High resolution image acquisition from magnetic resonance and computed tomography scans using the curvelet fusion algorithm with inverse interpolation techniques.

We present a new approach, based on the curvelet transform, for the fusion of magnetic resonance and computed tomography images. The objective of this fusion process is to obtain images, with as much detail as possible, for medical diagnosis. This approach is based on the application of the additive wavelet transform on both images and the segmentation of their detail planes into small overlapping tiles. The ridgelet transform is then applied on each of these tiles, and the fusion process is performed on the ridgelet transforms of the tiles. To maximize the benefit of the fused images, inverse interpolation techniques are used to obtain high resolution images from the low resolution fused images. Three inverse interpolation techniques are presented and compared. Simulation results show the superiority of the proposed curvelet fusion approach to the traditional discrete wavelet transform fusion technique. Results also reveal that inverse interpolation techniques have succeeded in obtaining high resolution images from the fused images with better quality than that of the traditional cubic spline interpolation technique.