Implementation and Comparative Study of Pyramid-based Image Fusion Techniques for Lumbar Spine Images

Abstract

Image fusion is a method of combining the necessary and relevant information from the set of source images into a single (fused) image which can be deemed to be more informative than the source. This paper discusses the implementation of various pyramid-based image fusion algorithms, such as the Laplacian pyramid, the ratio of the low-pass pyramid, the contrast pyramid, and the filter subtract decimate pyramid on multimodal CT and MR images of the lumbar spine. The fused images were evaluated using various objective evaluation quality metrics. The experimental results demonstrated that the ratio of the low pass pyramid achieved better performance compared to the other pyramids implemented, indicating that the fused image can also be used for further image fusion application or analysis purposes.

Optimal machine learning model based medical image compression techniques for smart healthcare

“…5G connects various items in the world and allows them to communicate with one another through the Internet with little to no human intervention. 2 Mobility management is specifically utilized to enable every mobile node to connect to the internet independent of location or movement. Increased expectations for creative applications that break through and outpace current constraints are a result of the 5G era.…”

“…The difficulties involved in medical diagnosis and therapy highlight how urgently improvements in medical image compression are needed. 2 For patients to receive appropriate care in the current healthcare environment, fast and reliable diagnostic information must be available. Nonetheless, storage capabilities, unequal access to cutting-edge imaging technologies, and restricted bandwidth for data transmission are common challenges faced by healthcare facilities.…”