Active contour model guided image metamorphosis for inter-slice interpolation of medical images

This paper presents an interpolation method that uses the contours of organs as the control parameters to recover the intensity information in the physical gaps of serial cross-sectional medical images. In this method, active contour models are used for generating the control lines required for the field morphing algorithm, which were previously manually specified. Contour information derived from this segmentation pre-process is then further processed and used as control parameters to warp the corresponding regions in both input data slices into compatible shapes. In this way, the reliability of correspondence to locate different segments of the same organs is improved and the intensity information for the interpolated intermediate slices can be derived more faithfully, To reduce the high time complexity for calculating the image warp in the field morphing process, a hierarchical decomposition process is proposed. In comparison with the existing intensity interpolation algorithms, which only consider corresponding points in a small physical neighborhood, this method warps the data images into similar shapes according to contour information to provide more meaningful correspondence relationships. The results show that this method generates more realistic and less blurred interpolated images especially when the local intensity variation is significant.