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.

• Highlights advancements in morphological filtering for contrast and edge enhancement of retinal images followed by optic cup/disc segmentation
• Features simulation results on more than 30 cases of Glaucoma with varying abnormalities and severities
• Provides remedial solutions of machine learning and a range of novel solutions in the domain of biomedical imaging for CAD in Glaucoma