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Image and Signal Processing for Networked eHealth ApplicationsMedical Data Encoding for Transmission

Image and Signal Processing for Networked eHealth Applications: Medical Data Encoding for... CHAP TE R 3 Medical Data Encoding for Transmission 3.1 INTRODUCTION Medical information, especially in time-varying or multidimensional and multiresolution forms, typically creates large databases and requires relevant storage media and strategies. High quality stereo sound, for example, is sampled in 44 kHz, with 16 bits allocated per sample and two channels combined to produce the final file; a simple multiplication shows that this acquisition scenario produces data at 1.4 Mb/s. In the same framework, uncompressed NTSC TV signal at 30 frames/s utilizes almost 300 Mb/s, while for quarter-frame sizes, e.g. webcams, this drops to almost 73 Mb/s. Different applications may impose additional requirements: for example, machine-learning techniques may well operate offline and thus alleviate the need for real time availability, while emergency processing for early detection needs as much as data as possible on demand. In the case of transmission, the choice of medium is another critical factor, since the difference in bandwidth capacity between T3 networks and normal telephony networks (PSTN) is in the order of 1000 to 1. Data compression may be an obvious option here, but this also presents a number of interesting questions, especially when lossy compression techniques are put to use, thereby removing http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Image and Signal Processing for Networked eHealth ApplicationsMedical Data Encoding for Transmission

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Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2006
ISBN
978-3-031-00481-0
Pages
11 –15
DOI
10.1007/978-3-031-01609-7_3
Publisher site
See Chapter on Publisher Site

Abstract

CHAP TE R 3 Medical Data Encoding for Transmission 3.1 INTRODUCTION Medical information, especially in time-varying or multidimensional and multiresolution forms, typically creates large databases and requires relevant storage media and strategies. High quality stereo sound, for example, is sampled in 44 kHz, with 16 bits allocated per sample and two channels combined to produce the final file; a simple multiplication shows that this acquisition scenario produces data at 1.4 Mb/s. In the same framework, uncompressed NTSC TV signal at 30 frames/s utilizes almost 300 Mb/s, while for quarter-frame sizes, e.g. webcams, this drops to almost 73 Mb/s. Different applications may impose additional requirements: for example, machine-learning techniques may well operate offline and thus alleviate the need for real time availability, while emergency processing for early detection needs as much as data as possible on demand. In the case of transmission, the choice of medium is another critical factor, since the difference in bandwidth capacity between T3 networks and normal telephony networks (PSTN) is in the order of 1000 to 1. Data compression may be an obvious option here, but this also presents a number of interesting questions, especially when lossy compression techniques are put to use, thereby removing

Published: Jan 1, 2006

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