Application of deep learning and virtual reality in ophthalmology for detection of glaucoma

Khan, Z.; Akhter, M. A.

AI has the immense caliber to perform efficiently according to the industry's needs. One of the reasons is AI's image processing technology. Since ophthalmology requires the processing of images of the eyes for different eye conditions, AI is playing a significant role in the field. It has allowed the growth of 'intelligent diagnosis' Through this study, a model will be proposed for the earliest detection of glaucoma using AI specifically Deep Learning (DL) and Virtual Reality (VR). This would help patients to begin treatment at the earliest stages to prevent complete loss of vision. The idea of designing this model as compared to more efficient yet complex techniques available in hospitals is because in the delay of glaucoma detection, precious time is lost and with it, irreparable damage is inflicted upon the eye. The diagnosis of glaucoma depends on the optic disc and surrounding retinal nerve fiber layer assessment performed by a trained professional. Therefore, the detection of glaucoma has always been limited in its economic value due to the precise skills required and its labor-intensive nature. Given the growing public health concern, especially after the COVID-19 pandemic, improvements towards the field of screening and diagnosis of glaucoma are endorsed. The proposed methodology would consist of a VR environment for obtaining information required like maximum peripheral distance combined with various inputs that would be taken for the DL model, an efficient and precise diagnosis would be expected which would highly cut the cost of performing expensive eyes tests. © 2021 IEEE.