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A Hybrid Data Model to Share Medical Images

by D. Revina Rebecca, I. Elizabeth Shanthi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 161 - Number 9
Year of Publication: 2017
Authors: D. Revina Rebecca, I. Elizabeth Shanthi
10.5120/ijca2017913300

D. Revina Rebecca, I. Elizabeth Shanthi . A Hybrid Data Model to Share Medical Images. International Journal of Computer Applications. 161, 9 ( Mar 2017), 31-36. DOI=10.5120/ijca2017913300

@article{ 10.5120/ijca2017913300,
author = { D. Revina Rebecca, I. Elizabeth Shanthi },
title = { A Hybrid Data Model to Share Medical Images },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2017 },
volume = { 161 },
number = { 9 },
month = { Mar },
year = { 2017 },
issn = { 0975-8887 },
pages = { 31-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume161/number9/27179-2017913300/ },
doi = { 10.5120/ijca2017913300 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:07:01.670080+05:30
%A D. Revina Rebecca
%A I. Elizabeth Shanthi
%T A Hybrid Data Model to Share Medical Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 161
%N 9
%P 31-36
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The challenges involved in effectively storing, retrieving and sharing medical images have led the researchers to look into various means and methods of doing the same. It is the need of the hour for a hybrid data model which will solve all the challenges involved in it. In the previous work the suitability of using NoSQL databases in storing and retrieval of medical images was analyzed. It was found the MongoDB, A NoSQL database suitable to handle medical images. It is also necessary to look for a better way to transfer medical images. Since medical images are huge, it is a challenge to share it with minimal latency. A Model based on a distributed strategy using the sharding environment is proposed. It may be considered to be a hybrid data model using MongoDB to share and handle medical images. This data model is based on storing and retrieving using parallel processing and distributing the data across many machines. The aim of this paper is to study the effectiveness of the sharding or distributed processing concepts available in the NoSQL databases and how it helps us to enhance the bandwidth in sharing of huge medical images.

References
  1. Oleg S. P ianykh,"Digital Imaging and Communications in Medicine (DlCOM), A Practical Introduction and Survival Guide ", book published by Springer-Verlag Berlin Heidelberg, pp 247-261, 2008 and 2012
  2. Yimeng Liu, Yizhi Wang,Yi Jin, Research on The Improvement of MongoDB Auto-Sharding in Cloud Environment, IEEE, 978-1-4673-0242-5-2012
  3. Kristina Chodrow, Michael Dirolf, Scaling MongoDB.
  4. Alexandre Savaris, Theo Härder, Aldo von Wangenheim, DCMDSM:A DICOM decomposed storage model, Journal of the American Medical Informatics Association · February 2014
  5. Alexandre Savaris, Gabriela Bussolo Colonetti, Rodrigo Rodrigues Pires de Mello, Aldo von Wangenheim Relational Databases versus Search Engines: A Performance Comparison for Storing and Querying DICOM Metadata
  6. D.Revina Rebecca, I.Elizabeth Shanthi,A NoSQL Solution to efficient storage and retrieval of Medical Images,International Journal of Scientific & Engineering Research, Volume 7, Issue 2, February-2016,ISSN 2229-5518
  7. Liliana BYCZKOWSKA-LIPIŃSKA, Agnieszka WOSIAK, Multimedia NoSQL database solutions in the medical imaging data analysis
  8. Simón J. Rascovsky, MD, MSc • Jorge A. Delgado, MD • Alexander Sanz, BS • Víctor D. Calvo, BS • Gabriel Castrillón, BS,Use of CouchDB for Document-based Storage of DICOM Objects
  9. Luís A. Bastião Silva, Louis Beroud, Carlos Costa and José Luis Oliveira,Medical imaging archiving: a comparison between several NoSQL,978-1-4799-2131-7/14/$31.00 ©2014 IEEE.
  10. Luan Henrique Santos Simões de Almeidaa, Marcelo Costa Oliveiraa, A Medical Image Backup Architecture Based on a NoSQL Database and Cloud Computing Services, MEDINFO 2015: eHealth-enabled Health, doi:10.3233/978-1-61499-564-7-929.
  11. Marcosa E., Acuna C.J., Vela B., Caveroa J. M., Hermandez J.A.: A database for medical image management, Computer methods and programs in biomedicine, vol. 86, pp: 255-269, 2007 Elsevier Ireland Ltd
  12. D.Revina Rebecca, I.Elizabeth Shanthi , Analysing the suitability of storing Medical Images in NoSQL Databases, International Journal of Scientific & Engineering Research, Volume 7, Issue 6, June-2016,ISSN 2229-5518
  13. http://www.siemens.com/innovation/en/home/pictures-of-the-future/health-and-well-being/medical-imaging-facts-and-forecasts.html
  14. Yan Hu, Fangjie Lu, Israr Khan, Guohua Bai, A Cloud Computing Solution for Sharing Healthcare Information
  15. D.Revina Rebecca et al, Impact of adapting Cloud Computing in health care industry for storing medical Images.
  16. Dandu Ravi Varma, Managing DICOM images: Tips and tricks for the radiologist, Indian J Radiol Imaging. 2012 Jan-Mar; 22(1): 4–13, doi:  10.4103/0971-3026.95396.
Index Terms

Computer Science
Information Sciences

Keywords

DICOM Cloud Computing MongoDB Chunked Storage sharding parallel processing Medical Images.

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