Optimization of PACS Data Persistency Using Indexed Hierarchical Data.

We present a new approach for the development of a data persistency layer for a Digital Imaging and Communications in Medicine (DICOM)-compliant Picture Archiving and Communications Systems employing a hierarchical database. Our approach makes use of the HDF5 hierarchical data storage standard for s...

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Bibliographic Details
Published in:Journal of Digital Imaging Vol. 27; no. 3; pp. 297 - 309
Main Authors: Prado, Thiago, Macedo, Douglas, Dantas, M., Wangenheim, Aldo
Format: pictorial tables/charts Journal Article
Published: Springer Nature Jun2014
Online Access:View this record in EBSCOhost
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      dt: Jun2014
      vid: 27
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10278-013-9665-9
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        atl: Optimization of PACS Data Persistency Using Indexed Hierarchical Data.
      aug:
        au:
          Prado, Thiago
          Macedo, Douglas
          Dantas, M.
          Wangenheim, Aldo
        affil: Department of Informatics and Statistics, INE, Florianópolis Brazil
      sug:
        subj:
          Picture Archiving and Communication Systems Brazil
          Data Management
          Access to Information
          Brazil
          Telehealth Brazil
          Metadata
          Information Storage
          Telemedicine
          Abstracting and Indexing
          Information Retrieval
      ab: We present a new approach for the development of a data persistency layer for a Digital Imaging and Communications in Medicine (DICOM)-compliant Picture Archiving and Communications Systems employing a hierarchical database. Our approach makes use of the HDF5 hierarchical data storage standard for scientific data and overcomes limitations of hierarchical databases employing inverted indexing for secondary key management and for efficient and flexible access to data through secondary keys. This inverted indexing is achieved through a general purpose document indexing tool called Lucene. This approach was implemented and tested using real-world data against a traditional solution employing a relational database, in various store, search, and retrieval experiments performed repeatedly with different sizes of DICOM datasets. Results show that our approach outperforms the traditional solution on most of the situations, being more than 600 % faster in some cases.
      pubtype: Academic Journal
      doctype:
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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