GPU Accelerated real-time Melanoma Detection

  • Authors

    • Ajai Sunny Joseph Mar Athanasius College of Engineering
    • Elizabeth Isaac
    2018-06-27
    https://doi.org/10.14419/ijet.v7i3.13169
  • Cancer Detection, GPU, Melanoma, Skin Cancer, Deep Learning

  • Abstract

    Melanoma is recognized as one of the most dangerous type of skin cancer. A novel method to detect melanoma in real time with the help of Graphical Processing Unit (GPU) is proposed. Existing systems can process medical images and perform a diagnosis based on Image Processing technique and Artiï¬cial Intelligence. They are also able to perform video processing with the help of large hardware resources at the backend. This incurs signiï¬cantly higher costs and space and are complex by both software and hardware. Graphical Processing Units have high processing capabilities compared to a Central Processing Unit of a system. Various approaches were used for implementing real time detection of Melanoma. The results and analysis based on various approaches and the best approach based on our study is discussed in this work. A performance analysis for the approaches on the basis of CPU and GPU environment is also discussed. The proposed system will perform real-time analysis of live medical video data and performs diagnosis. The system when implemented yielded an accuracy of 90.133% which is comparable to existing systems.

     

     

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  • How to Cite

    Sunny Joseph, A., & Isaac, E. (2018). GPU Accelerated real-time Melanoma Detection. International Journal of Engineering & Technology, 7(3), 1208-1215. https://doi.org/10.14419/ijet.v7i3.13169

    Received date: 2018-05-23

    Accepted date: 2018-06-18

    Published date: 2018-06-27