An improved multimodal medical image fusion algorithm based on fuzzy transform

Multimodal medical image fusion has become a powerful tool in clinical applications. The main aim is to fuse different multimodal medical images, obtained from different imaging modalities, into a single fused image that is extensively used by the physicians for explicit diagnosis and treatment of diseases. In this paper, an improved multimodal medical image fusion algorithm based on fuzzy transform (FTR) is proposed. The core idea behind the proposed algorithm is to improve the performance of multimodal medical image fusion algorithm by taking into consideration the error images obtained using FTR pair. Subjective as well as objective evaluations demonstrate that the fusion quality in terms of edge strength, standard deviation, feature mutual information, fusion factor, feature similarity and structural similarity has significantly improved in the proposed algorithm as compared to other state-of-art multimodal medical image fusion algorithms.