Spectra Fuse Diagnostic Imaging

This paper presents a cutting-edge method for medical image fusion, consolidating multiple images from different modalities into a singular, enhanced image. Consequently, the resulting image is of exceptional quality, showcasing intricate details that are ideal for both human visual interpretation and machine perception, ensuring a comprehensive and accurate representation. The paper seeks to improve early and accurate diagnosis, along with precise treatment planning, which are vital in saving patients’ lives. The different modality images that can be considered for processing is Ultrasound, Magnetic Resonance Imaging (MRI), X-ray, Computed Tomography (CT), Positron Emission Tomography (PET). In the framework of our analysis, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans of the human brain are fused using a hybrid algorithm that incorporate both the Discrete WaveletTransform (DWT) and Curvelet Transform. The fused output which contains the complementary data that is present in both the images. The hybrid algorithm that is employed improves the accuracy of diagnosis which can be proved through the various image parameters such as Entropy, PSNR, Correlation, SSIM and Standard Deviation.