The primary goal of this paper is how to detect the lung cancer tumor based on the K-means clustering thresholding (K-MTh) segmentation technique, rate of death from lung cancer diseases is increased in the last years so the discovered of lung cancer early can protect a lot of people from died . The technique of image processing is utilized ,in image processing ,there are a lot of steps are done for improving the performance of medical diagnostic machine .The technique which used is considered very important to classify the degree of a tumor by improving the thresholding technique before using the classification methods such as support vector machine (SVM). Actually, we have applied Gabor Gaussian filtration method to improve and denoise the CT-image, then we applied the segmentation method (K-MTh) and SVM. Finally, the system has been achieved accuracy more than have been expected for classification method after applying K-MTh (more than 90%).
Aouf, M. (2019). Application of K-MTh Algorithm for Accurate Lunge Cancer Detection. International Journal of Intelligent Computing and Information Sciences, 19(2), 1-20. doi: 10.21608/ijicis.2019.71026
MLA
Mohamed Aouf. "Application of K-MTh Algorithm for Accurate Lunge Cancer Detection". International Journal of Intelligent Computing and Information Sciences, 19, 2, 2019, 1-20. doi: 10.21608/ijicis.2019.71026
HARVARD
Aouf, M. (2019). 'Application of K-MTh Algorithm for Accurate Lunge Cancer Detection', International Journal of Intelligent Computing and Information Sciences, 19(2), pp. 1-20. doi: 10.21608/ijicis.2019.71026
VANCOUVER
Aouf, M. Application of K-MTh Algorithm for Accurate Lunge Cancer Detection. International Journal of Intelligent Computing and Information Sciences, 2019; 19(2): 1-20. doi: 10.21608/ijicis.2019.71026
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