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The proposed fusion method is evaluated on 20 pairs of multi-modality medical images and compared with seven previous fusion methods and two deep-learning-based fusion methods. Quantitative and qualitative experimental results demonstrate the advantage of the proposed fusion method in terms of visual quality and fusion performance.<\/jats:p>","DOI":"10.1142\/s0129065720500501","type":"journal-article","created":{"date-parts":[[2020,6,4]],"date-time":"2020-06-04T23:20:26Z","timestamp":1591312826000},"page":"2050050","source":"Crossref","is-referenced-by-count":113,"title":["Medical Image Fusion Method Based on Coupled Neural P Systems in Nonsubsampled Shearlet Transform Domain"],"prefix":"10.1142","volume":"31","author":[{"given":"Bo","family":"Li","sequence":"first","affiliation":[{"name":"School of Computer and Software Engineering, Xihua University, Chengdu 610039, P. R. 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