An Efficient Algorithm for Medical Image Fusion Using Nonsubsampled Shearlet Transform

摘要

Multimodal medical image fusion techniques are utilized to fuse two images obtained from dissimilar sensors for obtaining additional information. These methods are used to fuse computed tomography (CT) images with magnetic resonance images (MRI), MR-T1 images with MR-T2 images, and MR images with single photon emission computed tomography (SPECT) images. In proposed method, nonsubsampled shearlet transform (NSST) is used for decomposition of source images to attain the low-frequency and high-frequency bands. The low-frequency bands are fused using weighted saliency-based fusion criteria, and high-frequency bands are fused with the help of phase stretch transform (PST) features. Applying inverse NSST operation, fused image is obtained. The results show the proposed method produces better results compared to state-of-the-art methods.