March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
Effects of Enhancement of Blood Vessel Contrast in OCT Fundus Images on Registration Performance
Author Affiliations & Notes
  • Ying Li
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida
  • Giovanni Gregori
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida
  • Byron L. Lam
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida
  • Philip J. Rosenfeld
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida
  • Footnotes
    Commercial Relationships  Ying Li, None; Giovanni Gregori, Carl Zeiss Meditec (F, P); Byron L. Lam, None; Philip J. Rosenfeld, Carl Zeiss Meditec (F, R)
  • Footnotes
    Support  NIH Center Core Grant P30EY014801, Research to Prevent Blindness Unrestricted Grant, Department of Defense (DOD-Grant#W81XWH-09-1-0675), Carl Zeiss Meditec.
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 2183. doi:
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    • Get Citation

      Ying Li, Giovanni Gregori, Byron L. Lam, Philip J. Rosenfeld; Effects of Enhancement of Blood Vessel Contrast in OCT Fundus Images on Registration Performance. Invest. Ophthalmol. Vis. Sci. 2012;53(14):2183.

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

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Abstract
 
Purpose:
 

To investigate the effects of blood vessels’ contrast enhancing, using a technique based on RPE segmentation, on the performance of a registration algorithm for OCT fundus images (OFIs).

 
Methods:
 

An automated algorithm, based on blood vessel features, was developed to register OFIs to each other or to other en face imaging modalities, like color fundus photography (CFP). Raster scans (200x200) acquired with a Cirrus HD-OCT were used to generate the OFIs to be registered. It is well known that enhanced OFIs, showing the blood vessels with higher contrast, can be obtained by limiting the summation of OCT intensities along the axial direction to specific retinal regions, in particular around the RPE layer.We use a very simple and fast automated algorithm to obtain a rough RPE segmentation. A window of 20 pixels above and 100 pixels below the RPE boundary is used to build the enhanced OFI. Comparisons between the performance of the registration algorithm on OFIs and enhanced OFIs were carried out in two particular settings. One is the registration between OFIs and CFPs, and the other is the montage of several partially overlapping OFIs in order to produce a larger field of view.

 
Results:
 

Registration performance was measured by the mean registration error of manually labeled matching points. The effects of enhancement of blood vessel contrast in OFIs on registration performance are summarized in Table 1.

 
Conclusions:
 

Enhancement of blood vessel contrast in OFIs, using a very simple and fast algorithm, greatly improves the performance of our registration algorithm for OFIs.  

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