Gradient Compass-Based Adaptive Multimodal Medical Image Fusion
In medical imaging, the use of different imaging modalities has significantly enhanced the diagnostic information available to physicians. Each type of modality exhibits unique information about the subject being imaged. In many cases, physicians are interested in multimodal information about the sa...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9345328/ |
| _version_ | 1818936155981217792 |
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| author | Muhammad Touseef Irshad Hafeez Ur Rehman |
| author_facet | Muhammad Touseef Irshad Hafeez Ur Rehman |
| author_sort | Muhammad Touseef Irshad |
| collection | DOAJ |
| description | In medical imaging, the use of different imaging modalities has significantly enhanced the diagnostic information available to physicians. Each type of modality exhibits unique information about the subject being imaged. In many cases, physicians are interested in multimodal information about the same organ, which is complementary in nature and its fusion is often required. A lot of methods are proposed to address the medical image fusion problem. However, the main downside of all such methods is the loss of key features from the input images to the fused image. Additionally, such methods also introduce unwanted artifacts in the fused image. In this work, we present a method for multimodal medical image fusion based on the gradient compass in the spatial domain, which can effectively fuse a pair of multimodal medical images. An edge detail is extracted from source multimodal medical images in eight different directions, which provides significant data for the construction of an edge map of source medical images. With the help of constructed edge maps two detailed medical images are generated. The statistical properties of detailed medical images are used to construct weight matrices, which are then used to perform adaptive pixel fusion. We benchmark our method on multiple Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) images of the same subject. The performance of the proposed algorithm has outperformed the existing methods by transferring only related information from the source image to the fused image. |
| first_indexed | 2024-12-20T05:31:35Z |
| format | Article |
| id | doaj.art-700dd2c4624c4d70a0875faeb9276176 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T05:31:35Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-700dd2c4624c4d70a0875faeb92761762022-12-21T19:51:43ZengIEEEIEEE Access2169-35362021-01-019226622267010.1109/ACCESS.2021.30548439345328Gradient Compass-Based Adaptive Multimodal Medical Image FusionMuhammad Touseef Irshad0https://orcid.org/0000-0002-3364-713XHafeez Ur Rehman1https://orcid.org/0000-0002-3274-6347Department of Computer Science, National University of Computer and Emerging Sciences, Peshawar, PakistanDepartment of Computer Science, National University of Computer and Emerging Sciences, Peshawar, PakistanIn medical imaging, the use of different imaging modalities has significantly enhanced the diagnostic information available to physicians. Each type of modality exhibits unique information about the subject being imaged. In many cases, physicians are interested in multimodal information about the same organ, which is complementary in nature and its fusion is often required. A lot of methods are proposed to address the medical image fusion problem. However, the main downside of all such methods is the loss of key features from the input images to the fused image. Additionally, such methods also introduce unwanted artifacts in the fused image. In this work, we present a method for multimodal medical image fusion based on the gradient compass in the spatial domain, which can effectively fuse a pair of multimodal medical images. An edge detail is extracted from source multimodal medical images in eight different directions, which provides significant data for the construction of an edge map of source medical images. With the help of constructed edge maps two detailed medical images are generated. The statistical properties of detailed medical images are used to construct weight matrices, which are then used to perform adaptive pixel fusion. We benchmark our method on multiple Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) images of the same subject. The performance of the proposed algorithm has outperformed the existing methods by transferring only related information from the source image to the fused image.https://ieeexplore.ieee.org/document/9345328/Medical image fusiongradient compassedge detailweightsimage registration |
| spellingShingle | Muhammad Touseef Irshad Hafeez Ur Rehman Gradient Compass-Based Adaptive Multimodal Medical Image Fusion IEEE Access Medical image fusion gradient compass edge detail weights image registration |
| title | Gradient Compass-Based Adaptive Multimodal Medical Image Fusion |
| title_full | Gradient Compass-Based Adaptive Multimodal Medical Image Fusion |
| title_fullStr | Gradient Compass-Based Adaptive Multimodal Medical Image Fusion |
| title_full_unstemmed | Gradient Compass-Based Adaptive Multimodal Medical Image Fusion |
| title_short | Gradient Compass-Based Adaptive Multimodal Medical Image Fusion |
| title_sort | gradient compass based adaptive multimodal medical image fusion |
| topic | Medical image fusion gradient compass edge detail weights image registration |
| url | https://ieeexplore.ieee.org/document/9345328/ |
| work_keys_str_mv | AT muhammadtouseefirshad gradientcompassbasedadaptivemultimodalmedicalimagefusion AT hafeezurrehman gradientcompassbasedadaptivemultimodalmedicalimagefusion |