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ThinkMind // DBKDA 2012, The Fourth International Conference on Advances in Databases, Knowledge, and Data Applications // View article dbkda_2012_8_20_30087


Cloud-based Medical Image Collection Database with Automated Annotation

Authors:
Anthony Maeder
Birgit Planitz

Keywords: medical imaging; content based image retrieval; cloud computing

Abstract:
Typical medical image annotation systems use manual annotation or complex proprietary software such as computer-assisted-diagnosis. A more objective approach is required to achieve generalised Content Based Image Retrieval (CBIR) functionality. The Automated Medical Image Collection Annotation (AMICA) toolkit described here addresses this need. A range of content analysis functions are provided to tag images and image regions. The user uploads a DICOM file to an online portal and the software finds and displays images that have similar characteristics. AMICA has been developed to run in the Microsoft cloud environment using the Windows Azure platform, to cater for the storage requirements of typical large medical image databases.

Pages: 182 to 186

Copyright: Copyright (c) IARIA, 2012

Publication date: February 29, 2012

Published in: conference

ISSN: 2308-4332

ISBN: 978-1-61208-185-4

Location: Saint Gilles, Reunion

Dates: from February 29, 2012 to March 5, 2012

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