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Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
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Abstract

Background

A clinical medical image provides vital information about a person's health and bodily condition. Typically, doctors monitor and examine several types of medical images individually to gather supplementary information for illness diagnosis and treatment. As it is arduous to analyze and diagnose from a single image, multi-modality images have been shown to enhance the precision of diagnosis and evaluation of medical conditions.

Objective

Several conventional image fusion techniques strengthen the consistency of the information by combining varied image observations; nevertheless, the drawback of these techniques in retaining all crucial elements of the original images can have a negative impact on the accuracy of clinical diagnoses. This research develops an improved image fusion technique based on fine-grained saliency and an anisotropic diffusion filter to preserve structural and detailed information of the individual image.

Methods

In contrast to prior efforts, the saliency method is not executed using a pyramidal decomposition, but rather an integral image on the original scale is used to obtain features of superior quality. Furthermore, an anisotropic diffusion filter is utilized for the decomposition of the original source images into a base layer and a detail layer. The proposed algorithm's performance is then contrasted to those of cutting-edge image fusion algorithms.

Results

The proposed approach cannot only cope with the fusion of medical images well, both subjectively and objectively, according to the results obtained, but also has high computational efficiency.

Conclusion

Furthermore, it provides a roadmap for the direction of future research.

© 2024 Kaur et al.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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2024-01-01
2025-04-24

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/content/journals/cmir/10.2174/0115734056269626231201042100
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Fusion of Multimodal Medical Images based on Fine-grained Saliency and Anisotropic Diffusion Filter
Curr. Med. Imaging 20, e15734056269626 (2024); https://doi.org/10.2174/0115734056269626231201042100
/content/journals/cmir/10.2174/0115734056269626231201042100
/content/journals/cmir/10.2174/0115734056269626231201042100
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  • Article Type:     Research Article
Keyword(s): Anisotropic diffusion filter; Biomedical image fusion; Fine-grained saliency; Healthy lives; Image quality assessment; MRI

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