Anatomy of an Extensible Open Source PACS

被引:38
|
作者
Valente, Frederico [1 ,2 ]
Bastiao Silva, Luis A. [1 ]
Godinho, Tiago Marques [1 ]
Costa, Carlos [1 ]
机构
[1] Univ Aveiro DETI IEETA, Aveiro, Portugal
[2] Inst Engn Elect & Telemat Aveiro, Campus Univ Santiago, P-3810193 Aveiro, Portugal
关键词
PACS; Digital Imaging and Communications in Medicine (DICOM); PACS implementation; PACS integration; PACS service; Radiation dose; Software design; OPEN-SOURCE SOFTWARE; COMMUNICATION; SYSTEM; IMPLEMENTATION; TELERADIOLOGY; INTEGRATION; MOBILE;
D O I
10.1007/s10278-015-9834-0
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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.
引用
收藏
页码:284 / 296
页数:13
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