Anatomy of an Extensible Open Source PACS.

The conception and deployment of cost effective Picture Archiving and Communication Systems (PACS) is a concern for small to medium medical imaging facilities, research environments, and developing countries' healthcare institutions. Financial constraints and the specificity of these scenarios contr...

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Publicado en:Journal of Digital Imaging Vol. 29; no. 3; pp. 284 - 297
Autores principales: Valente, Frederico, Silva, Luís, Godinho, Tiago, Costa, Carlos
Formato: diagnostic images pictorial tables/charts Journal Article
Publicado: Springer Nature Jun2016
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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          Valente, Frederico
          Silva, Luís
          Godinho, Tiago
          Costa, Carlos
        affil: University of Aveiro DETI/IEETA, Aveiro Portugal
      sug:
        subj:
          Picture Archiving and Communication Systems
          Software Design
          DICOM
          Systems Implementation
          Information Retrieval
      ab: The conception and deployment of cost effective Picture Archiving and Communication Systems (PACS) is a concern for small to medium medical imaging facilities, research environments, and developing countries' healthcare institutions. Financial constraints and the specificity of these scenarios contribute to a low adoption rate of PACS in those environments. Furthermore, with the advent of ubiquitous computing and new initiatives to improve healthcare information technologies and data sharing, such as IHE and XDS-i, a PACS must adapt quickly to changes. This paper describes Dicoogle, a software framework that enables developers and researchers to quickly prototype and deploy new functionality taking advantage of the embedded Digital Imaging and Communications in Medicine (DICOM) services. This full-fledged implementation of a PACS archive is very amenable to extension due to its plugin-based architecture and out-of-the-box functionality, which enables the exploration of large DICOM datasets and associated metadata. These characteristics make the proposed solution very interesting for prototyping, experimentation, and bridging functionality with deployed applications. Besides being an advanced mechanism for data discovery and retrieval based on DICOM object indexing, it enables the detection of inconsistencies in an institution's data and processes. Several use cases have benefited from this approach such as radiation dosage monitoring, Content-Based Image Retrieval (CBIR), and the use of the framework as support for classes targeting software engineering for clinical contexts.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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