The reason of using red channel as color represent or is the fact that each ethnic group has healthy skin color of reddish and skin lesions are regions of skin with altered color. The reason of using the first component is the fact that this component contains maximum changes in

the image, and in skin lesion buy Bicalutamide images, maximum changes as well as most of texture information occur on the lesion border. Separation of lesion from healthy skin is more effective by using one of the three mentioned single-channel images which are determined by examining the histogram information. In general, histogram of skin lesion image has two peaks corresponding to healthy skin and lesion area which whatever they are farther and the valley between them is deeper, lesions area will be separated with higher accuracy from healthy skin. Therefore, a single-channel image is selected which distance between peaks of its smoothed histogram using local regression is maximum. Four different thresholds are defined and calculated over the optimum single-channel image as follows: First threshold is calculated using Otsu thresholding algorithm (levelo) Second threshold that is the mean value of lesion and healthy skin distribution peaks of the histogram (levelm) Third threshold that is the starting point of healthy skin Gaussian distribution (levelf) Fourth threshold

that is the point with the lowest height between lesion and healthy skin distribution on the histogram (levelv). Then the thresholds on the image histogram which have the minimum distances to each other in terms of intensity level are selected and the largest one of them which covers results of other selected thresholds is applied on the optimal

single-channel image. Since the shadow effect is corrected at first and thereafter, the threshold and borders are determined; shadow will not be mistaken by the lesion area and cannot affect on the borders determination. Figure 5 shows a histogram of the optimum gray scale image of a skin lesion image with the four Entinostat mentioned thresholds and the results of applying them and the optimal one. In the histogram of Figure 5a, the first and fourth thresholds completely matches and, therefore, are considered as the closest ones. Figure 5c shows results of using these two thresholds that indicates the lesion boundaries very accurate. As can be seen in Figure ​Figure5d5d-​-g,g, the boundaries of the second and third thresholds show large errors, while the selected thresholds by segmentation algorithm lead to the best results. Figure 5 (a) Histogram of the optimal grayscale skin lesion image, (b) The preprocessed image of skin lesion, (c) Final result of segmentation, (d) Determined boundaries using the first threshold, (e) The second threshold, (f) The third threshold, (g) The fourth …