Segmentation of Fused CT and MRI Images with Brain Tumor

Abstract

This paper proposes an approach for combining two multimodality images [CT and MRI] with tumor cell, helps to delineate the anatomical and physiological differences from one dataset to another using Wavelet transform and its inverse transform. Image fusion is the process that matches two or more image datasets resulting in a single image dataset. There are many fusion processes that can take place at different levels, in this paper focuses on pixel level fusion process, where each pixel from the input images [CT and MRI] are taken as composite input data for further processing. In this project the next proposed step is to segment the tumor using Otsu’s Algorithm. Segmentation process is performed to detect the tumor from all the above three images i.e., CT, MRI and Fused Image by using OTSU’s segmentation algorithm for future comparison. The fused image contains both soft tissue information’s like Tumor and also hard tissues information’s like bones, helpful for physician and doctors to quantify the area of tumor for surgical planning. This paper also reduces the treatment cost to patient where there is no need of separate imaging device to obtain CT/MRI imaging modality.