Volume 6, Issue 3, September 2018, Page: 25-32
An Effective Method for e-Medical Data Compression Using Wavelet Analysis
Ibrahim Abdulai Sawaneh, Department of Computer Science, Institute of Advanced Management and Technology (IAMTECH), Freetown, Sierra Leone
Received: Oct. 28, 2018;       Accepted: Nov. 13, 2018;       Published: Dec. 20, 2018
DOI: 10.11648/j.ijmi.20180603.12      View  44      Downloads  17
Abstract
The continuous utilization of massive patient data via telecommunication medium is raising a concern either in data transmission speed, storage, security and privacy. The introduction of Informatization, Internet of Things (IoT), Big Data Technology, and e-health require effective data compression techniques that will help solve the numerous challenges evident in the conventional medical image compression schemes. In order to successfully transmit medical data via the network of networks demands an efficient data compression mechanisms without reduction in the image quality with reduced size. This mechanism greatly minimizes costs, provides mobility and comfort to the users, increase speed in medical file transmission and lot of more. The research investigates the various medical image compression platforms so, as to achieve efficient and effective scheme. Medical image compression require more proactive scheme that maintains vital features of patients. Several compression methods were applied and Discrete Cosine Transform (DCT) proved to have a superior compression ratio as opposed to Discrete Wavelet Transform (DWT). The proposed study indicated that the recovered medical images had similar results compared to the original image data. Finally, the research mitigated data storage issue of hard drive, reduce transmission time, improved patient’s mobility and the high cost of medical hardware devices.
Keywords
Wavelet Transform, Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT)
To cite this article
Ibrahim Abdulai Sawaneh, An Effective Method for e-Medical Data Compression Using Wavelet Analysis, International Journal of Medical Imaging. Vol. 6, No. 3, 2018, pp. 25-32. doi: 10.11648/j.ijmi.20180603.12
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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