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Doppler Optical Coherence Tomography of Retinal Circulation
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A novel method for retinal optic disc detection using bat meta-heuristic algorithm.

Ahmad S Abdullah1,2, Yasa Ekşioğlu Özok3, Javad Rahebi4

  • 1Altinbas University, Istanbul, Turkey. Ahmed.alogaidi28@gmail.com.

Medical & Biological Engineering & Computing
|May 10, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a novel bat algorithm (BA) optimized method for accurate optic disc detection in retinal images. The approach enhances segmentation for conditions like glaucoma and diabetic retinopathy, achieving high accuracy in under 2.1 seconds.

Keywords:
AccuracyBat algorithmGray scale imagingOptic disc segmentationRetinal image

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Computer Vision

Background:

  • Optic disc detection is crucial for diagnosing glaucoma and diabetic retinopathy.
  • Retinal image analysis presents challenges due to variations in optic disc appearance and surrounding vasculature.

Purpose of the Study:

  • To propose a novel, optimized method for accurate optic disc segmentation in retinal images.
  • To improve the efficiency and accuracy of optic disc detection for clinical applications.

Main Methods:

  • A novel preprocessing technique using grayscale conversion and morphological operations.
  • Bat Algorithm (BA) optimization for determining optimal threshold values.
  • Ellipse fitting using the least squares method for boundary refinement.

Main Results:

  • Achieved optic disc segmentation accuracy between 96.6% and 99.91%.
  • Demonstrated high overlap rates ranging from 78.5% to 88.2% across six datasets.
  • Processed retinal images in under 2.1 seconds per image.

Conclusions:

  • The proposed BA-optimized method provides accurate and efficient optic disc segmentation.
  • The technique is effective for both healthy and pathological retinal images.
  • Offers a valuable tool for the early detection and management of eye diseases.