Diabetes and Fundus OCT: Computer-Assisted Diagnosis
Editat de Ayman S. El-Baz, Jasjit S. Surien Limba Engleză Paperback – 3 apr 2020
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.
- Includes unique information for academic clinicians, researchers and bioengineers
- Provides insights needed to understand the imaging modalities involved, the unmet clinical need that is being addressed, and the engineering and technical approaches applied
- Brings together details on the retinal vasculature in diabetics as imaged by optical coherence tomography angiography and automated detection of retinal disease
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Specificații
ISBN-13: 9780128174401
ISBN-10: 0128174404
Pagini: 434
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
Seria Computer-Assisted Diagnosis
ISBN-10: 0128174404
Pagini: 434
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
Seria Computer-Assisted Diagnosis
Public țintă
Diabetes researchers, endocrinology, cardiovascular, and ophthalmology researchers; bioengineers, and bioinformatics and imaging scientists interested in diabetes.Cuprins
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
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