Application of K-MTh Algorithm for Accurate Lunge Cancer Detection

Abstract

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%).

Experimental Comparative Study on Autoencoder Performance for Aided Melanoma Skin Disease Recognition

“…In the last years, simultaneously with improvements in the computational power of GPUs, methodologies based on deep learning are mainly characterized as one of the most powerful approaches in image processing, such as [6][7][8][9][10]. Image segmentation has been a hot topic since its emergence and since then many researchers have worked on the detection and segmentation of melanoma.…”