Performance Enhancement of Multisensor Medical Image Fusion using Hybrid Fuzzy Logic

Abstract

newline In recent years, many fast-growing technologies coupled with wide volume of medical data for the digitalization of that data. Thus, researchers have shown their immense interest in Multi-sensor image fusion technologies which convey image information based on data from various sensor modalities into a single image. The image fusion technique is a widespread technique for the diagnosis of medical instrumentation and measurement. Therefore, in study initially we have introduced a novel multimodal sensor medical image fusion method based on type-2 fuzzy logic is proposed using Sugeno model. Moreover, a Gaussian smoothing filter is introduced to extract detailed information of an image using sharp feature points. Type-2 fuzzy algorithm is used to achieve highly efficient feature points from both the b images to provide high visually classified resultant image. Afterwards we proposed multiple modal medical image fusion, which is an essential method for medical imaging technologies. In these Multi-modal medical image fusion usually are Positron Emission Tomography (and#119875;and#119864;and#119879;) and Single-photon Emission Computer Tomography (and#119878;and#8722;and#119875;and#119864;and#119862;and#119879;), Magnetic Resonance Imaging (and#119872;and#119877;and#119868;) and Computed Tomography (and#119862;and#119879;) images are utilized. However, the conventional state-of-art-fusion-techniques consists of less redundant and less comprehensive information. Therefore, here, we present an image fusion technique to control non-linear uncertainties and provide stability based on and#119868;and#119879;2and#119865;and#119871;and#119863;and#119878; for multi-modal medical color images. The core idea is to perform fusion on color source images of either functional or structural type by extracting both large and small structural information which is rarely done in any other conventional state-of-art-techniques. This can be achieved with the help of and#119868;and#119879;2and#119865;and#119871;and#119863;S. The fuzzy membership functions based image fusion technique helps to combining low and high frequency components of multi-model medical color images. newline newline