Open Access
1 July 2010 Improving image segmentation performance and quantitative analysis via a computer-aided grading methodology for optical coherence tomography retinal image analysis
Delia Cabrera DeBuc, Harry M. Salinas, Sudarshan Ranganathan, Erika Tátrai, Wei Gao, Meixiao Shen, Jianhua Wang, Gabor Márk Somfai M.D., Carmen A. Puliafito M.D.
Author Affiliations +
Abstract
We demonstrate quantitative analysis and error correction of optical coherence tomography (OCT) retinal images by using a custom-built, computer-aided grading methodology. A total of 60 Stratus OCT (Carl Zeiss Meditec, Dublin, California) B-scans collected from ten normal healthy eyes are analyzed by two independent graders. The average retinal thickness per macular region is compared with the automated Stratus OCT results. Intergrader and intragrader reproducibility is calculated by Bland-Altman plots of the mean difference between both gradings and by Pearson correlation coefficients. In addition, the correlation between Stratus OCT and our methodology-derived thickness is also presented. The mean thickness difference between Stratus OCT and our methodology is 6.53 µm and 26.71 µm when using the inner segment/outer segment (IS/OS) junction and outer segment/retinal pigment epithelium (OS/RPE) junction as the outer retinal border, respectively. Overall, the median of the thickness differences as a percentage of the mean thickness is less than 1% and 2% for the intragrader and intergrader reproducibility test, respectively. The measurement accuracy range of the OCT retinal image analysis (OCTRIMA) algorithm is between 0.27 and 1.47 µm and 0.6 and 1.76 µm for the intragrader and intergrader reproducibility tests, respectively. Pearson correlation coefficients demonstrate R2>0.98 for all Early Treatment Diabetic Retinopathy Study (ETDRS) regions. Our methodology facilitates a more robust and localized quantification of the retinal structure in normal healthy controls and patients with clinically significant intraretinal features.
©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)
Delia Cabrera DeBuc, Harry M. Salinas, Sudarshan Ranganathan, Erika Tátrai, Wei Gao, Meixiao Shen, Jianhua Wang, Gabor Márk Somfai M.D., and Carmen A. Puliafito M.D. "Improving image segmentation performance and quantitative analysis via a computer-aided grading methodology for optical coherence tomography retinal image analysis," Journal of Biomedical Optics 15(4), 046015 (1 July 2010). https://doi.org/10.1117/1.3470116
Published: 1 July 2010
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CITATIONS
Cited by 25 scholarly publications.
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KEYWORDS
Optical coherence tomography

Image segmentation

Retina

Quantitative analysis

Image analysis

Imaging systems

Control systems

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