Rapid Multimodal Medical Image Registration and Fusion in 3D Conformal Radiotherapy Treatment Planning
Bin Li, Lianfang Tian, Shanxing Ou · International Conference on Bioinformatics and Biomedical Engineering · 2010
In order to realize effectively and efficiently the automatic registration and fusion of multimodal medical images data in 3D conformal radiotherapy treatment planning (3D CRTP), a rapid image registration and fusion method is proposed in this paper. This proposed registration method is based on hierarchical adaptive free-form deformation(FFD) algorithm, which can be described as follows: First the ROI(region of interest) is extracted by using C-V level sets algorithm, and feature points are matched automatically which is based on parallel computing method. Then, the global rough registration is carried out by employing principal axes algorithm. Next, the automatic fine registration of the multimodal medical images is realized by a FFD method based on hierarchical B-splines. Moreover, in order to speed up the calculation of the FFD coefficients, stochastic gradient descent method-Simultaneous Perturbation(SP) and the criteria of maximum mutual information entropy are adopted. After the registration of multimodal images, their sequence images are fused by applying an image fusion method based on parallel computing and wavelet transform with the fusion rule of combining the local standard deviation and energy. This study demonstrates the superiority of the proposed method.