April 2010
Volume 51, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2010
Image Extraction and Advanced Visualization of Oct Retinal Images
Author Affiliations & Notes
  • B. Madow
    Ophthalmology, University of South Florida, Tampa, Florida
  • Footnotes
    Commercial Relationships  B. Madow, None.
  • Footnotes
    Support  None.
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 1787. doi:
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      B. Madow; Image Extraction and Advanced Visualization of Oct Retinal Images. Invest. Ophthalmol. Vis. Sci. 2010;51(13):1787.

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

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Abstract

Purpose: : To design and validate computer algorithms and create software for image extraction archiving and advanced visualization of retinal images acquired with spectral domain optical coherence tomography (OCT). The application is aimed to increase effectiveness in the clinical practice and to assist OCT image reading centers for clinical trials.

Methods: : Fast programming languages were used to design algorithms for rapid image retrieval, segmentation and display. The platform consists of multiple tiers. On the front-end there are two modes: 1) for automatic and 2) for manual insertion of demographic data and images. The core of the program consists of image presentation and clinical data comparison module. A friendly graphical user interface was created to display the OCT images and data together. Information for the right and left eye is presented separately. Selection menu for desired type of visualization with image presentation filters is also incorporated. The back-end of the platform contains fast database for image and clinical data archiving. Advanced searching capabilities allow for data mining.

Results: : The platform was tested on computer with Intel processor: Core 2 Duo, 2.5 GHz, 4 GB RAM under Microsoft Vista 32-bit operating system. One hundred sham test images with the same resolution as the original OCT images were used to test the platform. The results show very robust and instantaneous loading and display of the image sets from multiple visits (average- less than 1 sec. from 5 visits with 6 images per visit), when archived on the local hard drive. The images from left and right eye are loaded simultaneously and remain in the memory, so that flipping back and forth between the eyes does not require more loading time. The visits are chronologically presented and can be filtered based on multiple criteria. During the test the software reliably filtered visits with intraocular procedure from follow-up visits without procedure.

Conclusions: : Robust, reliable software platform for OCT image extraction, visualization and archiving was designed and validated for the purposes of clinical evaluation and OCT image reading centers.

Keywords: retina • imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • imaging/image analysis: clinical 
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