Predicting Source and Age of Brain Tumor Using Canny Edge Detection Algorithm and Threshold Technique

Abstract

Objective: We propose an iterative method and associated with thresholding technique for detecting the tumor<br />source and the age of tumor. Methods: The technique is based on Euclidean distance with strong edge and weak edge<br />for identifying the spreading area of disease and also detecting the tumor age. The work involves the use of canny<br />edge detection algorithm and thresholding technique, which exploits the information detection of brain tumor source<br />through Magnetic Resonance Image (MRI). This system helps in the calculation of the age of tumor (approximate)<br />using Euclidean distance. Results: Calculation of the age range between 0 -100 as 0th stage, between 100 - 250 as 1st<br />stage, between 250 - 400 as 2nd stage, 400 – 650 as 3rd stage and also detection of the spread area, helps stopping the<br />tumor from invading the neighbor cells thereby reducing the percentage of invasion of cancerous cells. Conclusion:<br />This method provides the simulation output of proposed algorithm in additional noise resilient and improved in edge<br />and well defined tumor detection than the existing algorithm.