| Literature DB >> 31980095 |
Ni Zhang1, Yi-Xin Cai1, Yong-Yong Wang1, Yi-Tao Tian1, Xiao-Li Wang2, Benjamin Badami3.
Abstract
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.Entities:
Keywords: Convolutional neural networks; Deep learning; Lévy flight; Skin cancer diagnosis; Whale optimization algorithm
Mesh:
Year: 2019 PMID: 31980095 DOI: 10.1016/j.artmed.2019.101756
Source DB: PubMed Journal: Artif Intell Med ISSN: 0933-3657 Impact factor: 5.326