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Updated: May 7, 2026

Doppler Optical Coherence Tomography of Retinal Circulation

Doppler Optical Coherence Tomography of Retinal Circulation

Published on: September 18, 2012

A novel method for optic disc localization using fast circlet transform and Chan-Vese segmentation.

S Gowthaman¹, Abhishek Das²

¹Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.

Scientific Reports

|August 26, 2025

Summary

This summary is machine-generated.

This study introduces a novel framework for accurately locating and segmenting the optic disc (OD) in retinal images, improving early disease detection. The method enhances robustness against image quality issues, crucial for diagnosing conditions like glaucoma.

Keywords:

Chan-Vese Segmentation Fast Circlet Transform Minkowski Weighted K-Means Optic Disc Localization PDE-based Inpainting Unsupervised Method

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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

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Published on: November 30, 2022

Area of Science:

Ophthalmology
Medical Image Analysis
Computer Vision

Background:

Accurate optic disc (OD) localization and segmentation are vital for early detection of ophthalmic diseases like glaucoma and diabetic retinopathy.
Existing methods face challenges including variable image quality, high noise, and poor edge information.
Robust OD analysis is essential for timely clinical intervention and disease management.

Purpose of the Study:

To develop an adaptive framework for robust optic disc (OD) localization and segmentation in retinal images.
To overcome limitations of existing methods related to image quality and noise.
To enhance the accuracy and generalizability of OD analysis for clinical applications.

Main Methods:

An adaptive framework combining Fast Circlet Transformation (FCT) with entropy-based retinal blood vessel features for OD localization.
Minkowski weighted K-means clustering for dynamic feature importance assessment and dataset variation resilience.
Partial differential equation-based inpainting for blood vessel removal and Chan-Vese active contour model for OD segmentation refinement.

Main Results:

Extensive evaluations across DRISHTI-GS, DRIONS-DB, IDRID, and ORIGA datasets demonstrated localization efficacy.
Achieved high segmentation performance with Dice coefficients of 0.94-0.95 and Jaccard indices of 0.9 on ORIGA and DRISHTI-GS.
The proposed method shows significant robustness and generalizability in retinal image analysis.

Conclusions:

The developed adaptive framework provides a robust solution for optic disc (OD) localization and segmentation.
The integration of FCT, entropy-based features, and advanced segmentation techniques addresses key challenges in retinal image analysis.
The method's strong performance highlights its potential for widespread clinical application in diagnosing ophthalmic diseases.