Main description:

Computer-Aided Diagnosis of Glaucoma using Morphological Filters and Machine Learning provides a focused research-based case-study of CAD of glaucoma using advanced image processing and machine learning algorithms. The book discusses relevant, state-of-the-art solutions and existing challenges, along with the steps needed to develop a CAD methodology as a projected solution. Different cases of vision disorders specific to Glaucoma are presented with results evaluated by various image quality assessment metrics and opinions from medical practitioners.

Contents:

1. Introduction
2. Cad of glaucoma
3. Evolution in cad of glaucoma
4. State of art techniques for cad of glaucoma
5. Design methodology for cad of glaucoma
6. Enhancement of retinal fundus images using morphological filters
7. Segmentation and localization of enhanced retinal images
8. Results and discussions: Enhancement and segmentation of retinal images
9. Feature extraction and classification for automated glaucoma diagnosis
10. Results and discussions: Feature extraction and classification
11. Conclusions and future research