Deep Neural Network Based Diagnosis System for Melanoma Skin Cancer

被引:0
|
作者
Basturk, Alper [1 ]
Yuksel, Mehmet Emin [2 ]
Badem, Hasan [1 ,3 ]
Caliskan, Abdullah [2 ]
机构
[1] Erciyes Univ, Bilgisayar Muhendisligi Bolumu, Kayseri, Turkey
[2] Erciyes Univ, Biyomed Muhendisligi Bolumu, Kayseri, Turkey
[3] Sutcu Imam Univ, Bilgisayar Muhendisligi Bolumu, Kahramanmaras, Turkey
关键词
deep learning; deep neural network; ABCD rule; melanoma;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Melanoma is a serious cancer that causes many people to lose their lives. This disease can be diagnosed by a dermatologist as a result of interpretation of the dermoscopy images by the ABCD rule. In this study, a deep neural network (DNN) is used as a new method for diagnosis of melanoma skin cancer. This method is compared with the-state-art-methods in literature. According to the obtained results, DNN was more successful than the comparative methods.
引用
收藏
页数:4
相关论文
共 50 条
  • [1] Skin Cancer Diagnosis Based on Neutrosophic Features with a Deep Neural Network
    Singh, Sumit Kumar
    Abolghasemi, Vahid
    Anisi, Mohammad Hossein
    SENSORS, 2022, 22 (16)
  • [2] Artificial Neural Network Based Diagnostic System For Melanoma Skin Cancer
    Ileri, Ramis
    Latifoglu, Fatma
    Icer, Semra
    2019 MEDICAL TECHNOLOGIES CONGRESS (TIPTEKNO), 2019, : 25 - 28
  • [3] Skin cancer diagnosis based on optimized convolutional neural network
    Zhang, Ni
    Cai, Yi-Xin
    Wang, Yong-Yong
    Tian, Yi-Tao
    Wang, Xiao-Li
    Badami, Benjamin
    ARTIFICIAL INTELLIGENCE IN MEDICINE, 2020, 102 (102)
  • [4] Deep Neural Network for Fuzzy Automatic Melanoma Diagnosis
    Abbes, Wiem
    Sellami, Dorra
    VISAPP: PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS, VOL 4, 2019, : 47 - 56
  • [5] A Refined Approach for Classification and Detection of Melanoma Skin Cancer using Deep Neural Network
    Babar, Manahil
    Butt, Roha Tariq
    Batool, Hira
    Asghar, Muhammad Adeel
    Majeed, Abdul Raffay
    Khan, Muhammad Jamil
    2021 INTERNATIONAL CONFERENCE ON DIGITAL FUTURES AND TRANSFORMATIVE TECHNOLOGIES (ICODT2), 2021,
  • [6] Efficacy of a Deep Learning Convolutional Neural Network System for Melanoma Diagnosis in a Hospital Population
    Martin-Gonzalez, Manuel
    Azcarraga, Carlos
    Martin-Gil, Alba
    Carpena-Torres, Carlos
    Jaen, Pedro
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (07)
  • [7] A Deep Neural Network based Detection System for the Visual Diagnosis of the Blackberry
    Rubio, Alejandro
    Avendano, Carlos
    Martinez, Fredy
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2022, 13 (08) : 736 - 741
  • [8] Deep Hybrid Convolutional Neural Network for Segmentation of Melanoma Skin Lesion
    Yang, Cheng-Hong
    Ren, Jai-Hong
    Huang, Hsiu-Chen
    Chuang, Li-Yeh
    Chang, Po-Yin
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2021, 2021
  • [9] A Novel Deep Convolutional Neural Network for Diagnosis of Skin Disease
    Kodepogu, Koteswara Rao
    Annam, Jagadeeswara Rao
    Vipparla, Aruna
    Krishna, Bala Venkata Naga Vudata Suresh
    Kumar, Naresh
    Viswanathan, Ramya
    Gaddala, Lalitha Kumari
    Chandanapalli, Suresh Kumar
    TRAITEMENT DU SIGNAL, 2022, 39 (05) : 1873 - 1877
  • [10] Classification of Melanoma Skin Cancer using Convolutional Neural Network
    Refianti, Rina
    Mutiara, Achmad Benny
    Priyandini, Rachmadinna Poetri
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (03) : 409 - 417