Machine learning classifiers based on structural ONH measurements for glaucoma diagnosis
by Medha V. Wyawahare; Pradeep M. Patil
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 21, No. 4, 2016

Abstract: Glaucoma which is a leading cause of blindness in the world is not a single disease but a group of disorders with diverse clinical manifestations. If not controlled at an early stage, it causes irreversible damage to vision. Proper medication slows down or even halts its growth. Identifying glaucoma at a very early stage is vital and at the same time difficult. Careful evaluation of optic nerve head structure is extremely important for the disease diagnosis. This paper focuses on use of machine learning classifiers for automatic discrimination between healthy and glaucomatous eyes. Structural optic nerve head measurements in fundus images form the basis of the classification. We investigate and compare performance of eight machine learning classifiers in this work.

Online publication date: Mon, 15-Aug-2016

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