Abstract
In this modern era, medical image processing is an indispensable part of many applications and practices in the medical domain. The images that are used should meet certain criteria, including having more accurate details and information than each individual image, which can help medical scientists with analysis and treatment. Medical image fusion is among the techniques that offer high-quality images, which are combined from different modalities. Multimodal medical image fusion provides remarkable improvement in the quality of the fused images. In this paper, we describe an image fusion method for magnetic resonance imaging (MRI) and computed tomography (CT) utilizing local features and fuzzy logic methods. The aim of the proposed technique is to create the maximum combination of useful information present in MRI and CT images. Image local features are distinguished and combined with fuzzy logic to calculate weights for each pixel. Simulation outcomes show that the proposed method produces considerably better results compared to cutting-edge techniques. The method is also used to detect and highlight tumorous areas, followed by morphology filters used to eliminate any noise and disturbance.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Innovative Research in Computer Science and Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
