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