G Parthasarathy, L Ramanathan, K Anitha, Y Justindhas
Department of CSE, Jeppiaar Maamallan Engineering College, Anna University, Chennai, India.Email:
School of Computer Science and Engineering (SCOPE), VIT, Vellore, India.
Asian Pac J Cancer Prev. 2019 May 25;20(5):1409-1414. doi: 10.31557/APJCP.2019.20.5.1409.
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.
我们提出一种迭代方法及相关的阈值技术，用于检测肿瘤源和肿瘤年龄。方法：该技术基于欧几里得距离，结合强边缘和弱边缘来识别疾病的扩散区域并检测肿瘤年龄。这项工作涉及使用坎尼边缘检测算法和阈值技术，通过磁共振成像（MRI）来利用脑肿瘤源的信息检测。该系统有助于使用欧几里得距离计算肿瘤年龄（近似值）。结果：计算出年龄范围在0 - 100为第0阶段，100 - 250为第1阶段，250 - 400为第2阶段，400 - 650为第3阶段，并且检测到扩散区域，有助于阻止肿瘤侵袭相邻细胞，从而降低癌细胞的侵袭百分比。结论：该方法提供了所提算法在额外抗噪声方面的模拟输出，并且在边缘检测和肿瘤检测清晰度上比现有算法有所改进。
