@article { author = {G, Parthasarathy and L, Ramanathan and K, Anitha and Y, Justindhas}, title = {Predicting Source and Age of Brain Tumor Using Canny Edge Detection Algorithm and Threshold Technique}, journal = {Asian Pacific Journal of Cancer Prevention}, volume = {20}, number = {5}, pages = {1409-1414}, year = {2019}, publisher = {West Asia Organization for Cancer Prevention (WAOCP), APOCP's West Asia Chapter.}, issn = {1513-7368}, eissn = {2476-762X}, doi = {10.31557/APJCP.2019.20.5.1409}, abstract = {Objective: We propose an iterative method and associated with thresholding technique for detecting the tumorsource and the age of tumor. Methods: The technique is based on Euclidean distance with strong edge and weak edgefor identifying the spreading area of disease and also detecting the tumor age. The work involves the use of cannyedge detection algorithm and thresholding technique, which exploits the information detection of brain tumor sourcethrough 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 1ststage, between 250 - 400 as 2nd stage, 400 – 650 as 3rd stage and also detection of the spread area, helps stopping thetumor 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 edgeand well defined tumor detection than the existing algorithm.}, keywords = {MRI image,Canny edge detection,Thresholding technique,Euclidean Distance}, url = {https://journal.waocp.org/article_87831.html}, eprint = {https://journal.waocp.org/article_87831_d412328f2af4149f173b760db3de2b85.pdf} }