Robust point matching method for multimodal retinal image registration

2015 ◽  
Vol 19 ◽  
pp. 68-76 ◽  
Author(s):  
Gang Wang ◽  
Zhicheng Wang ◽  
Yufei Chen ◽  
Weidong Zhao
Keyword(s):  
Image Registration ◽  
Retinal Image ◽  
Matching Method ◽  
Point Matching

Retinal Image Registration Based on Robust Non-Rigid Point Matching Method

2018 ◽  
Vol 8 (2) ◽  
pp. 240-249 ◽  
Author(s):  
Haolin Tang ◽  
Anning Pan ◽  
Yang Yang ◽  
Kun Yang ◽  
Yi Luo ◽  
...  
Keyword(s):  
Image Registration ◽  
Retinal Image ◽  
Matching Method ◽  
Point Matching

Multi-Modal Medical Image Registration of by Combining Improved Mean Shift and RPM

2012 ◽  
Vol 239-240 ◽  
pp. 1472-1475
Author(s):  
Dan Ai ◽  
Jing Li Shi ◽  
Jun Jun Cao ◽  
Hong Yan Zhong
Keyword(s):  
Image Registration ◽  
Medical Image ◽  
Mean Shift ◽  
Decisive Role ◽  
Experimental Results ◽  
Medical Image Registration ◽  
Image Content ◽  
Point Matching ◽  
Target Mode ◽  
Convergence Process

Landmark correspondence plays a decisive role in the landmark-based multi-modality image registration. We combine RPM (Robust Point Matching) and improved Mean Shift to estimate the correspondence of landmarks in images. We improve the target mode and bandwidth used in Mean Shift, and we also perform RPM to estimate the initial landmark correspondence. Next, we use improved Mean Shift to adjust corresponding relations between points. Our method is benefit to make corresponding relations between points more accurate and impels the convergence process of RPM to be related to the image content. Experimental results show that our method can achieve accurate registration of the multi-modal images.

Gaussian field estimator with manifold regularization for retinal image registration

2019 ◽  
Vol 157 ◽  
pp. 225-235 ◽  
Author(s):  
Jiahao Wang ◽  
Jun Chen ◽  
Huihui Xu ◽  
Shuaibin Zhang ◽  
Xiaoguang Mei ◽  
...  
Keyword(s):  
Image Registration ◽  
Retinal Image ◽  
Manifold Regularization ◽  
Gaussian Field
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