Analysis and Comparison of Medical Image Fusion Techniques: Wavelet based Transform and Contourlet based Transform

Medical Image Fusion provides additional information for diagnosis when a registered and overlaid multiple patient images. Multiple images from the same imaging modality or multiple modalities can be used to create a fused image. The fused image is of immense help and provides more information to the doctor so as to diagnose the diseases. The CT (Computer Tomography) offers less detailed information for soft tissues and good information on bony structures. But the MRI (Magnetic Resonance Imaging) provides a more detailed information on the soft tissues but less detailed information on bone structures and the contrast resolution of soft tissues is far better in MRI than in CT. In this paper, Wavelet based Transform like DWT (Discrete Wavelet Transform) and CWT (Complex Wavelet Transform) is analyzed theoretically and it is compared with Contourlet based Transform like CCT (Complex Contourlet Transform) and NSCT (No-Subsampled Contourlet Transform). The experimental results showing the evaluation measures like IE (Information Entrophy) , AG (Average Gradient) and SD (Standard Deviation).