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Considering the interpolation of cross-sectional medical images is one of the key steps of 3D medical image reconstruction and it directly affects the accuracy of the results on the three-dimensional reconstruction of human tissues and organs. To overcome the shortcomings such as blurred border of images and lower efficiency caused by present interpolation methods, an interslice interpolation in view of the relativity for medical images is presented in this paper. This algorithm which makes good use of voxel relativity and structure relativity can classify human tissue, and then the different methods are adopted to interpolate the different points, In addition, error checkout is introduced to check the mismatching points.And the experimental validation and analysis indicate that our proposed algorithm has less computational complexity and improves the quality of image, and the edge of these images will be clearer. The result can be used to 3D reconstruction effectively.