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Data Compression as a Base for eHealth Interoperability: 3D FWT Applied on Volumetric Neuroimages
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Author(s): Martin Žagar (University of Applied Sciences, Croatia), Branko Mihaljević (Rochester Institute of Technology, Croatia)and Josip Knezović (University of Zagreb, Croatia)
Copyright: 2017
Pages: 16
Source title:
Intelligent Analysis of Multimedia Information
Source Author(s)/Editor(s): Siddhartha Bhattacharyya (RCC Institute of Information Technology, India), Hrishikesh Bhaumik (RCC Institute of Information Technology, India), Sourav De (The University of Burdwan, India)and Goran Klepac (University College for Applied Computer Engineering Algebra, Croatia & Raiffeisenbank Austria, Croatia)
DOI: 10.4018/978-1-5225-0498-6.ch010
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Abstract
eHealth is a set of systems and services that enable the sharing of medical diagnostic imaging data remotely. The application of eHealth solves the problem of the lack of specialized personnel, unnecessary execution of multiple diagnostic imaging and rapid exchange of information and remote diagnostics. Medical imaging generates large amounts of data. An MRI study can contain up to several Gigabytes (GB). The exchange of such large amounts of data in the local network facilities is a significant problem due to bandwidth sharing which is even more significant in mobile and wireless networks. A possible solution to this problem is data compression with the requirement that there is no loss of data. The goal of this chapter is a conceptual compression prototype that will allow faster and more efficient exchange of medical images in systems with limited bandwidth and communication speeds (cellular networks, wireless networks). To obtain this conceptual compression prototype we will use wavelets.
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