Collaborative compressed I-cloud medical image storage with decompress viewer

Israna Hossain Arka, Kalaivani Chell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

Healthcare collaborative approach is anticipated to be an appropriate solution for disease management structure in the growing global population. Efficient disease management structure needs deep analytical skills in making effective decisions based on medical data. The nature of medical data being huge in size has been categorized as big data. Big data management in a collaborative environment needs multiple technological integrations. In this paper we have proposed an independent cloud based collaborative medical image storage and mobile viewer assisted with effective compression and decompression technique with unique security structure design. The proposed design has considered deep technology exploitation to offer medical image access via mobile devices by considering all the current constraints in terms of storage, image clarity and security. The proposed architecture allows both patient and medical practioners to have a cost effective approach in disease management and treatment process. It also introduces healthcare analysts and practitioners to the advancements in the computing field to effectively handle and make inferences from voluminous and heterogeneous healthcare data. Due to the broad nature of the topic, our primary emphasis will be on introducing healthcare data repositories, challenges, and concepts in data science. Not much focus will be on describing the details of any particular techniques and/or solutions in image compression, security and the medical field in particular other than convenient data access opportunity framework.

Original languageEnglish
Title of host publicationProcedia Computer Science
PublisherElsevier
Pages114-121
Number of pages8
Volume42
EditionC
DOIs
Publication statusPublished - 2014
EventInternational Symposium on Medical and Rehabilitation Robotics and Instrumentation, MRRI 2013 - Shah Alam, Malaysia
Duration: 2 Dec 20134 Dec 2013

Other

OtherInternational Symposium on Medical and Rehabilitation Robotics and Instrumentation, MRRI 2013
CountryMalaysia
CityShah Alam
Period2/12/134/12/13

Fingerprint

Image compression
Mobile devices
Information management
Decision making
Costs
Big data

Keywords

  • Cloud storage
  • Collaborative
  • Compression
  • Data security
  • Decompression
  • Medical imaging
  • Mobile devices

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Arka, I. H., & Chell, K. (2014). Collaborative compressed I-cloud medical image storage with decompress viewer. In Procedia Computer Science (C ed., Vol. 42, pp. 114-121). Elsevier. https://doi.org/10.1016/j.procs.2014.11.041

Collaborative compressed I-cloud medical image storage with decompress viewer. / Arka, Israna Hossain; Chell, Kalaivani.

Procedia Computer Science. Vol. 42 C. ed. Elsevier, 2014. p. 114-121.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Arka, IH & Chell, K 2014, Collaborative compressed I-cloud medical image storage with decompress viewer. in Procedia Computer Science. C edn, vol. 42, Elsevier, pp. 114-121, International Symposium on Medical and Rehabilitation Robotics and Instrumentation, MRRI 2013, Shah Alam, Malaysia, 2/12/13. https://doi.org/10.1016/j.procs.2014.11.041
Arka, Israna Hossain ; Chell, Kalaivani. / Collaborative compressed I-cloud medical image storage with decompress viewer. Procedia Computer Science. Vol. 42 C. ed. Elsevier, 2014. pp. 114-121
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