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Collaborative telemedicine for interactive multiuser segmentation of volumetric medical images

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Abstract

Telemedicine has evolved rapidly in recent years to enable unprecedented access to digital medical data, such as with networked image distribution/sharing and online (distant) collaborative diagnosis, largely due to the advances in telecommunication and multimedia technologies. However, interactive collaboration systems which control editing of an object among multiple users are often limited to a simple “locking” mechanism based on a conventional client/server architecture, where only one user edits the object which is located in a specific server, while all other users become viewers. Such systems fail to provide the needs of a modern day telemedicine applications that demand simultaneous editing of the medical data distributed in diverse local sites. In this study, we introduce a novel system for telemedicine applications, with its application to an interactive segmentation of volumetric medical images. We innovate by proposing a collaborative mechanism with a scalable data sharing architecture which makes users interactively edit on a single shared image scattered in local sites, thus enabling collaborative editing for, e.g., collaborative diagnosis, teaching, and training. We demonstrate our collaborative telemedicine mechanism with a prototype image editing system developed and evaluated with a user case study. Our result suggests that the ability for collaborative editing in a telemedicine context can be of great benefit and hold promising potential for further research.

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Authors and Affiliations

  1. MIRALab, University of Geneva, Geneva, Switzerland

    Seunghyun Han, Niels A. Nijdam, Jérôme Schmid, Jinman Kim & Nadia Magnenat-Thalmann

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  1. Seunghyun Han
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  2. Niels A. Nijdam
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  3. Jérôme Schmid
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  4. Jinman Kim
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  5. Nadia Magnenat-Thalmann
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Correspondence to Seunghyun Han.

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Han, S., Nijdam, N.A., Schmid, J. et al. Collaborative telemedicine for interactive multiuser segmentation of volumetric medical images. Vis Comput 26, 639–648 (2010). https://doi.org/10.1007/s00371-010-0445-y

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