Biomedical image visualization as a web application

We aim at building the Web-based Laboratory Information System (LIS) and Radiology Information System (RIS). It is challenging to make the functionality of the dedicated imaging and visualization programs compiled from a native programming language publicly available via a Web based interface. Acces...

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Bibliographic Details
Main Authors: Yadav, Kuleesha, Feng, Lin
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/97725
http://hdl.handle.net/10220/17097
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Institution: Nanyang Technological University
Language: English
Description
Summary:We aim at building the Web-based Laboratory Information System (LIS) and Radiology Information System (RIS). It is challenging to make the functionality of the dedicated imaging and visualization programs compiled from a native programming language publicly available via a Web based interface. Accessing information of the original image data and algorithmic details should be hidden, thus scripts executed by the webpage browser should be avoided. In this regard, we propose a solution based on the ASP.NET framework. Managed codes in C# are developed for Web controls, server-side GUI and relational database management; whereas unmanaged server-dependent imaging programs are invoked from within the managed programs. We present such a Web application for biomedical imaging and visualization, addressing its capability of implementing comprehensive image processing algorithms at the server side where proprietary datasets reside and direct access to them by client-side applications is restricted. The advantages of such a Web application include (a) high security of the proprietary data which is always a primary consideration in deployment of a networked system, (b) thin-client strategy in which heavy computing tasks are completed on the dedicated server with highperformance hardware, and (c) less demand for network bandwidth as only the rendering results instead of multiple high-dimensional datasets need to be transferred.