Early diabetic retinopathy diagnosis based on local retinal blood vessel analysis in optical coherence tomography angiography (OCTA) images

Nabila Eladawi, Mohammed Elmogy, Fahmi Khalifa, Mohammed Ghazal, Nicola Ghazi, Ahmed Aboelfetouh, Alaa Riad, Harpal Sandhu, Shlomit Schaal, Ayman El-Baz

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


Purpose: This paper introduces a new computer-aided diagnosis (CAD) system for detecting early-stage diabetic retinopathy (DR) using optical coherence tomography angiography (OCTA) images. Methods: The proposed DR-CAD system is based on the analysis of new local features that describe both the appearance and retinal structure in OCTA images. It starts with a new segmentation approach that has the ability to extract the blood vessels from superficial and deep retinal OCTA maps. The high capability of our segmentation approach stems from using a joint Markov–Gibbs random field stochastic model integrating a 3D spatial statistical model with a first-order appearance model of the blood vessels. Following the segmentation step, three new local features are estimated from the segmented vessels and the foveal avascular zone (FAZ): (a) vessels density, (b) blood vessel calibre, and (c) width of the FAZ. To distinguish mild DR patients from normal cases, the estimated three features are used to train and test a support vector machine (SVM) classifier with the radial basis function (RBF) kernel. Results: On a cohort of 105 subjects, the presented DR-CAD system demonstrated an overall accuracy (ACC) of 94.3%, a sensitivity of 97.9%, a specificity of 87.0%, the area under the curve (AUC) of 92.4%, and a Dice similarity coefficient (DSC) of 95.8%. This in turn demonstrates the promise of the proposed CAD system as a supplemental tool for early detection of DR. Conclusion: We developed a new DR-CAD system that is capable of diagnosing DR in its early stage. The proposed system is based on extracting three different features from the segmented OCTA images, which reflect the changes in the retinal vasculature network.

Original languageEnglish (US)
Pages (from-to)4582-4599
Number of pages18
JournalMedical Physics
Issue number10
StatePublished - Oct 2018


  • early diabetic retinopathy (DR) diagnosis
  • local retinal blood vessels analysis
  • optical coherence tomography angiography (OCTA)
  • support vector machine (SVM), foveal avascular zone (FAZ)

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging


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