Multimodal Medical Image Fusion Based on Fuzzy Enhancement and Fuzzy Transform

Abstract

Multimodal medical image fusion is a process of extracting information from different medical images to obtain a single image called fused image.  Fused image analysis is extensively used by clinical professionals for quick diagnosis and treatment of critical diseases. This paper is developed using fuzzy logic enhancement and fuzzy transform (FT) for integrated multimodal medical image fusion. FT based fusion helps in preservation as well as effective transfer of detailed information present in input images into a fused image. The proposed work is effective and generates better fused images compared to existing techniques such as discrete wavelet transform (DWT) and non-subsampled contourlet transform (NSCT). The fused image is also compared with quality metrics such as Entropy (E), Mutual Information (MI) and Edge based quality metric (Q^AB/F).