Medical Image Fusion based on Frei-Chen Masks in NSST Domain

Abstract

Medical image fusion presents the information given by different imaging modalities in a single composite image. Fused image provides more clinical information useful for the precise diagnosis, treatment planning and follow-up studies of various diseases. A medical image fusion method based on Frei-Chen operators in nonsubsampled shearlet transform (NSST) domain is presented in this research paper. The proposed method is tested on four multimodality medical image datasets. The visual and quantitative evaluation of fusion results exhibited the superior performance of the proposed image fusion approach.