December 2002
Volume 43, Issue 13
ARVO Annual Meeting Abstract  |   December 2002
Evaluation of SVG Based Ophthalmic Image Annotation in Internet Based Multi-center Clinical Trials
Author Affiliations & Notes
  • P Jain
    INDENT INC Jacksonville FL
  • KV Chalam
    Ophthalmology University of Florida Jacksonville FL
  • S Gupta
    Ophthalmology University of Florida Jacksonville FL
  • Footnotes
    Commercial Relationships   P. Jain, None; K.V. Chalam, None; S. Gupta, None.
Investigative Ophthalmology & Visual Science December 2002, Vol.43, 4342. doi:
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      P Jain, KV Chalam, S Gupta; Evaluation of SVG Based Ophthalmic Image Annotation in Internet Based Multi-center Clinical Trials . Invest. Ophthalmol. Vis. Sci. 2002;43(13):4342.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract: : Purpose: To evaluate a Scalable Vector Graphics (SVG) based ophthalmic image annotation system for multiple patient visits in multiple centers as part of multi-center trails. Methods: Software solutions were introduced to a University based retina practice (UF-Jacksonville) enabling physicians to create rich annotations on fundus images. The annotated files were transmitted via web to a reading center (also in Jacksonville) and tracked over multiple patient visits. Annotations were created using a touch-screen stylus on a web browser in two components: annotation marking (drawing the boundary of a lesion with a stylus) and annotation properties (attributes associated with annotation marking that have been measured, read, or interpreted). Properties included the area of lesion, greatest dimension, or grading of pathology. Rich annotations were created using Scalable Vector Graphics (SVG). SVG as a standard was recently approved by the World Wide Web Consortium (W3C) for 2D graphics on the web. Results: Fundus images of patients with age related macular degeneration were successfully annotated, transmitted between separate facilities, retrieved, and clinically correlated on multiple patient visits reliably. Because SVG is an XML based language that is interpreted by the browser for drawing and annotating, SVG files are 1/10th the size of traditional bitmap based files (tif, jpeg). Amount of time needed to transmit annotations was much faster compared to standard systems (p<0.01). Conclusion: Ophthalmic Image Annotation is clinically feasible and useful to interpret and track image data between multiple sites over multiple patient visits, such as in multi-center clinical trials.

Keywords: 429 image processing • 430 imaging/image analysis: clinical • 431 imaging/image analysis: non-clinical 

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