ArticleFrontiers in computational neuroscience2021
Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation.
Article in Frontiers in computational neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- NFSAOA: a new approach of medical brain image fusion using neutrosophic fuzzy set and arithmetic optimization algorithm.Medical & biological engineering & computing · 2026Article
- Alzheimer's disease stage recognition from MRI and PET imaging data using Pareto-optimal quantum dynamic optimization.Heliyon · 2024Article
- Infection detection revolution: Harnessing AI-powered image analysis to combat infectious diseases.PloS one · 2024Article
- An Improved Multimodal Medical Image Fusion Approach Using Intuitionistic Fuzzy Set and Intuitionistic Fuzzy Cross-Correlation.Diagnostics (Basel, Switzerland) · 2023Article
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6 authors.
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Abstract
Medical image fusion has an indispensable value in the medical field. Taking advantage of structure-preserving filter and deep learning, a structure preservation-based two-scale multimodal medical image fusion algorithm is proposed. First, we used a two-scale decomposition method to decompose source images into base layer components and detail layer components. Second, we adopted a fusion method based on the iterative joint bilateral filter to fuse the base layer components. Third, a convolutional neural network and local similarity of images are used to fuse the components of the detail layer. At the last, the final fused result is got by using two-scale image reconstruction. The contrast experiments display that our algorithm has better fusion results than the state-of-the-art medical image fusion algorithms.
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