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Non-rigid Multimodal Image Registration Based on the Expectation-Maximization Algorithm

  • Edgar Arce-Santana
  • Daniel U. Campos-Delgado
  • Flavio Vigueras-Gómez
  • Isnardo Reducindo
  • Aldo R. Mejía-Rodríguez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8333)

Abstract

In this paper, we present a novel methodology for multimodal non-rigid image registration. The proposed approach is formulated by using the Expectation-Maximization (EM) technique in order to estimate a displacement vector field that aligns the images to register. In this approach, the image alignment relies on hidden stochastic random variables which allow to compare the intensity values between images of different modality. The methodology is basically composed of two steps: first, we provide an initial estimation of the the global deformation vector field by using a rigid registration technique based on particle filtering, obtaining, at the same time, an initial estimation of the joint conditional intensity distribution of the registered images; second, we approximate the remaining deformations by applying an iterative EM-technique approach, where at each step, a new estimation of the joint conditional intensity distribution and the displacement vector field are computed. The proposed algorithm was tested with different kinds of medical images; preliminary results show that the methodology is a good alternative for non-rigid multimodal registration.

Keywords

Image Registration Source Image Rigid Registration Displacement Vector Field Image Registration Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Edgar Arce-Santana
    • 1
  • Daniel U. Campos-Delgado
    • 1
  • Flavio Vigueras-Gómez
    • 1
  • Isnardo Reducindo
    • 1
  • Aldo R. Mejía-Rodríguez
    • 1
  1. 1.Facultad de CienciasUniversidad Autónoma de San Luis PotosíSan Luis PotosíMéxico

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