Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Diabetic Retinopathy

Diabetic Retinopathy

DefinitionDiabetic retinopathy is a microvascular complication of diabetes affecting the retinal blood vessels.Risk FactorsDiabetic retinopathy is present in almost all individuals with type 1 diabetes and more than 60% of those with type 2 diabetes after two decades of disease.The risk increases with poor glycemic control, hypertension, dyslipidemia, smoking, pregnancy, and puberty.Although cataracts and glaucoma are also more frequent in people with diabetes, retinopathy remains the leading...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same journal

Correction: Shah et al. Visualization of Critical Limits and Critical Values Facilitates Interpretation. <i>Diagnostics</i> 2025, <i>15</i>, 604.

Diagnostics (Basel, Switzerland)·2026

Same journal

How Does ACR BI-RADS<sup>®</sup> v2025 Change the Radiologist's Approach? A Practical Guide Across Mammography, Ultrasound, and MRI: A Narrative Review.

Diagnostics (Basel, Switzerland)·2026

Same journal

Ultrasonographic Knee Abnormalities and Their Association with Pain in Young Male Handball and Basketball Athletes: A Cross-Sectional Study.

Diagnostics (Basel, Switzerland)·2026

Same journal

Current Landscape of Molecular Diagnostic Tests and Emerging Tools for Tuberculosis and Drug Resistance.

Diagnostics (Basel, Switzerland)·2026

Same journal

Inflammatory Signatures of Graves' Orbitopathy: Linking Thyroid Autoimmunity, Disease Activity, and Novel Hematological Biomarkers.

Diagnostics (Basel, Switzerland)·2026

Same journal

Benchmarking Multimodal Large Language Models for Cardiopulmonary Findings on Chest Radiographs: Sex-Stratified Discrimination and Operating Characteristics.

Diagnostics (Basel, Switzerland)·2026

Search research articles

Related Experiment Video

Updated: May 6, 2026

Using Retinal Imaging to Study Dementia

Using Retinal Imaging to Study Dementia

Published on: November 6, 2017

Early Diabetic Retinopathy Detection from OCT Images Using Multifractal Analysis and Multi-Layer Perceptron

Ahlem Aziz¹, Necmi Serkan Tezel¹, Seydi Kaçmaz²

¹Electrical and Electronics Engineering Department, Karabuk University, 78050 Karabuk, Türkiye.

Diagnostics (Basel, Switzerland)

|July 12, 2025

Summary

Early diabetic retinopathy (DR) detection is improved using multifractal analysis of Optical Coherence Tomography (OCT) images. Machine learning, particularly Multi-Layer Perceptron, achieved 98.02% accuracy for automated DR screening.

Keywords:

Diabetic Retinopathy Multi-Layer Perceptron (MLP)Optical Coherence Tomography (OCT)computer-aided diagnosis early detection machine learning multifractal analysis retinal imaging

More Related Videos

Application of Optical Coherence Tomography to a Mouse Model of Retinopathy

Application of Optical Coherence Tomography to a Mouse Model of Retinopathy

Published on: January 12, 2022

Author Spotlight: Understanding Retinal Vessel Resilience and Disease Progression

Author Spotlight: Understanding Retinal Vessel Resilience and Disease Progression

Published on: January 12, 2024

Related Experiment Videos

Last Updated: May 6, 2026

Using Retinal Imaging to Study Dementia

Using Retinal Imaging to Study Dementia

Published on: November 6, 2017

Application of Optical Coherence Tomography to a Mouse Model of Retinopathy

Application of Optical Coherence Tomography to a Mouse Model of Retinopathy

Published on: January 12, 2022

Author Spotlight: Understanding Retinal Vessel Resilience and Disease Progression

Author Spotlight: Understanding Retinal Vessel Resilience and Disease Progression

Published on: January 12, 2024

Area of Science:

Ophthalmology
Medical Imaging
Computational Biology

Background:

Diabetic retinopathy (DR) is a leading cause of preventable blindness globally.
Early detection and management are crucial to prevent irreversible vision loss.
Automated, non-invasive screening tools are vital for modern ophthalmology.

Purpose of the Study:

To develop a novel framework for early diabetic retinopathy detection.
To utilize multifractal analysis of Optical Coherence Tomography (OCT) images for DR screening.
To evaluate machine learning algorithms for classifying DR based on OCT data.

Main Methods:

A novel framework employing multifractal analysis of OCT images was developed.
Multifractal features were extracted using a box-counting approach.
Several machine learning algorithms were evaluated for classification performance.

Main Results:

The Multi-Layer Perceptron (MLP) algorithm demonstrated the highest predictive accuracy at 98.02%.
MLP achieved excellent performance metrics: 98.24% precision, 97.80% recall, and 98.01% F1-score.
The study successfully quantified structural irregularities in retinal tissue associated with DR.

Conclusions:

Combining OCT imaging, multifractal geometry, and deep learning offers a robust approach for DR screening.
The proposed method shows significant potential for improving early diagnosis and patient outcomes in diabetic eye care.
This automated system can aid clinical decision-making and enhance the scalability of DR screening programs.