The University of Southampton
University of Southampton Institutional Repository

Cloud Computing for brain segmentation technology

Cloud Computing for brain segmentation technology
Cloud Computing for brain segmentation technology
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.
Healthcare Cloud, brain segmentation technology by Cloud Computing, Medical Cloud Computing Education.
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4

Chang, Victor (2013) Cloud Computing for brain segmentation technology. At IEEE CloudCom 2013 IEEE CloudCom 2013. 02 - 05 Dec 2013.

Record type: Conference or Workshop Item (Paper)

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.

PDF VC_biomed_CloudCom13_revised_submission.pdf - Other
Download (201kB)

More information

Published date: 30 September 2013
Venue - Dates: IEEE CloudCom 2013, 2013-12-02 - 2013-12-05
Keywords: Healthcare Cloud, brain segmentation technology by Cloud Computing, Medical Cloud Computing Education.
Organisations: Electronics & Computer Science, Electronic & Software Systems

Identifiers

Local EPrints ID: 357188
URI: https://eprints.soton.ac.uk/id/eprint/357188
PURE UUID: 4bd867dc-af1b-417f-bd3d-63a169b63aad

Catalogue record

Date deposited: 21 Sep 2013 15:49
Last modified: 18 Jul 2017 03:34

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×