Image interpolation of cross-sections is one of the key steps of medical visualization. Aiming at the problem of fuzzy boundaries and large amount of calculation, which are brought by the traditional interpolation, a novel adaptive 3-D medical image interpolation method is proposed in this paper. Firstly, the contour is obtained by the edge interpolation, and the corresponding points are found according to the relation of the contour and points on the original images. Secondly, this algorithm utilizes volume relativity to get the best point-pair with the adaptive methods. Finally, the grey value of interpolation pixel is got by the matching point interpolation. The experimental results show that the method presented in the paper not only can meet the requirements of interpolation accuracy, but also can be used effectively in medical image 3D reconstruction.