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14 December 2015Non-rigid registration of medical images based on ordinal feature and manifold learning
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.
Qi Li,Jin Liu, andBo Zang
"Non-rigid registration of medical images based on ordinal feature and manifold learning", Proc. SPIE 9814, MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing, 98140E (14 December 2015); https://doi.org/10.1117/12.2204937
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Qi Li, Jin Liu, Bo Zang, "Non-rigid registration of medical images based on ordinal feature and manifold learning," Proc. SPIE 9814, MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing, 98140E (14 December 2015); https://doi.org/10.1117/12.2204937