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    This study presents an automated method for detecting neovascularization in the optic disc region (NVD) in retinal images. Early detection of NVD, a key indicator of proliferative diabetic retinopathy, is crucial for preventing vision loss.

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    Area of Science:

    • Ophthalmology
    • Medical Imaging
    • Computer Vision

    Background:

    • Neovascularization in the optic disc region (NVD) is a critical indicator for proliferative diabetic retinopathy.
    • The presence of new, fragile retinal vessels (NV) poses a significant risk of sudden vision loss.
    • Accurate and timely detection of NV is essential for effective patient management.

    Purpose of the Study:

    • To develop and evaluate an automated image processing procedure for NVD detection in color fundus retinal images.
    • To improve the accuracy and efficiency of NVD identification compared to manual methods.
    • To aid in the early diagnosis and management of proliferative diabetic retinopathy.

    Main Methods:

    • Vessel segmentation using multilevel Gabor filtering.
    • Extraction of vessel morphological and texture features.
    • Image classification using a support vector machine (SVM) classifier.
    • Feature selection to reduce dimensionality from 42 features to 18 optimal features.

    Main Results:

    • The automated system achieved an average accuracy of 95.23% on a dataset of 424 retinal images (134 NVD, 290 non-NVD).
    • High performance metrics were reported: specificity of 96.30%, sensitivity of 92.90%, and an area under the curve (AUC) of 98.51%.
    • The feature selection process effectively identified the most discriminative features for NVD classification.

    Conclusions:

    • The proposed automated method demonstrates high accuracy and reliability for NVD detection in retinal images.
    • This technique has the potential to significantly assist ophthalmologists in diagnosing and monitoring diabetic retinopathy.
    • Further validation on larger datasets is recommended for clinical implementation.