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Big Data Analytics in Telemedicine: A Role of Medical Image Compression

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Big Data Management

Abstract

Big data analytics which is one of most rapidly expanding field has started to play a vital role in the field of healthcare. A major goal of telemedicine is to eliminate unnecessary travelling of patients and their escorts. Data acquisition, data storage, data display and processing, and data transfer represent the basis of telemedicine. Telemedicine hinges on transfer of text, reports, voice, images and video, between geographically separated locations. Out of these, the simplest and easiest is through text, as it is quick and simple to use, since sending text requires very little bandwidth. The problem with images and videos is that they require a large amount of bandwidth, for transmission and reception. Therefore, there is a need to reduce the size of the image that is to be sent or received i.e. data compression is necessary. This chapter deals with employing prediction as a method for compression of biomedical images. The approach presented in this chapter offers great potential in complete lossless compression of the medical image under consideration, without degrading the diagnostic ability of the image.

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Authors and Affiliations

  1. E&TC Department, AISSMS-Institute of Information Technology, Pune, India

    Vinayak K. Bairagi

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  1. Vinayak K. Bairagi
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Correspondence to Vinayak K. Bairagi .

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Editors and Affiliations

  1. ETSI Industriales de Ciudad Real, University of Castilla-La Mancha, Ciudad Real, Spain

    Fausto Pedro García Márquez

  2. Drexel University, Philadelphia, Pennsylvania, USA

    Benjamin Lev

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Bairagi, V.K. (2017). Big Data Analytics in Telemedicine: A Role of Medical Image Compression. In: García Márquez, F., Lev, B. (eds) Big Data Management . Springer, Cham. https://doi.org/10.1007/978-3-319-45498-6_7

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