Multimodal Medical Image Fusion: A Review of Techniques, Metrics, and Trends

Multimodal image fusion combines anatomical computed tomography/magnetic resonance imaging with functional positron emission tomography/single-photon emission computed tomography to improve analysis and treatment planning; review covers six method families and future trends.

• Covers common modalities and public databases used for fusion research.
• Systematically reviews spatial-domain, transform-domain, sparse representation, deep learning, hybrid, and Mamba-based methods.
• Discusses quality metrics, reported quantitative performance, and future challenges including robustness and clinical translation.

Automated summary

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