Jelinek / Cree Automated Image Detection of Retinal Pathology

1. Auflage 2011
ISBN: 978-1-4398-5909-4
Verlag: Taylor & Francis
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 393 Seiten

Discusses the Effect of Automated Assessment Programs on Health Care Provision
Diabetes is approaching pandemic numbers, and as an associated complication, diabetic retinopathy is also on the rise. Much about the computer-based diagnosis of this intricate illness has been discovered and proven effective in research labs. But, unfortunately, many of these advances have subsequently failed during transition from the lab to the clinic. So what is the best way to diagnose and treat retinopathy? Automated Image Detection of Retinal Pathology discusses the epidemiology of the disease, proper screening protocols, algorithm development, image processing, and feature analysis applied to the retina.

Conveys the Need for Widely Implemented Risk-Reduction Programs
Offering an array of informative examples, this book analyzes the use of automated computer techniques, such as pattern recognition, in analyzing retinal images and detecting diabetic retinopathy and its progression as well as other retinal-based diseases. It also addresses the benefits and challenges of automated health care in the field of ophthalmology. The book then details the increasing practice of telemedicine screening and other advanced applications including arteriolar-venous ratio, which has been shown to be an early indicator of cardiovascular, diabetes, and cerebrovascular risk.

Although tremendous advances have been made in this complex field, there are still many questions that remain unanswered. This book is a valuable resource for researchers looking to take retinal pathology to that next level of discovery as well as for clinicians and primary health care professionals that aim to utilize automated diagnostics as part of their health care program.

Zielgruppe

Biomedical researchers, practitioners in medical imaging, community health, pattern recognition, pattern analysis, and ophthalmology.

Autoren/Hrsg.

Jelinek, Herbert

Cree, Michael J.

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Bildgebende Verfahren, Nuklearmedizin, Strahlentherapie Radiologie, Bildgebende Verfahren
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Augenheilkunde, Optometrie

Inhaltsverzeichnis

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

Über Autor(innen)

Herbert Jelinek, Charles Stuart University, Albury, New South Wales, Australia
Michael J. Cree, University of Waikato, Hamilton, New Zealand