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Directive clustering contrast-based multi-modality medical image fusion for smart healthcare system

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Abstract

Smart healthcare is being adopted gradually as information technology advances. The enormous increase in demand for smart medical imaging has resulted in the fusion of a number of important imaging technologies. In smart imaging, many times single modality images are not sufficient to extract the major or minor information from medical images. Therefore in this paper, a new fusion algorithm is introduced for multi-modality medical images to extract maximum information and provide an efficient fused image. In proposed scheme, NSCT is used to get low- and high-frequency components of the medical images. Further, clustering-based fusion technique is used for fusing low-frequency components by analysing cluster features. Similarly, contrast-preserving image fusion on the high-frequency coefficients is accomplished by the use of directed contrast based on cluster-based components. The experimental results and comparison analysis is conducted on the multi-modal medical image dataset. Test results and evaluations of the proposed technique show that it outperforms the leading fusion strategies in terms of contrast and edge preservations.

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Correspondence to Soumya Ranjan Nayak.

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Diwakar, M., Singh, P., Shankar, A. et al. Directive clustering contrast-based multi-modality medical image fusion for smart healthcare system. Netw Model Anal Health Inform Bioinforma 11, 15 (2022). https://doi.org/10.1007/s13721-021-00342-2

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  • DOI: https://doi.org/10.1007/s13721-021-00342-2

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