Computer-Aided Diagnosis of Glaucoma using Morphological Filters and Machine Learning

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