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Evolutionary Computing Enriched Computer-Aided Diagnosis System for Diabetic Retinopathy: A Survey.

Romany F Mansour

    IEEE Reviews in Biomedical Engineering
    |May 24, 2017
    PubMed
    Summary

    Diabetic retinopathy (DR) causes vision loss, necessitating advanced computer-aided diagnosis (CAD) systems. Evolutionary computing methods show promise for optimizing DR-CAD systems, improving early detection and diagnosis.

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    Area of Science:

    • Ophthalmology
    • Medical Imaging
    • Computer Science

    Background:

    • Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes mellitus, leading to irreversible vision loss.
    • Accurate and early diagnosis of DR is challenging due to subtle morphological changes in retinal structures.
    • Computer-aided diagnosis (CAD) systems are crucial for efficient DR detection.

    Purpose of the Study:

    • To survey and analyze existing literature on DR CAD systems.
    • To evaluate the role of traditional and evolutionary approaches in DR CAD.
    • To identify opportunities for optimizing DR CAD system components.

    Main Methods:

    • Comprehensive literature review of DR CAD systems.
    • Analysis of traditional and evolutionary computing methods (e.g., genetic algorithms, particle swarm optimization) applied to DR CAD.

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  • Evaluation of evolutionary approaches for optimizing preprocessing, segmentation, feature extraction, selection, and classification.

    • Main Results:

    • Existing DR CAD systems have undergone functional enhancements for improved accuracy.
    • Evolutionary computing methods offer significant potential for optimizing various DR CAD components.
    • These methods can enhance filter coefficients, clustering, feature selection, and classification.

    Conclusions:

    • Evolutionary computing methods are vital for optimizing DR CAD systems.
    • Optimized DR CAD systems can lead to earlier and more efficient diagnosis of diabetic retinopathy.
    • Further research into evolutionary approaches can advance DR detection and management.