July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Automated Quantification of Haller's Layer in Choroid using Swept-source Optical Coherence Tomography
Author Affiliations & Notes
  • Jay Chhablani
    Vitreo-Retina, L V Prasad Eye Insititute, Hyderabad, India
  • Sushmita Rao Uppugunduri
    Vitreo-Retina, L V Prasad Eye Insititute, Hyderabad, India
  • Mohammed Abdul Rasheed
    Vitreo-Retina, L V Prasad Eye Insititute, Hyderabad, India
  • Ashutosh Richhariya
    Vitreo-Retina, L V Prasad Eye Insititute, Hyderabad, India
  • Soumya Jana
    Vitreo-Retina, L V Prasad Eye Insititute, Hyderabad, India
  • Kiran Vupparaboina
    Vitreo-Retina, L V Prasad Eye Insititute, Hyderabad, India
  • Footnotes
    Commercial Relationships   Jay Chhablani, None; Sushmita Rao Uppugunduri, None; Mohammed Abdul Rasheed, None; Ashutosh Richhariya, None; Soumya Jana, None; Kiran Vupparaboina, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 1674. doi:
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      Jay Chhablani, Sushmita Rao Uppugunduri, Mohammed Abdul Rasheed, Ashutosh Richhariya, Soumya Jana, Kiran Vupparaboina; Automated Quantification of Haller's Layer in Choroid using Swept-source Optical Coherence Tomography. Invest. Ophthalmol. Vis. Sci. 2018;59(9):1674.

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

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Abstract

Purpose : To develop an algorithm for automated quantification of Haller's layer in choroid using swept-source optical coherence tomography.

Methods : The primary contribution of this work involves defining the approach
for detecting the boundaries of Haller's and Sattler's layer. In brief, the proposed
algorithm extracts the choroidal vessel cross-sections using novel exponentiation-based
binarization. Subsequently, it detects the large choroidal vessels based on statistically
defined median criteria. Finally, the desired boundary is obtained by extrapolating and
smoothening the innermost points of the large vessel cross-sections. On 50 OCT B-scans
of 50 healthy subjects, algorithm is validated, both qualitatively and quantitatively,
vis-a-vis intra-observer variability. A thorough statistical analysis has been performed
using various metrics including Dice coefficient (DC), correlation coefficient (CC) and
absolute difference (AD).

Results : The proposed algorithm achieves a mean DC of 89.48% (SD:5.03%) which is
in close agreement with corresponding intra-observer repeatability value of 89.12%
(SD:5.68%). Similarly, proposed algorithm achieves mean AD and mean CC of 17.54 m
(SD:16.45 m) and 98.10% (SD:1.60%) which are close to corresponding intra-observer
repeatability values of 19.19 m (SD:17.69 m) and 98.58% (SD:1.12%), respectively.

Conclusions : Our study demonstrates high correlation between algorithmic and
manual delineations and can be deployed for further clinical applications to analyze
choroid in greater depth, especially in diseased eyes.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

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