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A region growing and local adaptive thresholding-based optic disc detection.

Tariq M Khan1, Mehwish Mehmood1, Syed S Naqvi1

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Summary
This summary is machine-generated.

This study introduces a fast and robust method for automatic optic disc (OD) localization and segmentation. The novel approach significantly improves accuracy and sensitivity in detecting the optic disc in retinal images.

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Computer Vision

Background:

  • Accurate optic disc (OD) localization and segmentation are crucial for diagnosing various eye conditions.
  • Existing methods struggle with variations in OD appearance and size among individuals.

Purpose of the Study:

  • To develop a novel, fast, and robust automatic method for optic disc localization and segmentation.
  • To enhance the accuracy and sensitivity of optic disc detection in retinal images.

Main Methods:

  • Image enhancement via de-hazing, followed by cropping around the optic disc region.
  • Utilizing the V channel in the HSV domain for optic disc detection.
  • Vessel extraction using a multi-scale line detector, removal via Laplace Transform, and subsequent binarization using local adaptive thresholding and region growing.
  • Employing region properties (eccentricity, area) and ellipse fitting for true OD region detection.

Main Results:

  • The proposed method demonstrates high accuracy and sensitivity in optic disc localization and segmentation.
  • Achieved superior performance compared to existing state-of-the-art methods on multiple datasets.

Conclusions:

  • The developed method offers a significant advancement in automated optic disc analysis.
  • This approach provides a reliable tool for clinical applications requiring precise optic disc segmentation.