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Current Medical Imaging

Editor-in-Chief

ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

Research Article

Fusion of Multimodal Medical Images based on Fine-grained Saliency and Anisotropic Diffusion Filter

Author(s): Harmanpreet Kaur*, Renu Vig, Naresh Kumar, Apoorav Sharma, Ayush Dogra and Bhawna Goyal

Volume 20, 2024

Published on: 26 January, 2024

Article ID: e15734056269626 Pages: 14

DOI: 10.2174/0115734056269626231201042100

open_access

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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.

Keywords: Biomedical image fusion, Healthy lives, Fine-grained saliency, Image quality assessment, Anisotropic diffusion filter, MRI.


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