Abstract: A multivariable artificial intelligence-based monitoring system for early detection of glaucoma and method thereof. The multivariable artificial intelligence system comprises a computing device having a control unit and one or more non-transitory storage devices for storing instructions to be executed by the control unit. The computing device is in communication with an application server via a network. The computing device includes an input module, an image enhancing module, a feature extraction module, a post image processing module, and a parameter selection module. The proposed multivariable artificial intelligence system provides a deep learning architecture to segment the optic disc and optic cup in two ways using two different networks termed multi spatial attention feature fusion network (MSAFF-Net) and multi dilated edge extraction network (MDEE-Net) respectively.

Abstract: A multivariable artificial intelligence-based monitoring system for early detection of glaucoma and method thereof. The multivariable artificial intelligence system comprises a computing device having a control unit and one or more non-transitory storage devices for storing instructions to be executed by the control unit. The computing device is in communication with an application server via a network. The computing device includes an input module, an image enhancing module, a feature extraction module, a post image processing module, and a parameter selection module. The proposed multivariable artificial intelligence system provides a deep learning architecture to segment the optic disc and optic cup in two ways using two different networks termed Multi Spatial Attention Feature Fusion Network (MSAFF-Net) and Multi Dilated Edge Extraction Network (MDEE-Net) respectively.