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Öğe Performance Analysis of Histogram-Threshold Method for Cancer Detection(IEEE, 2014) Koc, Gamze; Gokdel, Yigit Daghan; Sarioglu, BaykalIn this paper, histogram-threshold method developed for cancer detection using miniaturized confocal microscopy system and its related performance analysis are presented. While doing the performance analysis, the receiver operation characteristics are applied in a novel fashion. Additionally, noise performances of different method are investigated. The highest and lowest success rates with 91.67% and 27.08% are acquired using Entropy Method and Mean Method, respectively.Öğe Statistical Analysis of Threshold Algorithms in Image Processing Based Cancer Cell Detection(IEEE, 2014) Koc, Gamze; Sarioglu, BaykalIn this paper, an algorithm which is implemented for cancer detection in image processing and the results of the algorithm are mentioned. Researched work has three main steps. In first step, images are passed through significant steps for noise removal; at the second step, various histogram thresholds are calculated and at the last step cancer is detected with respect to calculated thresholds. As a result, the highest success rate is obtained as 81.25 percent while the lowest success rate is 37.5 percent.