• DocumentCode
    3435603
  • Title

    Cloud Computing for Brain Segmentation Technology

  • Author

    Chang, V.

  • Author_Institution
    Sch. of Comput., Creative Technol. & Eng., Leeds Metropolitan Univ., Leeds, UK
  • Volume
    1
  • fYear
    2013
  • fDate
    2-5 Dec. 2013
  • Firstpage
    499
  • Lastpage
    504
  • Abstract
    This paper introduces the brain segmentation technology offered by Cloud Computing. It explains eleven APIs associated with each brain segment, as well as the process of capturing data in regard to each segment. Functionality and experiments associated with each API are discussed. Dancing is chosen because data related to fast and skilled movements can be captured more easily. The results captured for each brain segment are discussed and used to explain why some segments are more active in dancing. With an emphasis in testing to ensure a high quality of data analysis and visualization, eleven Cloud APIs can produce results quickly, accurately and effectively. Simulations for brain segmentations can be used by Medical Cloud Computing Education (MCCE). Results of analysis confirms that Cloud Computing can offer 20% improvement in learning satisfaction. Benefits of using Cloud brain segmentation technology are presented. The use of Cloud Computing can make positive impacts to healthcare informatics and education.
  • Keywords
    application program interfaces; brain; cloud computing; data analysis; data visualisation; health care; medical computing; MCCE; cloud APIs; cloud brain segmentation technology; cloud computing; data analysis; data visualization; healthcare informatics; medical cloud computing education; Brain; Cloud computing; Data visualization; Educational institutions; Medical services; Standards; Healthcare Cloud; Medical Cloud Computing Education; brain segmentation technology by Cloud Computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2013 IEEE 5th International Conference on
  • Conference_Location
    Bristol
  • Type

    conf

  • DOI
    10.1109/CloudCom.2013.110
  • Filename
    6753838