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A Cloud Scalable Platform for DICOM Image Analysis as a Tool for Remote Medical Support

Authors:
Iuliana Ojog
Miguel Arias-Estrada
Jesus Gonzalez
Beatriz Flores

Keywords: DICOM; X3D; WebGL; HTML5; 3D graphics; mobile medical applications; medical cloud DICOM processing; GPU processing on the cloud; Amazon AWS.

Abstract:
Remote diagnosis has become an important research field to provide high quality health care services to larger communities. Even when the importance of providing these services is undisputed, the computational cost of performing such processes is high. In order to deliver this kind of services, we present a scalable platform in the cloud able to process DICOM files with a modular structure. Our platform extracts and processes relevant information from the DICOM file to be used for support in diagnosis in medical applications. The paper presents a discussion about the cloud infrastructures and our choice of storage and HPC processing capabilities on Amazon AWS infrastructure. We also propose an HTML5 and WebGL web based access interface to allow remote access, visualization and manipulation from the user side, but keeping the computational cost on the cloud. The platform offers Cloud processing for computationally expensive tasks (from DICOM image segmentation to data mining in order to extract relevant information from the DICOM file). We present a basic proof of concept and describe the relevant modules of our platform.

Pages: 246 to 249

Copyright: Copyright (c) IARIA, 2013

Publication date: February 24, 2013

Published in: conference

ISSN: 2308-4359

ISBN: 978-1-61208-252-3

Location: Nice, France

Dates: from February 24, 2013 to March 1, 2013