Title :
Robust Multimodal Medical Image Elastic Registration Using RPM and Mean Shift
Author :
Yang, Xuan ; Pei, Jihong
Author_Institution :
Coll. of Inf. Eng., Shenzhen Univ., Shenzhen
Abstract :
Landmark matching is widely applied in multimodal medical image registration. In this paper, a novel landmarks corresponding estimation combining robust point matching (RPM) and mean shift algorithm is proposed. At first, corners of images are detected to be the landmarks sets. Robust point matching algorithm is used to estimate the coarse transformation parameters between two landmark sets. Next, mean shift iterations are adopted to search the exact corresponding point positions in the two images based on the edge structure feature. Moreover, mutual information between two local regions and the topology relations between landmarks are analyzed to eliminate mis-matching landmarks. Finally, the deformed image is transformed by compact support thin-plate spline interpolation. Experiments show that the precision in location of corresponding landmarks is satisfied. The proposed technique is feasible and robust shown in the experiments of various multi-modal medical images registration.
Keywords :
edge detection; image matching; image registration; interpolation; iterative methods; medical image processing; splines (mathematics); coarse transformation parameter estimation; corner detection; iterative method; landmark matching; mean shift algorithm; multimodal medical image elastic registration; mutual information; robust point matching algorithm; thin-plate spline interpolation; Biomedical imaging; Data mining; Feature extraction; Image registration; Intelligent networks; Intelligent systems; Mutual information; Probability density function; Robustness; Topology; Elastic Transformation; Mean Shift; Multimodal Image Registration; Robust Point Matching;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2008. ICINIS '08. First International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3391-9
Electronic_ISBN :
978-0-7695-3391-9
DOI :
10.1109/ICINIS.2008.25