Data Compression as a Base for eHealth Interoperability: 3D FWT Applied on Volumetric Neuroimages

Data Compression as a Base for eHealth Interoperability: 3D FWT Applied on Volumetric Neuroimages

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
DOI: 10.4018/978-1-5225-0498-6.ch010
OnDemand PDF Download:
$30.00
List Price: $37.50

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.
Chapter Preview
Top

Background

Application of ICT in health care and improving the overall health system and services are nowadays defined in most national strategies for the development of health in the world. Following this, eHealth as a set of systems and services that enable the sharing of medical diagnostic imaging data remotely is an important factor in the achievement of these strategies. 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. The increased availability of medical imaging technologies that yield 4D data (3D + time), combined with the low-bandwidth requirements of telemedicine, generate demands for new medical image compression methods. Medical imaging generates large amounts of data. An MRI study can contain up to several gigabytes (GB). The obtained image data together with other metadata (about the patient) packed in standardized formats such as DICOM and NIfTI are stored in a centralized data repository. From there the needed data are sent to the client device (PC) and presented to a specialist who performs diagnostics. 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 (Žagar, 2012). The application of mobile devices (e.g. tablet) as client devices in recent years has also become possible and interesting due to their increasing computational capabilities. It allows reading of diagnostic data and diagnostics at any place and at any time without restriction (Žagar, 2011). In such applications, the need for data compression is even more stressed because of the limited communication opportunities (cellular networks, wireless networks), and the limited storage capacity of the current study data for these client devices. 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). Communicated data are meant to be finally decompressed and displayed on mobile devices with limited computational capabilities (Knezović, 2011).

Complete Chapter List

Search this Book:
Reset