Multi-Level Fusion of CT and MRI Brain Images for Classifying Tumor

Abstract

Abstract: Medical image processing is the most stimulating and developing field in our day today life. Now a day's processing of MRI images is one of the parts of this field This paper proposes an efficient method for detection of brain tumor from CT and MRI images of brain, by applying image fusion, segmentation, feature extraction and classification. Image Fusion is the process of combining relevant information from two or more images into a single composite image. First, the CT and MRI images of brain are subjected to multilevel fusion using discrete wavelet transform. The fusion strategy uses multi-level decomposition of the images obtained using wavelet transform. By analyzing the images at multiple levels, the method is able to extract finer details from them and in turn improves the quality of the fused image. The fused image is then segmented using morphological operations. And the features are extracted. Finally the extracted image is exposed to fuzzy based classification to identify whether the tumor is benign or malignant