Multi-modal Medical Image Fusion Algorithm Based on Spatial Frequency Motivated PA-PCNN in the NSST Domain

Abstract

BACKGROUND: Image fusion has been grown as an effectual method in diseases related diagnosis schemes. METHODS: In this paper, a new method for combining multimodal medical images using spatial frequency motivated parameter-adaptive PCNN (SF-PAPCNN) is suggested. The multi- modal images are disintegrated into frequency bands by using decomposition NSST. The coefficients of low frequency bands are selected using maximum rule. The coefficients of high frequency bands are combined by SF-PAPCNN. METHODS: In this paper, a new method for combining multimodal medical images using spatial frequency motivated parameter-adaptive PCNN (SF-PAPCNN) is suggested. The multi-modal images are disintegrated into frequency bands by using decomposition NSST. The coefficients of low frequency bands are selected using maximum rule. The coefficients of high frequency bands are combined by SF-PAPCNN. RESULTS: The fused medical images is obtained by applying INSST to above coefficients. CONCLUSION: The quality metrics such as entropy ENT, fusion symmetry FS, deviation STD, mutual information Q(MI) and edge strength Q(AB/F) are used to validate the efficacy of suggested scheme.