To diagnose diseases, various healthcare systems use content-predicted picture analysis and computer vision
techniques. Fundus images acquired with a fundus camera are used to detect anomalies in a human ocular perceiver. Glaucoma
is the second most common ocular perceiver disease that can lead to neurodegeneration. The main cause of this condition is said
to be an insufficient intraocular pressure within the human ocular perceiver. Glaucoma has no symptoms in its early stages and
can lead to ocular incapacitation if it is not treated. Glaucoma can be detected early enough to prevent representative vision loss.
Manual evaluation of the human ocular perceiver is a valid technique, but it is prone to human error. To identify glaucoma, we
will need image processing, artificial intelligence, and computer vision techniques.
