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Thin client (web browser)-based collaboration for medical imaging and web-enabled data.

Tuong Huu Le¹, Nadeem Malhi

¹Department of Radiology, University of California Medical School, San Francisco, CA 94143, USA. Tuong.Le@radiology.ucsf.edu

Journal of Digital Imaging

|July 10, 2002

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This study introduces a collaborative system for sharing medical images (DICOM) and other visuals with real-time markup. The thin client architecture enhances accessibility and streamlines image collaboration for medical professionals.

Area of Science:

Medical Imaging Technology
Web-based Collaboration Systems
Open Source Software

Background:

Sharing and annotating medical images (DICOM) is crucial for diagnosis and education.
Existing systems may lack real-time collaboration features or require substantial client-side resources.
The need for accessible, efficient image-sharing platforms in healthcare is growing.

Purpose of the Study:

To develop and implement a collaborative architecture for sharing DICOM and non-DICOM images.
To enable real-time markup and navigation capabilities within a web browser interface.
To leverage thin client software and open-source server technology for improved accessibility.

Main Methods:

Implemented a collaborative architecture using thin client software and open-source server technology.

Related Experiment Videos

Integrated web browser with DHTML, JavaScript, and Java for a thin client.

Utilized a web server/proxy server combination with Java Servlets and Java Server Pages for collaboration.

Developed a 'driver' role for navigation control and a 'passenger' role for viewing and markup.

Main Results:

Successfully enabled real-time sharing and markup of both DICOM and non-DICOM images.
The server-side processing ensured a thin and accessible client experience.
Facilitated collaborative sessions with controlled navigation and annotation.
Demonstrated the effectiveness of open-source components in building the collaborative platform.

Conclusions:

The implemented thin client architecture provides an accessible and efficient solution for medical image collaboration.
Web browser integration with open-source technologies enables robust real-time image sharing and markup.
This approach reduces client-side burden, making advanced collaboration tools more widely available.