Abstract
Background: Cotton-wool spots also referred as soft exudates are the early signs of complications in the eye fundus of the patients suffering from diabetic retinopathy. Early detection of exudates helps in the diagnosis of the disease and provides better medical attention.
Methods: In this paper, an automated system for the detection of soft exudates has been suggested. The system has been developed by the combination of different techniques like Scale Invariant Feature Transform (SIFT), Visual Dictionaries, K-means clustering and Support Vector Machine (SVM).
Results: The performance of the system is evaluated on a publically available dataset and AUC of 94.59% is achieved with the highest accuracy obtained is 94.59%. The experiments are also performed after mixing three datasets and AUC of 92.61% is observed with 91.94% accuracy.
Conclusion: The proposed system is easy to implement and can be used by medical experts both online and offline for referral of Cotton-wool spots in large populations. The system shows promising performance.
Keywords: Cotton-wool spots, diabetic retinopathy, eye fundus, SIFT, SVM, visual dictionary.
Current Diabetes Reviews
Title:Automated System for Referral of Cotton-Wool Spots
Volume: 14 Issue: 2
Author(s): Syed A.G. Naqvi*, Hafiz M.F. Zafar and Ihsan ul Haq
Affiliation:
- Department of Electronic Engineering, Faculty of Engineering and Technology, International Islamic University, Islamabad,Pakistan
Keywords: Cotton-wool spots, diabetic retinopathy, eye fundus, SIFT, SVM, visual dictionary.
Abstract: Background: Cotton-wool spots also referred as soft exudates are the early signs of complications in the eye fundus of the patients suffering from diabetic retinopathy. Early detection of exudates helps in the diagnosis of the disease and provides better medical attention.
Methods: In this paper, an automated system for the detection of soft exudates has been suggested. The system has been developed by the combination of different techniques like Scale Invariant Feature Transform (SIFT), Visual Dictionaries, K-means clustering and Support Vector Machine (SVM).
Results: The performance of the system is evaluated on a publically available dataset and AUC of 94.59% is achieved with the highest accuracy obtained is 94.59%. The experiments are also performed after mixing three datasets and AUC of 92.61% is observed with 91.94% accuracy.
Conclusion: The proposed system is easy to implement and can be used by medical experts both online and offline for referral of Cotton-wool spots in large populations. The system shows promising performance.
Export Options
About this article
Cite this article as:
Naqvi A.G. Syed*, Zafar M.F. Hafiz and ul Haq Ihsan, Automated System for Referral of Cotton-Wool Spots, Current Diabetes Reviews 2018; 14 (2) . https://dx.doi.org/10.2174/1573399812666161201114309
DOI https://dx.doi.org/10.2174/1573399812666161201114309 |
Print ISSN 1573-3998 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6417 |
![](/images/wayfinder.jpg)
- Author Guidelines
- Bentham Author Support Services (BASS)
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
- Announcements
Related Articles
-
Innovative Technologies for Oral Drug Delivery
Current Drug Delivery Metformin Beyond Diabetes: New Life for an Old Drug
Current Diabetes Reviews Flavonoids, Vascular Function and Cardiovascular Protection
Current Pharmaceutical Design Mannose-Binding Lectin Protein Deficiency Among Patients with Primary Immunodeficiency Disease Receiving IVIG Therapy
Endocrine, Metabolic & Immune Disorders - Drug Targets Initiation of Dialysis: A Mini-Review of a Changing Paradigm
Cardiovascular & Hematological Disorders-Drug Targets Post-Approval Changes in Pharmaceuticals: Regulatory Perspectives in Europe
Applied Clinical Research, Clinical Trials and Regulatory Affairs Exercise as a platform for pharmacotherapy development in cardiac diseases
Current Pharmaceutical Design Natural Products as Promising Drug Candidates for the Treatment of Alzheimer’s Disease: Molecular Mechanism Aspect
Current Neuropharmacology Chromones and their Derivatives as Radical Scavengers: A Remedy for Cell Impairment
Current Topics in Medicinal Chemistry RNA Interference and Potential Applications
Current Topics in Medicinal Chemistry Actinomycetes as a Paramount Source of Biologically Important Enzyme Inhibitors – “A Boon to Mankind”
Current Bioactive Compounds Neuroinflammation in Alzheimer’s Disease: Microglia, Molecular Participants and Therapeutic Choices
Current Alzheimer Research Prognostic Implications of Genetics in Cardiovascular Disease
Current Pharmacogenomics The Effect of Coconut Jelly with Stevia as a Natural Sweetener on Blood Glucose, Insulin and C-Peptide Responses in Twelve Healthy Subjects
Recent Patents on Food, Nutrition & Agriculture Modulating Poly (ADP-Ribose) Polymerase Activity: Potential for the Prevention and Therapy of Pathogenic Situations Involving DNA Damage and Oxidative Stress
Current Pharmaceutical Biotechnology Pharmacological Profile of SSRIs and SNRIs in the Treatment of Eating Disorders
Current Clinical Pharmacology Hepatobiliary Diseases and Insulin Resistance
Current Medicinal Chemistry Maternal Vitamin D Status and Development of Asthma and Allergy in Early Childhood
Mini-Reviews in Medicinal Chemistry Postoperative Care of the Transplanted Patient
Current Cardiology Reviews Roles of L5-7 Loop in the Structure and Chaperone Function of SsHSP14.1
Protein & Peptide Letters