May 2007
Volume 48, Issue 13
ARVO Annual Meeting Abstract  |   May 2007
Efficient Automatic Image Transfer of Digital Fundus Photos Over the Internet for Clinical Trials
Author Affiliations & Notes
  • B. Madjarov
    Ophthalmology, Scheie Eye Institute, Philadelphia, Pennsylvania
  • Footnotes
    Commercial Relationships B. Madjarov, None.
  • Footnotes
    Support None.
Investigative Ophthalmology & Visual Science May 2007, Vol.48, 2583. doi:
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    • Get Citation

      B. Madjarov; Efficient Automatic Image Transfer of Digital Fundus Photos Over the Internet for Clinical Trials. Invest. Ophthalmol. Vis. Sci. 2007;48(13):2583.

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

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Purpose:: Currently there is no standard or efficient way for transferring and tracking images over the Internet. E-mails and direct server upload have significant limitations. Firewalls at the universities are often restrictive. We sought to design and evaluate the performance of robust automated transfer system to serve for the purposes of the clinical trials.

Methods:: The design included developing of software utilizing several integrated fast programming languages. Separate modules with friendly graphical user interface were created: submitting module - for accepting, verifying, transferring the images; central storage space module; control module - for tracking and accepting the images and image database module. Images were encrypted before submission and automatically submitted based on predetermined preference. An inventory report for the images was generated automatically and submitted separately to the Coordinating and Image Reading center.

Results:: The modules were tested for reliability and speed for uploading and tracking the images. Reproducibly was also assessed in a separate sessions. 150 color images with resolution of 640X480 pixels and file size of 900 Kb. were selected. Images were automatically transferred to a remote central server in Europe from multiple university network computers in USA. Average time for transfer of 10 images was 40 sec. (range 32-65 sec.) in 50 separate sessions. There were diurnal and traffic dependent speed variations. The transfer of images was 100 % successful in all sessions. No image was lost, corrupted or unaccounted for during the Internet transfer. Notification for all the images from the European server were received within 1 min in US from the tracking module.

Conclusions:: A robust, reliable automated image transfer platform was designed for sending images to remote Reading center or for teleconsult over the Internet. Once images are generated they are automatically handled and reliably delivered to remote computer.

Keywords: retina • clinical (human) or epidemiologic studies: systems/equipment/techniques • imaging/image analysis: clinical 

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