May 2008
Volume 49, Issue 13
ARVO Annual Meeting Abstract  |   May 2008
Comparison of Polarization Techniques for Enhanced Fundus Imaging
Author Affiliations & Notes
  • C. J. Cookson
    Physics & Astronomy/School of Optometry, University of Waterloo, Waterloo, Ontario, Canada
  • J. M. Bueno
    Laboratorio de Optica, Universidad de Murcia, Murica, Spain
  • M. L. Kisilak
    Physics & Astronomy/School of Optometry, University of Waterloo, Waterloo, Ontario, Canada
  • J. J. Hunter
    Center for Visual Science, University of Rochester, Rochester, New York
  • M. C. W. Campbell
    Physics & Astronomy/School of Optometry, University of Waterloo, Waterloo, Ontario, Canada
    GWPI, Waterloo, Ontario, Canada
  • Footnotes
    Commercial Relationships  C.J. Cookson, None; J.M. Bueno, N/A, P; M.L. Kisilak, None; J.J. Hunter, N/A, P; M.C.W. Campbell, N/A, P.
  • Footnotes
    Support  Centre for Photonics, Ontario; NSERC, Canada, Ontario Photonics Consortium
Investigative Ophthalmology & Visual Science May 2008, Vol.49, 4212. doi:
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    • Get Citation

      C. J. Cookson, J. M. Bueno, M. L. Kisilak, J. J. Hunter, M. C. W. Campbell; Comparison of Polarization Techniques for Enhanced Fundus Imaging. Invest. Ophthalmol. Vis. Sci. 2008;49(13):4212.

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

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Purpose: : Improved visualization of retinal features aids in the detection, localization and tracking of ocular disease. A number of image improvement techniques have been developed which incorporate polarimetry into a scanning laser ophthalmoscope (SLO). We compare polarimetry methods for fundus image enhancement by applying different methods to images taken under similar conditions. We use image quality metrics to quantify improvements.

Methods: : In method 1, a generator, a linear polarizer followed by a quarter wave plate, was incorporated into a confocal SLO. For 2 young adult participants, a series of 4 images of the optic nerve head were recorded with different generator settings and used to compute the top row of the Mueller matrix for each pixel. From this, images with the maximum and minimum values of the overall image quality metrics (signal to noise ratio (max SNR image) and entropy (max entropy image)) were constructed. In method 2, the generator was set to circular polarization and an analyzer, a quarter wave plate followed by a linear polarizer was added. Subsequently, 4 fundus images were taken. From these images, the Stokes vector, S0 and the degree of polarization (DOP) were calculated for each image pixel. Originally recorded images and constructed images were examined for image quality and the quantitative metric values were compared. Features such as blood vessels, the retinal nerve fiber layer (RNFL) and the neural retinal rim were qualitatively compared.

Results: : For method 1, when compared to the same best original image, the max SNR and entropy images yielded 4% and 7% improvements for subject 1 and 11% and 17% improvements for subject 2, respectively. For method 2, the DOP image showed improvements of 2% and 1% for subjects 1 and 2 in entropy value. S0 showed increases of 8% and 6% (subject 1) and 9% and 0.3% (subject 2) for SNR and entropy respectively. Max SNR, max entropy and S0 all gave higher contrast and resolution images when compared to the DOP image, which was darker and noisier. The blood vessels are most visible in the S0, max SNR and max entropy images. Fine striations of the RNFL are most visible in the S0 image. The max SNR and max entropy images display the highest contrast of the neural retinal rim.

Conclusions: : We have reported a comparison of polarimetric techniques to improve the quality of fundus images using image quality metrics. The constructed images of method 1 and S0 of method 2 provide similar quality; however, the best technique to use is dependent on the feature being assessed.

Keywords: imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • optic nerve • optical properties 

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