DocumentCode
3135577
Title
Rapid Multimodal Medical Image Registration and Fusion in 3D Conformal Radiotherapy Treatment Planning
Author
Li, Bin ; Tian, Lianfang ; Ou, Shanxing
Author_Institution
Sch. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
fYear
2010
fDate
18-20 June 2010
Firstpage
1
Lastpage
5
Abstract
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.
Keywords
entropy; feature extraction; gradient methods; image fusion; image registration; image sequences; medical image processing; positron emission tomography; radiation therapy; stochastic processes; wavelet transforms; 3D conformal radiotherapy treatment planning; FFD coefficients; ROI; automatic fine registration; global rough registration; hierarchical adaptive free-form deformation algorithm; image sequence; maximum mutual information entropy criteria; parallel computing method; principal axes algorithm; rapid multimodal medical image fusion; rapid multimodal medical image registration; region of interest; stochastic gradient descent method-simultaneous perturbation; wavelet transform; Biomedical imaging; Capacitance-voltage characteristics; Data mining; Image registration; Level set; Medical treatment; Mutual information; Parallel processing; Spline; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on
Conference_Location
Chengdu
ISSN
2151-7614
Print_ISBN
978-1-4244-4712-1
Electronic_ISBN
2151-7614
Type
conf
DOI
10.1109/ICBBE.2010.5517203
Filename
5517203
Link To Document