Diabetes and Fundus OCT brings together a stellar cast of authors who review the computer-aided diagnostic (CAD) systems developed to diagnose non-proliferative diabetic retinopathy in an automated fashion using Fundus and OCTA images. Academic researchers, bioengineers, new investigators and students interested in diabetes and retinopathy need an authoritative reference to bring this multidisciplinary field together to help reduce the amount of time spent on source-searching and instead focus on actual research and the clinical application. This reference depicts the current clinical understanding of diabetic retinopathy, along with the many scientific advances in understanding this condition.
As the role of optical coherence tomography (OCT) in the assessment and management of diabetic retinopathy has become significant in understanding the vireo retinal relationships and the internal architecture of the retina, this information is more critical than ever.
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Table of Contents
1. Computer Aided Diagnosis System Based on a Comprehensive Local Features Analysis for Early Diabetic Retinopathy Detection using OCTA
2. Deep Learning Approach for Classification of Eye Diseases Based on Color Fundus Images
3. Fundus Retinal Image Analyses for Screening and Diagnosing Diabetic Retinopathy, Macular edema, and Glaucoma Disorders
4. Mobile Phone Based Diabetic Retinopathy Detection System
5. Computer Aided Diagnosis of Age Related Macular Degeneration by OCT, Fundus Image Analysis
6. Retinal Diseases Diagnosis Based on Optical Coherence Tomography Angiography (OCTA)
7. Optical Coherence Tomography: A Review
8. An Accountable Saliency-Oriented Data-Driven Approach to Diabetic Retinopathy Detection
9. Machine Learning Based Abnormalities Detection In Retinal Fundus Images
10. Optical Coherence Tomography Angiography of Retinal Vascular Diseases
11. Screening of The Diabetic Retinopathy In Engineering
12. Optical Coherence Tomography Angiography In Type 3 Neovascularization
13. Diabetic Retinopathy Detection in Ocular Images by Dictionary Learning
14. Lesion Detection Using Segmented Structure Of Retina
Authors
Ayman S. El-Baz University of Louisville. Dr. El-Baz is a Professor, University Scholar, and Chair of the Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master's degrees in Electrical Engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contributions to the field of biomedical translational research. Dr. El-Baz has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 450 technical articles (105 journals, 15 books, 50 book chapters, 175 refereed-conference papers, 100 abstracts, and 15 US patents). Jasjit Suri Chairman, AtheroPoint LLC.Dr. Jasjit Suri, PhD, MBA, is an innovator, visionary, scientist, and internationally known world leader. Dr Suri received the Director General's Gold medal in 1980 and Fellow of (i) American Institute of Medical and Biological Engineering, awarded by the National Academy of Sciences, Washington DC, (ii) Institute of Electrical and Electronics Engineers, (iii) American Institute of Ultrasound in Medicine, (iv) Society of Vascular Medicine, (v) Asia Pacific Vascular Society, and (vi) Asia Association of Artificial Intelligence. Dr. Suri was honored with life time achievement awards by Marcus, NJ, USA and Graphics Era University, Dehradun, India. He has published nearly 300 peer-reviewed Artificial Intelligence articles, nearly 2000 Google Scholar Publications, 100 books, and 100 innovations/trademarks leading to an H-index of nearly 100 with about 43,000 citations. He has held positions as chairman of AtheroPoint, CA, USA, IEEE Denver section, Colorado, USA, and advisory board member to healthcare industries and several universities in the United States of America and abroad.
