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A Parallel Method to Improve Medical Image Transmission

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Abstract

The staggering number of images acquired by modern modalities requires new approaches for medical data transmission. There have been several attempts to improve data transmission time between medical imaging systems. These attempts were mostly based on compression. Although the compression methods can help in many cases, they are sometimes ineffectual in high-speed networks. This paper introduces parallelism to provide an effective method of medical data transmission over both local area network (LAN) and wide area network (WAN). It is based on the Digital Imaging and Communications in Medicine (DICOM) protocol and uses parallel TCP connections in storage services within the protocol. Using the proposed interface in our method, current medical imaging applications can take advantage of parallelism without any modification. Experimental results show a speedup of about 1.3 to 1.5 for CT images and relatively high speedup of about 2.2 to 3.5 times for magnetic resonance (MR) images over LAN. The transmission time is improved drastically over WAN. The speedup is about 16.1 for CT images and about 5.6 to 11.5 for MR images.

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Authors and Affiliations

  1. Department of Computer Science, E2-445 EITC, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada

    Rouzbeh Maani, Sergio Camorlinga & Neil Arnason

  2. TRLabs, 100-135 Innovation Drive, Winnipeg, MB, Canada

    Rouzbeh Maani, Sergio Camorlinga & Neil Arnason

  3. Radiology Department, Faculty of Medicine, University of Manitoba, Winnipeg, MB, Canada

    Sergio Camorlinga

  4. Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada

    Rouzbeh Maani

Authors
  1. Rouzbeh Maani
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  2. Sergio Camorlinga
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  3. Neil Arnason
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Correspondence to Rouzbeh Maani.

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Maani, R., Camorlinga, S. & Arnason, N. A Parallel Method to Improve Medical Image Transmission. J Digit Imaging 25, 101–109 (2012). https://doi.org/10.1007/s10278-011-9387-9

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  • DOI: https://doi.org/10.1007/s10278-011-9387-9

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