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Proceedings Paper

Non-rigid registration of medical images based on ordinal feature and manifold learning
Author(s): Qi Li; Jin Liu; Bo Zang
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Paper Abstract

With the rapid development of medical imaging technology, medical image research and application has become a research hotspot. This paper offers a solution to non-rigid registration of medical images based on ordinal feature (OF) and manifold learning. The structural features of medical images are extracted by combining ordinal features with local linear embedding (LLE) to improve the precision and speed of the registration algorithm. A physical model based on manifold learning and optimization search is constructed according to the complicated characteristics of non-rigid registration. The experimental results demonstrate the robustness and applicability of the proposed registration scheme.

Paper Details

Date Published: 14 December 2015
PDF: 6 pages
Proc. SPIE 9814, MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing, 98140E (14 December 2015); doi: 10.1117/12.2204937
Show Author Affiliations
Qi Li, Xidian Univ. (China)
Jin Liu, Xidian Univ. (China)
Bo Zang, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 9814:
MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing
Jianguo Liu, Editor(s)

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