Brain Segmentation – A Case study of Biomedical Cloud Computing for Education and Research
Brain Segmentation – A Case study of Biomedical Cloud Computing for Education and Research
Medical imaging is widely adopted in Hospitals and medical institutes, and new ways to improve existing medical imaging services are regularly exploited. This paper describes the adoption of Cloud Computing is useful for medical education and research, and describes the methodology, results and lesson learned. A working Bioinformatics Cloud platform can demonstrate computation and visualisation of brain imaging. The aim is to study segmentation of brains, which divides the brain into ten major regions. The Cloud platform has these two functions: (i) it can highlight each region for ten different segments; and (ii) it can adjust intensity of segmentation to allow basic study of brain medicine. Two types of benefits are reported as follows. Firstly, all the medical student participants are reported to have 20% improvement in their learning satisfaction. Secondly, 100% of volunteer participants are reported to have positive learning experience.
Keywords
Brain Segmentation, Medical Cloud Computing Education (MCCE), Cloud Computing Brain Segmentation Technology (CCBST).
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
6 June 2013
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Chang, Victor
(2013)
Brain Segmentation – A Case study of Biomedical Cloud Computing for Education and Research.
Learning Technologies Workshop, Higher Education Academy (HEA), University of Greenwich.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Medical imaging is widely adopted in Hospitals and medical institutes, and new ways to improve existing medical imaging services are regularly exploited. This paper describes the adoption of Cloud Computing is useful for medical education and research, and describes the methodology, results and lesson learned. A working Bioinformatics Cloud platform can demonstrate computation and visualisation of brain imaging. The aim is to study segmentation of brains, which divides the brain into ten major regions. The Cloud platform has these two functions: (i) it can highlight each region for ten different segments; and (ii) it can adjust intensity of segmentation to allow basic study of brain medicine. Two types of benefits are reported as follows. Firstly, all the medical student participants are reported to have 20% improvement in their learning satisfaction. Secondly, 100% of volunteer participants are reported to have positive learning experience.
Text
VC_medical_education_by_Cloud_submission.pdf
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More information
Accepted/In Press date: 23 April 2013
Published date: 6 June 2013
Venue - Dates:
Learning Technologies Workshop, Higher Education Academy (HEA), University of Greenwich, 2013-04-23
Keywords:
Keywords
Brain Segmentation, Medical Cloud Computing Education (MCCE), Cloud Computing Brain Segmentation Technology (CCBST).
Organisations:
Electronics & Computer Science
Identifiers
Local EPrints ID: 351752
URI: http://eprints.soton.ac.uk/id/eprint/351752
PURE UUID: f8b256cf-e05d-4a8b-a89c-be24d0152e32
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Date deposited: 24 Apr 2013 09:59
Last modified: 14 Mar 2024 13:42
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Contributors
Author:
Victor Chang
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