Multi Modalities Medical Image Fusion Using Deep Learning and Metaverse Technology: Healthcare 4.0 A Futuristic Approach

Abstract

Multimodal medical image fusion is the efficient integration of various imaging modalities to improve the ability to assess, direct therapy, treat patients, or predict outcomes. As image fusion offers additional essential information, the correctness of the image generated from different medical imaging modalities has a substantial impact on the success of a disease's diagnosis. A single medical imaging modality cannot provide complete and precise information. In the modern research area, multimodality medical image fusion approach is one of the meaningful research in the area of medical imaging and radiation medicine. The fusion of medical images is the process of enrolling and combining multiple images from one or more imaging modalities, enhancing the image quality and to achieve randomness and redundancy, heighten the clinical utility of medical images in the diagnosis and evaluation of medical problems. The thought is to enhance the image occurrence Magnetic resonance imaging (MRI) is achieved by combining images like computerized tomography (CT) as well as magnetic resonance imaging (MRI) gives fine soft tissue information as long as CT gives fine facts over denser tissue. In this research paper, we have an account that features for future development with demanding performance requirements and processing speed.