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Five Levels of PACS Modularity: Integrating 3D and Other Advanced Visualization Tools

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Abstract

The current array of PACS products and 3D visualization tools presents a wide range of options for applying advanced visualization methods in clinical radiology. The emergence of server-based rendering techniques creates new opportunities for raising the level of clinical image review. However, best-of-breed implementations of core PACS technology, volumetric image navigation, and application-specific 3D packages will, in general, be supplied by different vendors. Integration issues should be carefully considered before deploying such systems. This work presents a classification scheme describing five tiers of PACS modularity and integration with advanced visualization tools, with the goals of characterizing current options for such integration, providing an approach for evaluating such systems, and discussing possible future architectures. These five levels of increasing PACS modularity begin with what was until recently the dominant model for integrating advanced visualization into the clinical radiologist's workflow, consisting of a dedicated stand-alone post-processing workstation in the reading room. Introduction of context-sharing, thin clients using server-based rendering, archive integration, and user-level application hosting at successive levels of the hierarchy lead to a modularized imaging architecture, which promotes user interface integration, resource efficiency, system performance, supportability, and flexibility. These technical factors and system metrics are discussed in the context of the proposed five-level classification scheme.

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Acknowledgments

KCW gratefully acknowledges the support of RSNA Research and Education Foundation Fellowship Training Grant #FT0904, as well as that of the Walter and Mary Ciceric Research Award.

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Correspondence to Kenneth C. Wang.

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Wang, K.C., Filice, R.W., Philbin, J.F. et al. Five Levels of PACS Modularity: Integrating 3D and Other Advanced Visualization Tools. J Digit Imaging 24, 1096–1102 (2011). https://doi.org/10.1007/s10278-011-9366-1

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