Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-01-01
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| Series: | Frontiers in Computational Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fncom.2021.803724/full |
| _version_ | 1798024803422044160 |
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| author | Shuaiqi Liu Shuaiqi Liu Shuaiqi Liu Mingwang Wang Mingwang Wang Lu Yin Lu Yin Xiuming Sun Yu-Dong Zhang Jie Zhao Jie Zhao |
| author_facet | Shuaiqi Liu Shuaiqi Liu Shuaiqi Liu Mingwang Wang Mingwang Wang Lu Yin Lu Yin Xiuming Sun Yu-Dong Zhang Jie Zhao Jie Zhao |
| author_sort | Shuaiqi Liu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T18:08:37Z |
| format | Article |
| id | doaj.art-553c0c1e172b401899c4051b8520bc06 |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-04-11T18:08:37Z |
| publishDate | 2022-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-553c0c1e172b401899c4051b8520bc062022-12-22T04:10:13ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882022-01-011510.3389/fncom.2021.803724803724Two-Scale Multimodal Medical Image Fusion Based on Structure PreservationShuaiqi Liu0Shuaiqi Liu1Shuaiqi Liu2Mingwang Wang3Mingwang Wang4Lu Yin5Lu Yin6Xiuming Sun7Yu-Dong Zhang8Jie Zhao9Jie Zhao10College of Electronic and Information Engineering, Hebei University, Baoding, ChinaMachine Vision Technological Innovation Center of Hebei, Baoding, ChinaSchool of Mathematics and Information Science, Zhangjiakou University, Zhangjiakou, ChinaCollege of Electronic and Information Engineering, Hebei University, Baoding, ChinaMachine Vision Technological Innovation Center of Hebei, Baoding, ChinaCollege of Electronic and Information Engineering, Hebei University, Baoding, ChinaMachine Vision Technological Innovation Center of Hebei, Baoding, ChinaSchool of Mathematics and Information Science, Zhangjiakou University, Zhangjiakou, ChinaSchool of Computing and Mathematics, University of Leicester, Leicester, United KingdomCollege of Electronic and Information Engineering, Hebei University, Baoding, ChinaMachine Vision Technological Innovation Center of Hebei, Baoding, ChinaMedical 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.https://www.frontiersin.org/articles/10.3389/fncom.2021.803724/fullmedical image fusionscale decompositionstructure preservationbilateral filterCNN |
| spellingShingle | Shuaiqi Liu Shuaiqi Liu Shuaiqi Liu Mingwang Wang Mingwang Wang Lu Yin Lu Yin Xiuming Sun Yu-Dong Zhang Jie Zhao Jie Zhao Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation Frontiers in Computational Neuroscience medical image fusion scale decomposition structure preservation bilateral filter CNN |
| title | Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation |
| title_full | Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation |
| title_fullStr | Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation |
| title_full_unstemmed | Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation |
| title_short | Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation |
| title_sort | two scale multimodal medical image fusion based on structure preservation |
| topic | medical image fusion scale decomposition structure preservation bilateral filter CNN |
| url | https://www.frontiersin.org/articles/10.3389/fncom.2021.803724/full |
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