1st Edition
Automated Image Detection of Retinal Pathology
Introduction
Why Automated Image Detection of Retinal Pathology?
Automated Assessment of Retinal Eye Disease
Diabetic Retinopathy and Public Health
Introduction
The pandemic of diabetes and its complications
Retinal structure and function
Definition and description
Classification of Diabetic Retinopathy
Differential Diagnosis of Diabetic Retinopathy
Systemic Associations of Diabetic Retinopathy
Pathogenesis
Treatment
Screening
Conclusion
Detecting Retinal Pathology Automatically with Special Emphasis on Diabetic Retinopathy
Historical aside
Approaches to computer (aided) diagnosis
Detection of diabetic retinopathy lesions
Detection of lesions and segmentation of retinal anatomy
Detection and staging of diabetic retinopathy: pixel to patient
Directions for research
Finding a Role for Computer-Aided Early Diagnosis of Diabetic Retinopathy
Mass Examinations of Eyes in Diabetes
Developing and Defending a Risk Reduction Programme
Assessing Accuracy of a Diagnostic Test
Improving Detection of Diabetic Retinopathy
Measuring Outcomes of Risk Reduction Programmes
User Experiences of Computer-Aided Diagnosis
Planning a Study to Evaluate Accuracy
Conclusion
Retinal Markers for Early Detection of Eye Disease
Abstract
Introduction
Non-Proliferative Diabetic Retinopathy
Chapter Overview
Related Works on Identification of Retinal Exudates and the Optic Disc
Preprocessing
Pixel-Level Exudate Recognition
Application of Pixel-Level Exudate Recognition on the Whole Retinal Image
Locating the Optic Disc in Retinal Images
Conclusion
Automated Microaneurysm Detection for Screening
Characteristics of microaneurysms and dot-haemorrhages
History of Automated Microaneurysm Detection
Microaneurysm Detection in Colour Retinal Images
The Waikato Automated Microaneurysm Detector
Issues for Microaneurysm Detection
Research Application of Microaneurysm Detection
Conclusion
Retinal Vascular Changes as Biomarkers of Systemic Cardiovascular Diseases
Introduction
Early Description of Retinal Vascular Changes
Retinal Vascular Imaging
Retinal Vascular Changes and Cardiovascular Disease
Retinal Vascular Changes and Metabolic Diseases
Retinal Vascular Changes and other Systemic Diseases
Genetic Associations of Retinal Vascular Changes
Conclusion
Segmentation of Retinal Vasculature Using Wavelets and Supervised Classification: Theory and Implementation
Introduction
Theoretical Background
Segmentation Using the 2-D Gabor Wavelet and Supervised Classification
Implementation and Graphical User Interface
Experimental Results
Conclusion
Determining Retinal Vessel Widths and Detection of Width Changes
Identifying Blood Vessels
Vessel Models
Vessel Extraction Methods
Can’s Vessel Extraction Algorithm
Measuring Vessel Width
Precise Boundary Detection
Continuous Vessel Models with Spline-based Ribbons
Estimation of Vessel Boundaries using Snakes
Vessel Width Change Detection
Conclusion
Geometrical and Topological Analysis of Vascular Branches from Fundus Retinal Images
Introduction
Geometry of Vessel Segments and Bifurcations
Vessel Diameter Measurements from Retinal Images
Clinical Findings from Retinal Vascular Geometry
Topology of the Vascular Tree
Automated Segmentation and Analysis of Retinal Fundus Images
Clinical Findings from Retinal Vascular Topology
Conclusion
Tele-Diabetic Retinopathy Screening and Image Based Clinical Decision Support
Introduction
Telemedicine
Telemedicine screening for Diabetic retinopathy
Image-based clinical decision support systems
Conclusion
Biography
Herbert Jelinek, Charles Stuart University, Albury, New South Wales, Australia
Michael J. Cree, University of Waikato, Hamilton, New Zealand
