CT And MRI Scan Using Discrete Wavelet Transform Algorithm in Fusion Technique

Most of previous image fusion methods aim at obtaining as many as information from the different modality images. The fusion criterion is to minimize different error between the fused image and the input images. With respect to the medical diagnosis, the edges and outlines of the interested objects is more important than other information. How to preserve the edge like features is worthy of investigating for medical image fusion. The image with higher contrast contains more edge-like features. We proposed a new medical image fusion scheme based on an improved discrete wavelet coefficient contrast. Multimodality medical image fusion has drawn lots of attention with the increasing rate at which multimodality medical images are available in many clinic application fields. Radiotherapy plan, for instance, often benefits from the complementary information in images of different modalities. Dose calculation is based on the computed tomography (CT) data, while tumor outline is often better performed in the corresponding magnetic resonance (MR) image. CT provides the better information on denser tissue with less distortion, while MRI offers better information on soft tissue with more distortion. With more available multimodality medical images in clinic application, the idea of encompassing different image information comes up very important, and medical image fusion has been emerging as a new and promising research area. The goal of image fusion is to obtain useful complementary information from multimodality images as much as possible.