Intelligent ControlHuazhong University of Science and TechnologyWuhanChina
  2. 2.National Laboratory of Magnetic Resonance and A. & M. PhysicsWuhan Institute of Physics and Mathematics (WIPM) of the Chinese Academy of Sciences (CAS)WuhanChina

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