Skin cancer diagnosis based on optimized convolutional neural network.

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...

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Publicado en:Artificial Intelligence in Medicine Vol. 102
Autores principales: Zhang, Ni, Cai, Yi-Xin, Wang, Yong-Yong, Tian, Yi-Tao, Wang, Xiao-Li, Badami, Benjamin
Formato: research Journal Article
Publicado: Elsevier B.V. Jan2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jan2020
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      pub: Elsevier B.V.
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        atl: Skin cancer diagnosis based on optimized convolutional neural network.
      aug:
        au:
          Zhang, Ni
          Cai, Yi-Xin
          Wang, Yong-Yong
          Tian, Yi-Tao
          Wang, Xiao-Li
          Badami, Benjamin
        affil: Department of Throracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, Hubei 430030, China
      sug:
        subj:
          Skin Neoplasms Diagnosis
          Mammals
          Behavior
          Carcinoma Diagnosis
          Early Diagnosis
          Human
          Computer Simulation
          Resource Databases
          Image Processing, Computer Assisted
          Diagnosis, Computer Assisted
          Algorithms
          Melanoma Diagnosis
          Animal Studies
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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