Early detection of skin cancer is very important and can prevent some skin cancers, such as focal cell carcinoma and melanoma. Although there are several reasons that have bad impacts on the detection precision. Recently, the utilization of image processing and machine vision in medical applications is increasing. In this paper, a new image processing based method has been proposed for the early detection of skin cancer. The method utilizes an optimal Convolutional neural network (CNN) for this purpose. In this paper, improved whale optimization algorithm is utilized for optimizing the CNN. For evaluation of the proposed method, it is compared with some different methods on two different datasets. Simulation results show that the proposed method has superiority toward the other compared methods.

早期发现皮肤癌非常重要，可以预防某些皮肤癌，例如局灶性细胞癌和黑色素瘤。尽管有几个原因会对检测精度产生不良影响。近来，在医疗应用中图像处理和机器视觉的利用正在增加。本文提出了一种基于图像处理的新方法，用于皮肤癌的早期检测。为此，该方法利用了最佳的卷积神经网络（CNN）。本文采用改进的鲸鱼优化算法对CNN进行优化。为了评估所提出的方法，将其与两个不同数据集上的一些不同方法进行了比较。仿真结果表明，该方法具有优于其他方法的优势。