2014
DOI: 10.1117/12.2042970
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Medical imaging document sharing solutions for various kinds of healthcare services based on IHE XDS/XDS-I profiles

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Cited by 3 publications
(3 citation statements)
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“…An interesting collection of topics presented included a remote volume rendering pipeline, 591 integration of medical images into a mobile device for bedside viewing, 592 and medical imaging document sharing using the IHE XDS profile. 593 Research data collections 594 and collaborative frameworks for data mining 595 were presented. Incorporating intelligence into structured radiology reports 596 was a paper of interest.…”
Section: S Pacs Conferencesmentioning
confidence: 99%
“…An interesting collection of topics presented included a remote volume rendering pipeline, 591 integration of medical images into a mobile device for bedside viewing, 592 and medical imaging document sharing using the IHE XDS profile. 593 Research data collections 594 and collaborative frameworks for data mining 595 were presented. Incorporating intelligence into structured radiology reports 596 was a paper of interest.…”
Section: S Pacs Conferencesmentioning
confidence: 99%
“…The developed system has been implemented and operated in 5 districts of Shanghai city for regional collaborative imaging diagnostic services [17][18] …”
Section: Grid-based Ihe Xds-i Image Sharing Solution For Collaborativmentioning
confidence: 99%
“…In the past few years, we studied implementation methods of the XDS-I profile and gave some preliminary results. 7 In this paper, we systemically present our full study about image sharing and exchange solutions for three image sharing scenarios, based on the IHE XDS-I profile, and also evaluate these solutions to determine whether the IHE XDS-I profile can serve as a foundation for medical image-sharing solutions across different regional health-care providers. These three scenarios include: (a) long-term health-care management across multiple hospitals and clinics; (b) patient-controlled image exchange between health-care providers and image data endusers; (c) telecollaboration for image diagnosis across multiple regional hospitals.…”
Section: Introductionmentioning
confidence: 99%