Interpolation of cross sectional medical images is an important procedure in 3D reconstruction．To overcome the shortcomings

which are brought by current algorithms

such as ambiguity of objects’ boundary

high cost of computing. In this paper we propose a novel adaptive image interpolation algorithm that is suitable to medical image processing．This algorithm makes good use of characteristics of anatomical structures and volume relativity and uses the following strategies: firstly to judge whether the interpolation point belongs to ROI

then to get the best point pair according to quality of curve．The experimental results show that the novel method produces new image that is in better accord with the practical demand not only in gray but anatomical structures as well．Moreover

this algorithm is more efficient than current algorithms.Therefore

our algorithm is more suitable to 3D reconstruction．