A novel method for constructing corresponding relationship
between sequential image and respiratory signal
1.Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China; 2.Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130000, China; 3.University of Chinese Academy of Sciences, Beijing 100049, China
Abstract：To quickly and accurately assign the positions of sequential images in respiratory cycle for building lung respiratory motion model, a novel distance correlation method was proposed to determine the corresponding relationship between 4D CT and respiratory signal by comparing the distance of in vitro labeling in 4D CT datasets with respiratory signal over the same time period. The proposed method was used to construct the correlational relationships between respiratory signal obtained by binocular visual system and 4D CT. The model error of a linear lung motion model built by the proposed method was calculated to evaluate the effectiveness of the proposed method. The error of the linear lung motion model based on the distance correlation method was within 2.5 mm. Compared with the motion model based on the gradient correlation method, the error was reduced more than 10%. Experimental results show that the proposed method is feasible and effective with high accuracy, and it is suitable for constructing the relationship between sequential images and respiratory signal.
2015, Vol. 36 
