Classification of Multidimensional Visual Field Data for Glaucoma Diagnosis

Visual field loss and glaucomatous optic disk damage are typical findings in glaucoma disease. The question is examined how the stages of optic disk damage are reflected in different patterns of visual field loss. Due to the complex situation of 59-dimensional visual field data and the assumed non-linear association with the optic disk diagnosis, a neural network was used to classify visual field patterns into morphometric stages of glaucoma. Good classification results were achieved with a backpropagation network consisting of 59 input neurons and 15 neurons in two hidden layers.