Abstract

We describe an image processing system which we have developed to align autofluorescence and high-magnification images taken with a laser scanning ophthalmoscope. The low signal to noise ratio of these images makes pattern recognition a non-trivial task. However, once n images are aligned and averaged, the noise levels drop by a factor of √n and the image quality is improved. We include examples of autofluorescence images and images of the cone photoreceptor mosaic obtained using this system.

© Optical Society of America

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References

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  1. F. C. Delori, "Spectrophotometer for noninvasive measurement of intrinsic fluorescence and reflectance of the ocular fundus," Appl. Opt. 33, 7439-7452 (1994).
    [CrossRef] [PubMed]
  2. A. von Ruckman, F. W. Fitzke and A. C. Bird, "Distribution of fundus autofluorescence with a scanning laser ophthalmoscope," Br. J. Ophthal. 79, 407-412 (1995).
    [CrossRef]
  3. A. R. Wade, and F. W. Fitzke, " In-vivo imaging of the human cone photoreceptor mosaic using a confocal LSO," Lasers and Light in Ophthalmology 1998. (In Press).
  4. L. G. Brown, "A survey of image registration techniques," Computing Surveys 24, 325-376 (1992).
    [CrossRef]

Other

F. C. Delori, "Spectrophotometer for noninvasive measurement of intrinsic fluorescence and reflectance of the ocular fundus," Appl. Opt. 33, 7439-7452 (1994).
[CrossRef] [PubMed]

A. von Ruckman, F. W. Fitzke and A. C. Bird, "Distribution of fundus autofluorescence with a scanning laser ophthalmoscope," Br. J. Ophthal. 79, 407-412 (1995).
[CrossRef]

A. R. Wade, and F. W. Fitzke, " In-vivo imaging of the human cone photoreceptor mosaic using a confocal LSO," Lasers and Light in Ophthalmology 1998. (In Press).

L. G. Brown, "A survey of image registration techniques," Computing Surveys 24, 325-376 (1992).
[CrossRef]

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Figures (4)

Fig. 1.
Fig. 1.

Stages in image averaging procedure

Fig. 2.
Fig. 2.

Raw SLO video frame

Fig. 3.
Fig. 3.

Effects of increasing blurring kernel size and noise levels on image alignment accuracy. An image set with SNR of -14dB was used to test the effect of blurring kernel size.

Fig. 4.
Fig. 4.

Examples of processed images. Top - High-magnification cone photoreceptor imaging. Bottom - IFA imaging

Equations (3)

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r = x = 0 X y = 0 Y M ( x , y ) I ( p x , q y )
r = X Y I M I M [ XY I 2 ( I ) 2 ] [ XY M 2 ( M ) 2 ]
SNR = 10 log 10 ( σ 2 ( signal ) σ 2 ( noise ) )

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