• Reddy Usha Sravani
• P. Sarvana Kumar
• P. Yashaswini
• Atragadda Purna Rajesh
• Pachigolla Sukumar

Medical image fusion is a crucial technique in image processing that integrates multi-modality images into a single, high-quality image, addressing the limitations of traditional methods by preserving critical edge and energy information for accurate lesion characterization. Utilizing automatic feature extraction, dedicated fusion networks, and robust reconstruction techniques, it enhances both the quality and diagnostic value of medical images, improving clinical diagnosis and decision-making. The increasing number of image acquisition systems has made image fusion essential for aligning key information from diverse sensors, such as multi-temporal, multi-view, and multi-sensor data, into a single image while preserving important features. This process is vital not only for medical imaging but also for applications like robot vision, aerial and satellite imaging, and vehicle guidance. Various fusion methods, including spatial and transform-based approaches, are employed, each with unique advantages and limitations, and quality metrics are used to assess their effectiveness. As the field evolves, state-of-the-art techniques are developed to enhance clarity and usability, with future directions aimed at improving the accuracy and efficiency of image fusion across various domains reliant on high-quality image processing.

Convolutional Neural Networks (CNNs) , Detail Layers , Edge preservation , Energy Retention , Feature Extraction , Lesion characterization , Medical image fusion , Multimodal imaging.

"Medical Image Fusion", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 12, page no.e178-e189, December-2024, Available :http://www.jetir.org/papers/JETIR2412419.pdf

"Medical Image Fusion", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 12, page no. ppe178-e189, December-2024, Available at : http://www.jetir.org/papers/JETIR2412419.pdf