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Proceedings Paper

An elastic image registration model based on FEM
Author(s): Kailu Guo; Junhong Sun; Feng Wang
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Paper Abstract

In this paper, a FEM-based model for elastic image registration is proposed for the medical images that containing abnormal region due to pathological changes. Such model is based on uniform triangulation and Bayesian theorem. Firstly, the continuous domain corresponding to the size of the registered images is discreted by applying uniform triangulation. According to the characteristics of the elastic match, the basis function are constructed on the vertices of the every triangles. Next, the pixels of the image that containing pathological changes is classified by using the region growth algorithm. Based on the Bayes theorem, the FEM-based model is then received, and the model is naturally an energy function that respect to the basis function. Therefore, the problem of the image registration can be translated into the problem of finding the minimum value of the energy function. The gradient descent method is used to calculate the value in this article. Finally, the result of the simulated experiment show the effectiveness and accuracy of the addressed model.

Paper Details

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003304 (29 August 2016); doi: 10.1117/12.2244598
Show Author Affiliations
Kailu Guo, Capital Normal Univ. (China)
Junhong Sun, Capital Normal Univ. (China)
Feng Wang, Capital Normal Univ. (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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